bump version to 6.2.8 in package.json and package-lock.json

refactor: 移除 ccw/package.json 文件并更新路径引用
fix: CodexLens model detection, hybrid search stability, and JSON logging
2026-02-06 01:54:11 +08:00 · 2025-12-23 09:49:55 +08:00 · 2025-12-23 09:47:07 +08:00 · 2025-12-22 21:49:10 +08:00 · 2025-12-22 20:17:38 +08:00 · 2025-12-22 17:55:05 +08:00
45 changed files with 4046 additions and 315 deletions
--- a/.claude/CLAUDE.md
+++ b/.claude/CLAUDE.md
@@ -3,4 +3,8 @@
 - **CLI Tools Usage**: @~/.claude/workflows/cli-tools-usage.md
 - **Coding Philosophy**: @~/.claude/workflows/coding-philosophy.md
 - **Context Requirements**: @~/.claude/workflows/context-tools.md
- **File Modification**: @~/.claude/workflows/file-modification.md
+- **File Modification**: @~/.claude/workflows/file-modification.md
+
+## Agent Execution
+
+- **Always use `run_in_background = false`** for Task tool agent calls to ensure synchronous execution and immediate result visibility
--- a/.mcp.json
+++ b/.mcp.json
@@ -9,11 +9,8 @@
      "env": {}
    },
    "ccw-tools": {
-      "command": "npx",
-      "args": [
-        "-y",
-        "ccw-mcp"
-      ],
+      "command": "ccw-mcp",
+      "args": [],
      "env": {
        "CCW_ENABLED_TOOLS": "write_file,edit_file,smart_search,core_memory"
      }
--- a/.npmignore
+++ b/.npmignore
@@ -46,7 +46,6 @@ Install-Claude.ps1
 install-remote.ps1
 *.mcp.json
 # ccw internal files
-ccw/package.json
 ccw/node_modules/
 ccw/*.md

--- a/ccw/.npmignore
+++ b/ccw/.npmignore
@@ -0,0 +1,15 @@
+# npm ignore file - overrides .gitignore for npm publish
+# dist/ is NOT excluded here so it gets published
+
+# Development files
+node_modules/
+*.log
+*.tmp
+
+# Test files
+tests/
+*.test.js
+*.spec.js
+
+# TypeScript source maps (optional, can keep for debugging)
+# *.map
--- a/ccw/package-lock.json
+++ b/ccw/package-lock.json
@@ -1,12 +1,12 @@
 {
-  "name": "ccw",
-  "version": "6.1.4",
+  "name": "claude-code-workflow",
+  "version": "6.2.6",
  "lockfileVersion": 3,
  "requires": true,
  "packages": {
    "": {
-      "name": "ccw",
-      "version": "6.1.4",
+      "name": "claude-code-workflow",
+      "version": "6.2.6",
      "license": "MIT",
      "dependencies": {
        "@modelcontextprotocol/sdk": "^1.0.4",
--- a/ccw/package.json
+++ b/ccw/package.json
@@ -1,65 +0,0 @@
-{
-  "name": "ccw",
-  "version": "6.2.0",
-  "description": "Claude Code Workflow CLI - Dashboard viewer for workflow sessions and reviews",
-  "type": "module",
-  "main": "dist/index.js",
-  "types": "dist/index.d.ts",
-  "bin": {
-    "ccw": "./bin/ccw.js",
-    "ccw-mcp": "./bin/ccw-mcp.js"
-  },
-  "scripts": {
-    "build": "tsc",
-    "dev": "tsx watch src/cli.ts",
-    "test": "node --test tests/*.test.js",
-    "test:codexlens": "node --test tests/codex-lens*.test.js",
-    "test:mcp": "node --test tests/mcp-server.test.js",
-    "lint": "eslint src/"
-  },
-  "keywords": [
-    "claude",
-    "workflow",
-    "cli",
-    "dashboard",
-    "code-review"
-  ],
-  "author": "Claude Code Workflow",
-  "license": "MIT",
-  "engines": {
-    "node": ">=16.0.0"
-  },
-  "dependencies": {
-    "@modelcontextprotocol/sdk": "^1.0.4",
-    "better-sqlite3": "^11.7.0",
-    "boxen": "^7.1.0",
-    "chalk": "^5.3.0",
-    "commander": "^11.0.0",
-    "figlet": "^1.7.0",
-    "glob": "^10.3.0",
-    "gradient-string": "^2.0.2",
-    "inquirer": "^9.2.0",
-    "open": "^9.1.0",
-    "ora": "^7.0.0",
-    "zod": "^4.1.13"
-  },
-  "files": [
-    "bin/",
-    "dist/",
-    "src/",
-    "README.md",
-    "LICENSE"
-  ],
-  "repository": {
-    "type": "git",
-    "url": "https://github.com/claude-code-workflow/ccw"
-  },
-  "devDependencies": {
-    "@types/better-sqlite3": "^7.6.12",
-    "@types/gradient-string": "^1.1.6",
-    "@types/inquirer": "^9.0.9",
-    "@types/node": "^25.0.1",
-    "tsx": "^4.21.0",
-    "typescript": "^5.9.3"
-  }
-}
--- a/ccw/src/core/lite-scanner-complete.ts
+++ b/ccw/src/core/lite-scanner-complete.ts
@@ -284,8 +284,12 @@ function normalizeTask(task: unknown): NormalizedTask | null {
  const implementation = taskObj.implementation as unknown[] | undefined;
  const modificationPoints = taskObj.modification_points as Array<{ file?: string }> | undefined;

+  // Ensure id is always a string (handle numeric IDs from JSON)
+  const rawId = taskObj.id ?? taskObj.task_id;
+  const stringId = rawId != null ? String(rawId) : 'unknown';
+
  return {
-    id: (taskObj.id as string) || (taskObj.task_id as string) || 'unknown',
+    id: stringId,
    title: (taskObj.title as string) || (taskObj.name as string) || (taskObj.summary as string) || 'Untitled Task',
    status: (status as string).toLowerCase(),
    // Preserve original fields for flexible rendering
--- a/ccw/src/core/lite-scanner.ts
+++ b/ccw/src/core/lite-scanner.ts
@@ -284,8 +284,12 @@ function normalizeTask(task: unknown): NormalizedTask | null {
  const implementation = taskObj.implementation as unknown[] | undefined;
  const modificationPoints = taskObj.modification_points as Array<{ file?: string }> | undefined;

+  // Ensure id is always a string (handle numeric IDs from JSON)
+  const rawId = taskObj.id ?? taskObj.task_id;
+  const stringId = rawId != null ? String(rawId) : 'unknown';
+
  return {
-    id: (taskObj.id as string) || (taskObj.task_id as string) || 'unknown',
+    id: stringId,
    title: (taskObj.title as string) || (taskObj.name as string) || (taskObj.summary as string) || 'Untitled Task',
    status: (status as string).toLowerCase(),
    // Preserve original fields for flexible rendering
--- a/ccw/src/core/routes/claude-routes.ts
+++ b/ccw/src/core/routes/claude-routes.ts
@@ -4,7 +4,7 @@
 * Handles all CLAUDE.md memory rules management endpoints
 */
 import type { IncomingMessage, ServerResponse } from 'http';
-import { readFileSync, writeFileSync, existsSync, readdirSync, statSync } from 'fs';
+import { readFileSync, writeFileSync, existsSync, readdirSync, statSync, unlinkSync, mkdirSync } from 'fs';
 import { join, relative } from 'path';
 import { homedir } from 'os';

@@ -453,8 +453,7 @@ function deleteClaudeFile(filePath: string): { success: boolean; error?: string
    writeFileSync(backupPath, content, 'utf8');

    // Delete original file
-    const fs = require('fs');
-    fs.unlinkSync(filePath);
+    unlinkSync(filePath);

    return { success: true };
  } catch (error) {
@@ -500,9 +499,8 @@ function createNewClaudeFile(level: 'user' | 'project' | 'module', template: str

    // Ensure directory exists
    const dir = filePath.substring(0, filePath.lastIndexOf('/') || filePath.lastIndexOf('\\'));
-    const fs = require('fs');
    if (!existsSync(dir)) {
-      fs.mkdirSync(dir, { recursive: true });
+      mkdirSync(dir, { recursive: true });
    }

    // Write file
--- a/ccw/src/core/routes/cli-routes.ts
+++ b/ccw/src/core/routes/cli-routes.ts
@@ -362,8 +362,9 @@ export async function handleCliRoutes(ctx: RouteContext): Promise<boolean> {
    const status = url.searchParams.get('status') || null;
    const category = url.searchParams.get('category') as 'user' | 'internal' | 'insight' | null;
    const search = url.searchParams.get('search') || null;
+    const recursive = url.searchParams.get('recursive') !== 'false';

-    getHistoryWithNativeInfo(projectPath, { limit, tool, status, category, search })
+    getHistoryWithNativeInfo(projectPath, { limit, tool, status, category, search, recursive })
      .then(history => {
        res.writeHead(200, { 'Content-Type': 'application/json' });
        res.end(JSON.stringify(history));
--- a/ccw/src/core/routes/codexlens-routes.ts
+++ b/ccw/src/core/routes/codexlens-routes.ts
@@ -10,11 +10,12 @@ import {
  executeCodexLens,
  checkSemanticStatus,
  installSemantic,
+  detectGpuSupport,
  uninstallCodexLens,
  cancelIndexing,
  isIndexingInProgress
 } from '../../tools/codex-lens.js';
-import type { ProgressInfo } from '../../tools/codex-lens.js';
+import type { ProgressInfo, GpuMode } from '../../tools/codex-lens.js';

 export interface RouteContext {
  pathname: string;
@@ -343,7 +344,7 @@ export async function handleCodexLensRoutes(ctx: RouteContext): Promise<boolean>
      }

      try {
-        const result = await executeCodexLens(['config-set', '--key', 'index_dir', '--value', index_dir, '--json']);
+        const result = await executeCodexLens(['config', 'set', 'index_dir', index_dir, '--json']);
        if (result.success) {
          return { success: true, message: 'Configuration updated successfully' };
        } else {
@@ -668,16 +669,43 @@ export async function handleCodexLensRoutes(ctx: RouteContext): Promise<boolean>
  }


-  // API: CodexLens Semantic Search Install (fastembed, ONNX-based, ~200MB)
+  // API: Detect GPU support for semantic search
+  if (pathname === '/api/codexlens/gpu/detect' && req.method === 'GET') {
+    try {
+      const gpuInfo = await detectGpuSupport();
+      res.writeHead(200, { 'Content-Type': 'application/json' });
+      res.end(JSON.stringify({ success: true, ...gpuInfo }));
+    } catch (err) {
+      res.writeHead(500, { 'Content-Type': 'application/json' });
+      res.end(JSON.stringify({ success: false, error: err.message }));
+    }
+    return true;
+  }
+
+  // API: CodexLens Semantic Search Install (with GPU mode support)
  if (pathname === '/api/codexlens/semantic/install' && req.method === 'POST') {
-    handlePostRequest(req, res, async () => {
+    handlePostRequest(req, res, async (body) => {
      try {
-        const result = await installSemantic();
+        // Get GPU mode from request body, default to 'cpu'
+        const gpuMode: GpuMode = body?.gpuMode || 'cpu';
+        const validModes: GpuMode[] = ['cpu', 'cuda', 'directml'];
+
+        if (!validModes.includes(gpuMode)) {
+          return { success: false, error: `Invalid GPU mode: ${gpuMode}. Valid modes: ${validModes.join(', ')}`, status: 400 };
+        }
+
+        const result = await installSemantic(gpuMode);
        if (result.success) {
          const status = await checkSemanticStatus();
+          const modeDescriptions = {
+            cpu: 'CPU (ONNX Runtime)',
+            cuda: 'NVIDIA CUDA GPU',
+            directml: 'Windows DirectML GPU'
+          };
          return {
            success: true,
-            message: 'Semantic search installed successfully (fastembed)',
+            message: `Semantic search installed successfully with ${modeDescriptions[gpuMode]}`,
+            gpuMode,
            ...status
          };
        } else {
--- a/ccw/src/core/routes/rules-routes.ts
+++ b/ccw/src/core/routes/rules-routes.ts
@@ -291,13 +291,14 @@ FOCUS AREAS: ${extractFocus || 'naming conventions, error handling, code structu
      return { error: `Unknown generation type: ${generationType}` };
    }

-    // Execute CLI tool (Gemini) with at least 10 minutes timeout
+    // Execute CLI tool (Claude) with at least 10 minutes timeout
    const result = await executeCliTool({
-      tool: 'gemini',
+      tool: 'claude',
      prompt,
      mode,
      cd: workingDir,
-      timeout: 600000 // 10 minutes
+      timeout: 600000, // 10 minutes
+      category: 'internal'
    });

    if (!result.success) {
--- a/ccw/src/core/routes/skills-routes.ts
+++ b/ccw/src/core/routes/skills-routes.ts
@@ -123,6 +123,7 @@ function getSkillsConfig(projectPath) {

            result.projectSkills.push({
              name: parsed.name || skill.name,
+              folderName: skill.name,  // Actual folder name for API queries
              description: parsed.description,
              version: parsed.version,
              allowedTools: parsed.allowedTools,
@@ -152,6 +153,7 @@ function getSkillsConfig(projectPath) {

            result.userSkills.push({
              name: parsed.name || skill.name,
+              folderName: skill.name,  // Actual folder name for API queries
              description: parsed.description,
              version: parsed.version,
              allowedTools: parsed.allowedTools,
@@ -197,6 +199,7 @@ function getSkillDetail(skillName, location, projectPath) {
    return {
      skill: {
        name: parsed.name || skillName,
+        folderName: skillName,  // Actual folder name for API queries
        description: parsed.description,
        version: parsed.version,
        allowedTools: parsed.allowedTools,
@@ -390,7 +393,7 @@ async function importSkill(sourcePath, location, projectPath, customName) {
 }

 /**
- * Generate skill via CLI tool (Gemini)
+ * Generate skill via CLI tool (Claude)
 * @param {Object} params - Generation parameters
 * @param {string} params.generationType - 'description' or 'template'
 * @param {string} params.description - Skill description from user
@@ -455,9 +458,9 @@ REQUIREMENTS:
 3. If the skill requires supporting files (e.g., templates, scripts), create them in the skill folder
 4. Ensure all files are properly formatted and follow best practices`;

-    // Execute CLI tool (Gemini) with write mode
+    // Execute CLI tool (Claude) with write mode
    const result = await executeCliTool({
-      tool: 'gemini',
+      tool: 'claude',
      prompt,
      mode: 'write',
      cd: baseDir,
@@ -515,8 +518,143 @@ export async function handleSkillsRoutes(ctx: RouteContext): Promise<boolean> {
    return true;
  }

-  // API: Get single skill detail
-  if (pathname.startsWith('/api/skills/') && req.method === 'GET' && !pathname.endsWith('/skills/')) {
+  // API: List skill directory contents
+  if (pathname.match(/^\/api\/skills\/[^/]+\/dir$/) && req.method === 'GET') {
+    const pathParts = pathname.split('/');
+    const skillName = decodeURIComponent(pathParts[3]);
+    const subPath = url.searchParams.get('subpath') || '';
+    const location = url.searchParams.get('location') || 'project';
+    const projectPathParam = url.searchParams.get('path') || initialPath;
+
+    const baseDir = location === 'project'
+      ? join(projectPathParam, '.claude', 'skills')
+      : join(homedir(), '.claude', 'skills');
+
+    const dirPath = subPath
+      ? join(baseDir, skillName, subPath)
+      : join(baseDir, skillName);
+
+    // Security check: ensure path is within skill folder
+    if (!dirPath.startsWith(join(baseDir, skillName))) {
+      res.writeHead(403, { 'Content-Type': 'application/json' });
+      res.end(JSON.stringify({ error: 'Access denied' }));
+      return true;
+    }
+
+    if (!existsSync(dirPath)) {
+      res.writeHead(404, { 'Content-Type': 'application/json' });
+      res.end(JSON.stringify({ error: 'Directory not found' }));
+      return true;
+    }
+
+    try {
+      const stat = statSync(dirPath);
+      if (!stat.isDirectory()) {
+        res.writeHead(400, { 'Content-Type': 'application/json' });
+        res.end(JSON.stringify({ error: 'Path is not a directory' }));
+        return true;
+      }
+
+      const entries = readdirSync(dirPath, { withFileTypes: true });
+      const files = entries.map(entry => ({
+        name: entry.name,
+        isDirectory: entry.isDirectory(),
+        path: subPath ? `${subPath}/${entry.name}` : entry.name
+      }));
+
+      res.writeHead(200, { 'Content-Type': 'application/json' });
+      res.end(JSON.stringify({ files, subPath, skillName }));
+    } catch (error) {
+      res.writeHead(500, { 'Content-Type': 'application/json' });
+      res.end(JSON.stringify({ error: (error as Error).message }));
+    }
+    return true;
+  }
+
+  // API: Read skill file content
+  if (pathname.match(/^\/api\/skills\/[^/]+\/file$/) && req.method === 'GET') {
+    const pathParts = pathname.split('/');
+    const skillName = decodeURIComponent(pathParts[3]);
+    const fileName = url.searchParams.get('filename');
+    const location = url.searchParams.get('location') || 'project';
+    const projectPathParam = url.searchParams.get('path') || initialPath;
+
+    if (!fileName) {
+      res.writeHead(400, { 'Content-Type': 'application/json' });
+      res.end(JSON.stringify({ error: 'filename parameter is required' }));
+      return true;
+    }
+
+    const baseDir = location === 'project'
+      ? join(projectPathParam, '.claude', 'skills')
+      : join(homedir(), '.claude', 'skills');
+
+    const filePath = join(baseDir, skillName, fileName);
+
+    // Security check: ensure file is within skill folder
+    if (!filePath.startsWith(join(baseDir, skillName))) {
+      res.writeHead(403, { 'Content-Type': 'application/json' });
+      res.end(JSON.stringify({ error: 'Access denied' }));
+      return true;
+    }
+
+    if (!existsSync(filePath)) {
+      res.writeHead(404, { 'Content-Type': 'application/json' });
+      res.end(JSON.stringify({ error: 'File not found' }));
+      return true;
+    }
+
+    try {
+      const content = readFileSync(filePath, 'utf8');
+      res.writeHead(200, { 'Content-Type': 'application/json' });
+      res.end(JSON.stringify({ content, fileName, path: filePath }));
+    } catch (error) {
+      res.writeHead(500, { 'Content-Type': 'application/json' });
+      res.end(JSON.stringify({ error: (error as Error).message }));
+    }
+    return true;
+  }
+
+  // API: Write skill file content
+  if (pathname.match(/^\/api\/skills\/[^/]+\/file$/) && req.method === 'POST') {
+    const pathParts = pathname.split('/');
+    const skillName = decodeURIComponent(pathParts[3]);
+
+    handlePostRequest(req, res, async (body) => {
+      const { fileName, content, location, projectPath: projectPathParam } = body;
+
+      if (!fileName) {
+        return { error: 'fileName is required' };
+      }
+
+      if (content === undefined) {
+        return { error: 'content is required' };
+      }
+
+      const baseDir = location === 'project'
+        ? join(projectPathParam || initialPath, '.claude', 'skills')
+        : join(homedir(), '.claude', 'skills');
+
+      const filePath = join(baseDir, skillName, fileName);
+
+      // Security check: ensure file is within skill folder
+      if (!filePath.startsWith(join(baseDir, skillName))) {
+        return { error: 'Access denied' };
+      }
+
+      try {
+        await fsPromises.writeFile(filePath, content, 'utf8');
+        return { success: true, fileName, path: filePath };
+      } catch (error) {
+        return { error: (error as Error).message };
+      }
+    });
+    return true;
+  }
+
+  // API: Get single skill detail (exclude /dir and /file sub-routes)
+  if (pathname.startsWith('/api/skills/') && req.method === 'GET' &&
+      !pathname.endsWith('/skills/') && !pathname.endsWith('/dir') && !pathname.endsWith('/file')) {
    const skillName = decodeURIComponent(pathname.replace('/api/skills/', ''));
    const location = url.searchParams.get('location') || 'project';
    const projectPathParam = url.searchParams.get('path') || initialPath;
@@ -576,7 +714,7 @@ export async function handleSkillsRoutes(ctx: RouteContext): Promise<boolean> {

        return await importSkill(sourcePath, location, projectPath, skillName);
      } else if (mode === 'cli-generate') {
-        // CLI generate mode: use Gemini to generate skill
+        // CLI generate mode: use Claude to generate skill
        if (!skillName) {
          return { error: 'Skill name is required for CLI generation mode' };
        }
--- a/ccw/src/core/routes/system-routes.ts
+++ b/ccw/src/core/routes/system-routes.ts
@@ -49,7 +49,7 @@ const VERSION_CHECK_CACHE_TTL = 3600000; // 1 hour
 */
 function getCurrentVersion(): string {
  try {
-    const packageJsonPath = join(import.meta.dirname, '../../../package.json');
+    const packageJsonPath = join(import.meta.dirname, '../../../../package.json');
    if (existsSync(packageJsonPath)) {
      const pkg = JSON.parse(readFileSync(packageJsonPath, 'utf8'));
      return pkg.version || '0.0.0';
--- a/ccw/src/templates/dashboard-js/components/cli-status.js
+++ b/ccw/src/templates/dashboard-js/components/cli-status.js
@@ -98,15 +98,17 @@ async function loadCodexLensStatus() {
    }
    window.cliToolsStatus.codexlens = {
      installed: data.ready || false,
-      version: data.version || null
+      version: data.version || null,
+      installedModels: []  // Will be populated by loadSemanticStatus
    };

    // Update CodexLens badge
    updateCodexLensBadge();

-    // If CodexLens is ready, also check semantic status
+    // If CodexLens is ready, also check semantic status and models
    if (data.ready) {
      await loadSemanticStatus();
+      await loadInstalledModels();
    }

    return data;
@@ -132,6 +134,37 @@ async function loadSemanticStatus() {
  }
 }

+/**
+ * Load installed embedding models
+ */
+async function loadInstalledModels() {
+  try {
+    const response = await fetch('/api/codexlens/models');
+    if (!response.ok) throw new Error('Failed to load models');
+    const data = await response.json();
+    
+    if (data.success && data.result && data.result.models) {
+      // Filter to only installed models
+      const installedModels = data.result.models
+        .filter(m => m.installed)
+        .map(m => m.profile);
+      
+      // Update window.cliToolsStatus
+      if (window.cliToolsStatus && window.cliToolsStatus.codexlens) {
+        window.cliToolsStatus.codexlens.installedModels = installedModels;
+        window.cliToolsStatus.codexlens.allModels = data.result.models;
+      }
+      
+      console.log('[CLI Status] Installed models:', installedModels);
+      return installedModels;
+    }
+    return [];
+  } catch (err) {
+    console.error('Failed to load installed models:', err);
+    return [];
+  }
+}
+
 // ========== Badge Update ==========
 function updateCliBadge() {
  const badge = document.getElementById('badgeCliTools');
--- a/ccw/src/templates/dashboard-js/components/hook-manager.js
+++ b/ccw/src/templates/dashboard-js/components/hook-manager.js
@@ -138,14 +138,14 @@ const HOOK_TEMPLATES = {
    category: 'memory',
    timeout: 5000
  },
-  // Session Context - Fires once per session at startup
-  // Uses state file to detect first prompt, only fires once
+  // Session Context - Progressive disclosure based on session state
+  // First prompt: returns cluster overview, subsequent: intent-matched sessions
  'session-context': {
    event: 'UserPromptSubmit',
    matcher: '',
-    command: 'bash',
-    args: ['-c', 'STATE_FILE="/tmp/.ccw-session-$CLAUDE_SESSION_ID"; [ -f "$STATE_FILE" ] && exit 0; touch "$STATE_FILE"; curl -s -X POST -H "Content-Type: application/json" -d "{\\"sessionId\\":\\"$CLAUDE_SESSION_ID\\"}" http://localhost:3456/api/hook/session-context 2>/dev/null | jq -r ".content // empty"'],
-    description: 'Load session context once at startup (cluster overview)',
+    command: 'ccw',
+    args: ['hook', 'session-context', '--stdin'],
+    description: 'Progressive session context (cluster overview → intent matching)',
    category: 'context',
    timeout: 5000
  }
--- a/ccw/src/templates/dashboard-js/components/mcp-manager.js
+++ b/ccw/src/templates/dashboard-js/components/mcp-manager.js
@@ -946,20 +946,15 @@ function setCcwProjectRootToCurrent() {
 }

 // Build CCW Tools config with selected tools
-// Uses isWindowsPlatform from state.js to generate platform-appropriate commands
+// Uses globally installed ccw-mcp command (from claude-code-workflow package)
 function buildCcwToolsConfig(selectedTools, pathConfig = {}) {
  const { projectRoot, allowedDirs } = pathConfig;
-  // Windows requires 'cmd /c' wrapper to execute npx
-  // Other platforms (macOS, Linux) can run npx directly
-  const config = isWindowsPlatform
-    ? {
-        command: "cmd",
-        args: ["/c", "npx", "-y", "ccw-mcp"]
-      }
-    : {
-        command: "npx",
-        args: ["-y", "ccw-mcp"]
-      };
+  // Use globally installed ccw-mcp command directly
+  // Requires: npm install -g claude-code-workflow
+  const config = {
+    command: "ccw-mcp",
+    args: []
+  };

  // Add env if not all tools or not default 4 core tools
  const coreTools = ['write_file', 'edit_file', 'codex_lens', 'smart_search'];
--- a/ccw/src/templates/dashboard-js/i18n.js
+++ b/ccw/src/templates/dashboard-js/i18n.js
@@ -23,6 +23,9 @@ const i18n = {
    'common.loading': 'Loading...',
    'common.error': 'Error',
    'common.success': 'Success',
+    'common.retry': 'Retry',
+    'common.refresh': 'Refresh',
+    'common.minutes': 'minutes',

    // Header
    'header.project': 'Project:',
@@ -277,8 +280,17 @@ const i18n = {
    'codexlens.installDeps': 'Install Dependencies',
    'codexlens.installDepsPrompt': 'Would you like to install them now? (This may take a few minutes)\n\nClick "Cancel" to create FTS index only.',
    'codexlens.installingDeps': 'Installing dependencies...',
+    'codexlens.installingMode': 'Installing with',
    'codexlens.depsInstalled': 'Dependencies installed successfully',
    'codexlens.depsInstallFailed': 'Failed to install dependencies',
+
+    // GPU Mode Selection
+    'codexlens.selectGpuMode': 'Select acceleration mode',
+    'codexlens.cpuModeDesc': 'Standard CPU processing',
+    'codexlens.directmlModeDesc': 'Windows GPU (NVIDIA/AMD/Intel)',
+    'codexlens.cudaModeDesc': 'NVIDIA GPU (requires CUDA Toolkit)',
+    'common.recommended': 'Recommended',
+    'common.unavailable': 'Unavailable',
    'codexlens.modelManagement': 'Model Management',
    'codexlens.loadingModels': 'Loading models...',
    'codexlens.downloadModel': 'Download',
@@ -293,6 +305,35 @@ const i18n = {
    'codexlens.modelListError': 'Failed to load models',
    'codexlens.noModelsAvailable': 'No models available',

+    // Model Download Progress
+    'codexlens.downloadingModel': 'Downloading',
+    'codexlens.connectingToHuggingFace': 'Connecting to Hugging Face...',
+    'codexlens.downloadTimeEstimate': 'Estimated time',
+    'codexlens.manualDownloadHint': 'Manual download',
+    'codexlens.downloadingModelFiles': 'Downloading model files...',
+    'codexlens.downloadingWeights': 'Downloading model weights...',
+    'codexlens.downloadingTokenizer': 'Downloading tokenizer...',
+    'codexlens.verifyingModel': 'Verifying model...',
+    'codexlens.finalizingDownload': 'Finalizing...',
+    'codexlens.downloadComplete': 'Download complete!',
+    'codexlens.downloadFailed': 'Download failed',
+    'codexlens.manualDownloadOptions': 'Manual download options',
+    'codexlens.cliDownload': 'CLI',
+    'codexlens.huggingfaceDownload': 'Hugging Face',
+    'codexlens.downloadCanceled': 'Download canceled',
+
+    // Manual Download Guide
+    'codexlens.manualDownloadGuide': 'Manual Download Guide',
+    'codexlens.cliMethod': 'Command Line (Recommended)',
+    'codexlens.cliMethodDesc': 'Run in terminal with progress display:',
+    'codexlens.pythonMethod': 'Python Script',
+    'codexlens.pythonMethodDesc': 'Pre-download model using Python:',
+    'codexlens.hfHubMethod': 'Hugging Face Hub CLI',
+    'codexlens.hfHubMethodDesc': 'Download using huggingface-cli with resume support:',
+    'codexlens.modelLinks': 'Direct Model Links',
+    'codexlens.cacheLocation': 'Model Storage Location',
+    'common.copied': 'Copied to clipboard',
+
    // CodexLens Indexing Progress
    'codexlens.indexing': 'Indexing',
    'codexlens.indexingDesc': 'Building code index for workspace',
@@ -302,6 +343,43 @@ const i18n = {
    'codexlens.indexSuccess': 'Index created successfully',
    'codexlens.indexFailed': 'Indexing failed',

+    // CodexLens Install
+    'codexlens.installDesc': 'Python-based code indexing engine',
+    'codexlens.whatWillBeInstalled': 'What will be installed:',
+    'codexlens.pythonVenv': 'Python virtual environment',
+    'codexlens.pythonVenvDesc': 'Isolated Python environment',
+    'codexlens.codexlensPackage': 'CodexLens package',
+    'codexlens.codexlensPackageDesc': 'Code indexing and search engine',
+    'codexlens.sqliteFtsDesc': 'Full-text search database',
+    'codexlens.installLocation': 'Installation Location',
+    'codexlens.installTime': 'First installation may take 2-3 minutes to download and setup Python packages.',
+    'codexlens.startingInstall': 'Starting installation...',
+    'codexlens.installing': 'Installing...',
+    'codexlens.creatingVenv': 'Creating virtual environment...',
+    'codexlens.installingPip': 'Installing pip packages...',
+    'codexlens.installingPackage': 'Installing CodexLens package...',
+    'codexlens.settingUpDeps': 'Setting up Python dependencies...',
+    'codexlens.installComplete': 'Installation complete!',
+    'codexlens.installSuccess': 'CodexLens installed successfully!',
+    'codexlens.installNow': 'Install Now',
+    'codexlens.accelerator': 'Accelerator',
+
+    // CodexLens Uninstall
+    'codexlens.uninstall': 'Uninstall',
+    'codexlens.uninstallDesc': 'Remove CodexLens and all data',
+    'codexlens.whatWillBeRemoved': 'What will be removed:',
+    'codexlens.removeVenv': 'Virtual environment at ~/.codexlens/venv',
+    'codexlens.removeData': 'All CodexLens indexed data and databases',
+    'codexlens.removeConfig': 'Configuration and semantic search models',
+    'codexlens.removing': 'Removing files...',
+    'codexlens.uninstalling': 'Uninstalling...',
+    'codexlens.removingVenv': 'Removing virtual environment...',
+    'codexlens.removingData': 'Deleting indexed data...',
+    'codexlens.removingConfig': 'Cleaning up configuration...',
+    'codexlens.finalizing': 'Finalizing removal...',
+    'codexlens.uninstallComplete': 'Uninstallation complete!',
+    'codexlens.uninstallSuccess': 'CodexLens uninstalled successfully!',
+
    // Index Manager
    'index.manager': 'Index Manager',
    'index.projects': 'Projects',
@@ -333,9 +411,12 @@ const i18n = {
    'index.fullDesc': 'FTS + Semantic search (recommended)',
    'index.selectModel': 'Select embedding model',
    'index.modelCode': 'Code (768d)',
+    'index.modelBase': 'Base (768d)',
    'index.modelFast': 'Fast (384d)',
-    'index.modelMultilingual': 'Multilingual (1024d)',
-    'index.modelBalanced': 'Balanced (1024d)',
+    'index.modelMinilm': 'MiniLM (384d)',
+    'index.modelMultilingual': 'Multilingual (1024d) ⚠️',
+    'index.modelBalanced': 'Balanced (1024d) ⚠️',
+    'index.dimensionWarning': '1024d models require more resources',

    // Semantic Search Configuration
    'semantic.settings': 'Semantic Search Settings',
@@ -1358,7 +1439,10 @@ const i18n = {
    'common.loading': '加载中...',
    'common.error': '错误',
    'common.success': '成功',
-    
+    'common.retry': '重试',
+    'common.refresh': '刷新',
+    'common.minutes': '分钟',
+
    // Header
    'header.project': '项目:',
    'header.recentProjects': '最近项目',
@@ -1612,8 +1696,17 @@ const i18n = {
    'codexlens.installDeps': '安装依赖',
    'codexlens.installDepsPrompt': '是否立即安装？（可能需要几分钟）\n\n点击"取消"将只创建 FTS 索引。',
    'codexlens.installingDeps': '安装依赖中...',
+    'codexlens.installingMode': '正在安装',
    'codexlens.depsInstalled': '依赖安装成功',
    'codexlens.depsInstallFailed': '依赖安装失败',
+
+    // GPU 模式选择
+    'codexlens.selectGpuMode': '选择加速模式',
+    'codexlens.cpuModeDesc': '标准 CPU 处理',
+    'codexlens.directmlModeDesc': 'Windows GPU（NVIDIA/AMD/Intel）',
+    'codexlens.cudaModeDesc': 'NVIDIA GPU（需要 CUDA Toolkit）',
+    'common.recommended': '推荐',
+    'common.unavailable': '不可用',
    'codexlens.modelManagement': '模型管理',
    'codexlens.loadingModels': '加载模型中...',
    'codexlens.downloadModel': '下载',
@@ -1628,6 +1721,35 @@ const i18n = {
    'codexlens.modelListError': '加载模型列表失败',
    'codexlens.noModelsAvailable': '没有可用模型',

+    // 模型下载进度
+    'codexlens.downloadingModel': '正在下载',
+    'codexlens.connectingToHuggingFace': '正在连接 Hugging Face...',
+    'codexlens.downloadTimeEstimate': '预计时间',
+    'codexlens.manualDownloadHint': '手动下载',
+    'codexlens.downloadingModelFiles': '正在下载模型文件...',
+    'codexlens.downloadingWeights': '正在下载模型权重...',
+    'codexlens.downloadingTokenizer': '正在下载分词器...',
+    'codexlens.verifyingModel': '正在验证模型...',
+    'codexlens.finalizingDownload': '正在完成...',
+    'codexlens.downloadComplete': '下载完成！',
+    'codexlens.downloadFailed': '下载失败',
+    'codexlens.manualDownloadOptions': '手动下载选项',
+    'codexlens.cliDownload': '命令行',
+    'codexlens.huggingfaceDownload': 'Hugging Face',
+    'codexlens.downloadCanceled': '下载已取消',
+
+    // 手动下载指南
+    'codexlens.manualDownloadGuide': '手动下载指南',
+    'codexlens.cliMethod': '命令行（推荐）',
+    'codexlens.cliMethodDesc': '在终端运行，显示下载进度：',
+    'codexlens.pythonMethod': 'Python 脚本',
+    'codexlens.pythonMethodDesc': '使用 Python 预下载模型：',
+    'codexlens.hfHubMethod': 'Hugging Face Hub CLI',
+    'codexlens.hfHubMethodDesc': '使用 huggingface-cli 下载，支持断点续传：',
+    'codexlens.modelLinks': '模型直链',
+    'codexlens.cacheLocation': '模型存储位置',
+    'common.copied': '已复制到剪贴板',
+
    // CodexLens 索引进度
    'codexlens.indexing': '索引中',
    'codexlens.indexingDesc': '正在为工作区构建代码索引',
@@ -1637,6 +1759,43 @@ const i18n = {
    'codexlens.indexSuccess': '索引创建成功',
    'codexlens.indexFailed': '索引失败',

+    // CodexLens 安装
+    'codexlens.installDesc': '基于 Python 的代码索引引擎',
+    'codexlens.whatWillBeInstalled': '将安装的内容：',
+    'codexlens.pythonVenv': 'Python 虚拟环境',
+    'codexlens.pythonVenvDesc': '隔离的 Python 环境',
+    'codexlens.codexlensPackage': 'CodexLens 包',
+    'codexlens.codexlensPackageDesc': '代码索引和搜索引擎',
+    'codexlens.sqliteFtsDesc': '全文搜索数据库',
+    'codexlens.installLocation': '安装位置',
+    'codexlens.installTime': '首次安装可能需要 2-3 分钟下载和配置 Python 包。',
+    'codexlens.startingInstall': '正在启动安装...',
+    'codexlens.installing': '安装中...',
+    'codexlens.creatingVenv': '正在创建虚拟环境...',
+    'codexlens.installingPip': '正在安装 pip 包...',
+    'codexlens.installingPackage': '正在安装 CodexLens 包...',
+    'codexlens.settingUpDeps': '正在配置 Python 依赖...',
+    'codexlens.installComplete': '安装完成！',
+    'codexlens.installSuccess': 'CodexLens 安装成功！',
+    'codexlens.installNow': '立即安装',
+    'codexlens.accelerator': '加速器',
+
+    // CodexLens 卸载
+    'codexlens.uninstall': '卸载',
+    'codexlens.uninstallDesc': '移除 CodexLens 及所有数据',
+    'codexlens.whatWillBeRemoved': '将被移除的内容：',
+    'codexlens.removeVenv': '虚拟环境 ~/.codexlens/venv',
+    'codexlens.removeData': '所有 CodexLens 索引数据和数据库',
+    'codexlens.removeConfig': '配置文件和语义搜索模型',
+    'codexlens.removing': '正在删除文件...',
+    'codexlens.uninstalling': '正在卸载...',
+    'codexlens.removingVenv': '正在删除虚拟环境...',
+    'codexlens.removingData': '正在删除索引数据...',
+    'codexlens.removingConfig': '正在清理配置文件...',
+    'codexlens.finalizing': '正在完成卸载...',
+    'codexlens.uninstallComplete': '卸载完成！',
+    'codexlens.uninstallSuccess': 'CodexLens 卸载成功！',
+
    // 索引管理器
    'index.manager': '索引管理器',
    'index.projects': '项目数',
@@ -1668,9 +1827,12 @@ const i18n = {
    'index.fullDesc': 'FTS + 语义搜索（推荐）',
    'index.selectModel': '选择嵌入模型',
    'index.modelCode': '代码优化 (768维)',
+    'index.modelBase': '通用基础 (768维)',
    'index.modelFast': '快速轻量 (384维)',
-    'index.modelMultilingual': '多语言 (1024维)',
-    'index.modelBalanced': '高精度 (1024维)',
+    'index.modelMinilm': 'MiniLM (384维)',
+    'index.modelMultilingual': '多语言 (1024维) ⚠️',
+    'index.modelBalanced': '高精度 (1024维) ⚠️',
+    'index.dimensionWarning': '1024维模型需要更多资源',

    // Semantic Search 配置
    'semantic.settings': '语义搜索设置',
--- a/ccw/src/templates/dashboard-js/views/claude-manager.js
+++ b/ccw/src/templates/dashboard-js/views/claude-manager.js
@@ -102,6 +102,7 @@ async function loadClaudeFiles() {
    updateClaudeBadge(); // Update navigation badge
  } catch (error) {
    console.error('Error loading CLAUDE.md files:', error);
+    showRefreshToast(t('claudeManager.loadError') || 'Failed to load files', 'error');
    addGlobalNotification('error', t('claudeManager.loadError'), null, 'CLAUDE.md');
  }
 }
@@ -113,6 +114,7 @@ async function refreshClaudeFiles() {
  renderFileViewer();
  renderFileMetadata();
  if (window.lucide) lucide.createIcons();
+  showRefreshToast(t('claudeManager.refreshed') || 'Files refreshed', 'success');
  addGlobalNotification('success', t('claudeManager.refreshed'), null, 'CLAUDE.md');
  // Load freshness data in background
  loadFreshnessDataAsync();
@@ -155,6 +157,7 @@ async function markFileAsUpdated() {

    if (!res.ok) throw new Error('Failed to mark file as updated');

+    showRefreshToast(t('claudeManager.markedAsUpdated') || 'Marked as updated', 'success');
    addGlobalNotification('success', t('claudeManager.markedAsUpdated') || 'Marked as updated', null, 'CLAUDE.md');

    // Reload freshness data
@@ -163,6 +166,7 @@ async function markFileAsUpdated() {
    renderFileMetadata();
  } catch (error) {
    console.error('Error marking file as updated:', error);
+    showRefreshToast(t('claudeManager.markUpdateError') || 'Failed to mark as updated', 'error');
    addGlobalNotification('error', t('claudeManager.markUpdateError') || 'Failed to mark as updated', null, 'CLAUDE.md');
  }
 }
@@ -481,10 +485,12 @@ async function saveClaudeFile() {
    selectedFile.stats = calculateFileStats(newContent);
    isDirty = false;

+    showRefreshToast(t('claudeManager.saved') || 'File saved', 'success');
    addGlobalNotification('success', t('claudeManager.saved'), null, 'CLAUDE.md');
    renderFileMetadata();
  } catch (error) {
    console.error('Error saving file:', error);
+    showRefreshToast(t('claudeManager.saveError') || 'Save failed', 'error');
    addGlobalNotification('error', t('claudeManager.saveError'), null, 'CLAUDE.md');
  }
 }
@@ -733,12 +739,13 @@ async function loadFileContent(filePath) {
 }

 function showClaudeNotification(type, message) {
-  // Use global notification system if available
+  // Show toast for immediate feedback
+  if (typeof showRefreshToast === 'function') {
+    showRefreshToast(message, type);
+  }
+  // Also add to global notification system if available
  if (typeof addGlobalNotification === 'function') {
    addGlobalNotification(type, message, null, 'CLAUDE.md');
-  } else {
-    // Fallback to simple alert
-    alert(message);
  }
 }

@@ -822,6 +829,7 @@ async function createNewFile() {
  var modulePath = document.getElementById('modulePath').value;

  if (level === 'module' && !modulePath) {
+    showRefreshToast(t('claude.modulePathRequired') || 'Module path is required', 'error');
    addGlobalNotification('error', t('claude.modulePathRequired') || 'Module path is required', null, 'CLAUDE.md');
    return;
  }
@@ -841,12 +849,14 @@ async function createNewFile() {

    var result = await res.json();
    closeCreateDialog();
+    showRefreshToast(t('claude.fileCreated') || 'File created successfully', 'success');
    addGlobalNotification('success', t('claude.fileCreated') || 'File created successfully', null, 'CLAUDE.md');

    // Refresh file tree
    await refreshClaudeFiles();
  } catch (error) {
    console.error('Error creating file:', error);
+    showRefreshToast(t('claude.createFileError') || 'Failed to create file', 'error');
    addGlobalNotification('error', t('claude.createFileError') || 'Failed to create file', null, 'CLAUDE.md');
  }
 }
@@ -870,6 +880,7 @@ async function confirmDeleteFile() {

    if (!res.ok) throw new Error('Failed to delete file');

+    showRefreshToast(t('claude.fileDeleted') || 'File deleted successfully', 'success');
    addGlobalNotification('success', t('claude.fileDeleted') || 'File deleted successfully', null, 'CLAUDE.md');
    selectedFile = null;

@@ -877,6 +888,7 @@ async function confirmDeleteFile() {
    await refreshClaudeFiles();
  } catch (error) {
    console.error('Error deleting file:', error);
+    showRefreshToast(t('claude.deleteFileError') || 'Failed to delete file', 'error');
    addGlobalNotification('error', t('claude.deleteFileError') || 'Failed to delete file', null, 'CLAUDE.md');
  }
 }
@@ -886,9 +898,11 @@ function copyFileContent() {
  if (!selectedFile || !selectedFile.content) return;

  navigator.clipboard.writeText(selectedFile.content).then(function() {
+    showRefreshToast(t('claude.contentCopied') || 'Content copied to clipboard', 'success');
    addGlobalNotification('success', t('claude.contentCopied') || 'Content copied to clipboard', null, 'CLAUDE.md');
  }).catch(function(error) {
    console.error('Error copying content:', error);
+    showRefreshToast(t('claude.copyError') || 'Failed to copy content', 'error');
    addGlobalNotification('error', t('claude.copyError') || 'Failed to copy content', null, 'CLAUDE.md');
  });
 }
--- a/ccw/src/templates/dashboard-js/views/cli-manager.js
+++ b/ccw/src/templates/dashboard-js/views/cli-manager.js
@@ -349,6 +349,50 @@ function getSelectedModel() {
  return select ? select.value : 'code';
 }

+/**
+ * Build model select options HTML, showing only installed models
+ * @returns {string} HTML string for select options
+ */
+function buildModelSelectOptions() {
+  var installedModels = window.cliToolsStatus?.codexlens?.installedModels || [];
+  var allModels = window.cliToolsStatus?.codexlens?.allModels || [];
+  
+  // Model display configuration
+  var modelConfig = {
+    'code': { label: t('index.modelCode') || 'Code (768d)', star: true },
+    'base': { label: t('index.modelBase') || 'Base (768d)', star: false },
+    'fast': { label: t('index.modelFast') || 'Fast (384d)', star: false },
+    'minilm': { label: t('index.modelMinilm') || 'MiniLM (384d)', star: false },
+    'multilingual': { label: t('index.modelMultilingual') || 'Multilingual (1024d)', warn: true },
+    'balanced': { label: t('index.modelBalanced') || 'Balanced (1024d)', warn: true }
+  };
+  
+  // If no models installed, show placeholder
+  if (installedModels.length === 0) {
+    return '<option value="" disabled selected>' + (t('index.noModelsInstalled') || 'No models installed') + '</option>';
+  }
+  
+  // Build options for installed models only
+  var options = '';
+  var firstInstalled = null;
+  
+  // Preferred order: code, fast, minilm, base, multilingual, balanced
+  var preferredOrder = ['code', 'fast', 'minilm', 'base', 'multilingual', 'balanced'];
+  
+  preferredOrder.forEach(function(profile) {
+    if (installedModels.includes(profile) && modelConfig[profile]) {
+      var config = modelConfig[profile];
+      var style = config.warn ? ' style="color: var(--muted-foreground)"' : '';
+      var suffix = config.star ? ' ⭐' : (config.warn ? ' ⚠️' : '');
+      var selected = !firstInstalled ? ' selected' : '';
+      if (!firstInstalled) firstInstalled = profile;
+      options += '<option value="' + profile + '"' + style + selected + '>' + config.label + suffix + '</option>';
+    }
+  });
+  
+  return options;
+}
+
 // ========== Tools Section (Left Column) ==========
 function renderToolsSection() {
  var container = document.getElementById('tools-section');
@@ -404,10 +448,7 @@ function renderToolsSection() {
      (codexLensStatus.ready
        ? '<span class="tool-status-text success"><i data-lucide="check-circle" class="w-3.5 h-3.5"></i> v' + (codexLensStatus.version || 'installed') + '</span>' +
          '<select id="codexlensModelSelect" class="btn-sm bg-muted border border-border rounded text-xs" onclick="event.stopPropagation()" title="' + (t('index.selectModel') || 'Select embedding model') + '">' +
-            '<option value="code">' + (t('index.modelCode') || 'Code (768d)') + '</option>' +
-            '<option value="fast">' + (t('index.modelFast') || 'Fast (384d)') + '</option>' +
-            '<option value="multilingual">' + (t('index.modelMultilingual') || 'Multilingual (1024d)') + '</option>' +
-            '<option value="balanced">' + (t('index.modelBalanced') || 'Balanced (1024d)') + '</option>' +
+            buildModelSelectOptions() +
          '</select>' +
          '<button class="btn-sm btn-primary" onclick="event.stopPropagation(); initCodexLensIndex(\'full\', getSelectedModel())" title="' + (t('index.fullDesc') || 'FTS + Semantic search (recommended)') + '"><i data-lucide="layers" class="w-3 h-3"></i> ' + (t('index.fullIndex') || '全部索引') + '</button>' +
          '<button class="btn-sm btn-outline" onclick="event.stopPropagation(); initCodexLensIndex(\'vector\', getSelectedModel())" title="' + (t('index.vectorDesc') || 'Semantic search with embeddings') + '"><i data-lucide="sparkles" class="w-3 h-3"></i> ' + (t('index.vectorIndex') || '向量索引') + '</button>' +
--- a/ccw/src/templates/dashboard-js/views/codexlens-manager.js
+++ b/ccw/src/templates/dashboard-js/views/codexlens-manager.js
@@ -126,10 +126,10 @@ function buildCodexLensConfigContent(config) {
              '<button class="inline-flex items-center gap-1.5 px-3 py-1.5 text-xs font-medium rounded-md border border-border bg-background hover:bg-muted/50 transition-colors" onclick="cleanCodexLensIndexes()">' +
                '<i data-lucide="trash" class="w-3.5 h-3.5"></i> ' + t('codexlens.cleanAllIndexes') +
              '</button>' +
-              '<button class="inline-flex items-center gap-1.5 px-3 py-1.5 text-xs font-medium rounded-md border border-destructive/30 bg-destructive/5 text-destructive hover:bg-destructive/10 transition-colors" onclick="uninstallCodexLens()">' +
+              '<button class="inline-flex items-center gap-1.5 px-3 py-1.5 text-xs font-medium rounded-md border border-destructive/30 bg-destructive/5 text-destructive hover:bg-destructive/10 transition-colors" onclick="uninstallCodexLensFromManager()">' +
                '<i data-lucide="trash-2" class="w-3.5 h-3.5"></i> ' + t('cli.uninstall') +
              '</button>'
-            : '<button class="inline-flex items-center gap-1.5 px-3 py-1.5 text-xs font-medium rounded-md bg-primary text-primary-foreground hover:bg-primary/90 transition-colors" onclick="installCodexLens()">' +
+            : '<button class="inline-flex items-center gap-1.5 px-3 py-1.5 text-xs font-medium rounded-md bg-primary text-primary-foreground hover:bg-primary/90 transition-colors" onclick="installCodexLensFromManager()">' +
                '<i data-lucide="download" class="w-3.5 h-3.5"></i> ' + t('codexlens.installCodexLens') +
              '</button>') +
        '</div>' +
@@ -335,6 +335,26 @@ function initCodexLensConfigEvents(currentConfig) {
 // SEMANTIC DEPENDENCIES MANAGEMENT
 // ============================================================

+// Store detected GPU info
+var detectedGpuInfo = null;
+
+/**
+ * Detect GPU support
+ */
+async function detectGpuSupport() {
+  try {
+    var response = await fetch('/api/codexlens/gpu/detect');
+    var result = await response.json();
+    if (result.success) {
+      detectedGpuInfo = result;
+      return result;
+    }
+  } catch (err) {
+    console.error('GPU detection failed:', err);
+  }
+  return { mode: 'cpu', available: ['cpu'], info: 'CPU only' };
+}
+
 /**
 * Load semantic dependencies status
 */
@@ -343,24 +363,58 @@ async function loadSemanticDepsStatus() {
  if (!container) return;

  try {
+    // Detect GPU support in parallel
+    var gpuPromise = detectGpuSupport();
    var response = await fetch('/api/codexlens/semantic/status');
    var result = await response.json();
+    var gpuInfo = await gpuPromise;

    if (result.available) {
-      container.innerHTML =
-        '<div class="flex items-center gap-2 text-sm">' +
-          '<i data-lucide="check-circle" class="w-4 h-4 text-success"></i>' +
-          '<span>' + t('codexlens.semanticInstalled') + '</span>' +
-          '<span class="text-muted-foreground">(' + (result.backend || 'fastembed') + ')</span>' +
-        '</div>';
-    } else {
+      // Build accelerator badge
+      var accelerator = result.accelerator || 'CPU';
+      var acceleratorIcon = 'cpu';
+      var acceleratorClass = 'bg-muted text-muted-foreground';
+
+      if (accelerator === 'CUDA') {
+        acceleratorIcon = 'zap';
+        acceleratorClass = 'bg-green-500/20 text-green-600';
+      } else if (accelerator === 'DirectML') {
+        acceleratorIcon = 'gpu-card';
+        acceleratorClass = 'bg-blue-500/20 text-blue-600';
+      } else if (accelerator === 'ROCm') {
+        acceleratorIcon = 'flame';
+        acceleratorClass = 'bg-red-500/20 text-red-600';
+      }
+
      container.innerHTML =
        '<div class="space-y-2">' +
+          '<div class="flex items-center gap-2 text-sm">' +
+            '<i data-lucide="check-circle" class="w-4 h-4 text-success"></i>' +
+            '<span>' + t('codexlens.semanticInstalled') + '</span>' +
+            '<span class="text-muted-foreground">(' + (result.backend || 'fastembed') + ')</span>' +
+          '</div>' +
+          '<div class="flex items-center gap-2">' +
+            '<span class="inline-flex items-center gap-1 px-2 py-0.5 rounded text-xs font-medium ' + acceleratorClass + '">' +
+              '<i data-lucide="' + acceleratorIcon + '" class="w-3 h-3"></i>' +
+              accelerator +
+            '</span>' +
+            (result.providers && result.providers.length > 0
+              ? '<span class="text-xs text-muted-foreground">' + result.providers.join(', ') + '</span>'
+              : '') +
+          '</div>' +
+        '</div>';
+    } else {
+      // Build GPU mode options
+      var gpuOptions = buildGpuModeSelector(gpuInfo);
+
+      container.innerHTML =
+        '<div class="space-y-3">' +
          '<div class="flex items-center gap-2 text-sm text-muted-foreground">' +
            '<i data-lucide="alert-circle" class="w-4 h-4"></i>' +
            '<span>' + t('codexlens.semanticNotInstalled') + '</span>' +
          '</div>' +
-          '<button class="btn-sm btn-outline" onclick="installSemanticDeps()">' +
+          gpuOptions +
+          '<button class="btn-sm btn-primary w-full" onclick="installSemanticDepsWithGpu()">' +
            '<i data-lucide="download" class="w-3 h-3"></i> ' + t('codexlens.installDeps') +
          '</button>' +
        '</div>';
@@ -373,21 +427,120 @@ async function loadSemanticDepsStatus() {
 }

 /**
- * Install semantic dependencies
+ * Build GPU mode selector HTML
 */
-async function installSemanticDeps() {
+function buildGpuModeSelector(gpuInfo) {
+  var modes = [
+    {
+      id: 'cpu',
+      label: 'CPU',
+      desc: t('codexlens.cpuModeDesc') || 'Standard CPU processing',
+      icon: 'cpu',
+      available: true
+    },
+    {
+      id: 'directml',
+      label: 'DirectML',
+      desc: t('codexlens.directmlModeDesc') || 'Windows GPU (NVIDIA/AMD/Intel)',
+      icon: 'gpu-card',
+      available: gpuInfo.available.includes('directml'),
+      recommended: gpuInfo.mode === 'directml'
+    },
+    {
+      id: 'cuda',
+      label: 'CUDA',
+      desc: t('codexlens.cudaModeDesc') || 'NVIDIA GPU (requires CUDA Toolkit)',
+      icon: 'zap',
+      available: gpuInfo.available.includes('cuda'),
+      recommended: gpuInfo.mode === 'cuda'
+    }
+  ];
+
+  var html =
+    '<div class="space-y-2">' +
+      '<div class="text-xs font-medium text-muted-foreground flex items-center gap-1">' +
+        '<i data-lucide="settings" class="w-3 h-3"></i>' +
+        (t('codexlens.selectGpuMode') || 'Select acceleration mode') +
+      '</div>' +
+      '<div class="text-xs text-muted-foreground bg-muted/50 rounded px-2 py-1">' +
+        '<i data-lucide="info" class="w-3 h-3 inline"></i> ' + gpuInfo.info +
+      '</div>' +
+      '<div class="space-y-1">';
+
+  modes.forEach(function(mode) {
+    var isDisabled = !mode.available;
+    var isRecommended = mode.recommended;
+    var isDefault = mode.id === gpuInfo.mode;
+
+    html +=
+      '<label class="flex items-center gap-3 p-2 rounded border cursor-pointer hover:bg-muted/50 transition-colors ' +
+        (isDisabled ? 'opacity-50 cursor-not-allowed' : '') + '">' +
+        '<input type="radio" name="gpuMode" value="' + mode.id + '" ' +
+          (isDefault ? 'checked' : '') +
+          (isDisabled ? ' disabled' : '') +
+          ' class="accent-primary">' +
+        '<div class="flex-1">' +
+          '<div class="flex items-center gap-2">' +
+            '<i data-lucide="' + mode.icon + '" class="w-4 h-4"></i>' +
+            '<span class="font-medium text-sm">' + mode.label + '</span>' +
+            (isRecommended ? '<span class="text-xs bg-primary/20 text-primary px-1.5 py-0.5 rounded">' + (t('common.recommended') || 'Recommended') + '</span>' : '') +
+            (isDisabled ? '<span class="text-xs text-muted-foreground">(' + (t('common.unavailable') || 'Unavailable') + ')</span>' : '') +
+          '</div>' +
+          '<div class="text-xs text-muted-foreground">' + mode.desc + '</div>' +
+        '</div>' +
+      '</label>';
+  });
+
+  html +=
+      '</div>' +
+    '</div>';
+
+  return html;
+}
+
+/**
+ * Get selected GPU mode
+ */
+function getSelectedGpuMode() {
+  var selected = document.querySelector('input[name="gpuMode"]:checked');
+  return selected ? selected.value : 'cpu';
+}
+
+/**
+ * Install semantic dependencies with GPU mode
+ */
+async function installSemanticDepsWithGpu() {
  var container = document.getElementById('semanticDepsStatus');
  if (!container) return;

+  var gpuMode = getSelectedGpuMode();
+  var modeLabels = {
+    cpu: 'CPU',
+    cuda: 'NVIDIA CUDA',
+    directml: 'DirectML'
+  };
+
  container.innerHTML =
-    '<div class="text-sm text-muted-foreground animate-pulse">' + t('codexlens.installingDeps') + '</div>';
+    '<div class="space-y-2">' +
+      '<div class="flex items-center gap-2 text-sm text-muted-foreground">' +
+        '<div class="animate-spin w-4 h-4 border-2 border-primary border-t-transparent rounded-full"></div>' +
+        '<span>' + t('codexlens.installingDeps') + '</span>' +
+      '</div>' +
+      '<div class="text-xs text-muted-foreground">' +
+        (t('codexlens.installingMode') || 'Installing with') + ': ' + modeLabels[gpuMode] +
+      '</div>' +
+    '</div>';

  try {
-    var response = await fetch('/api/codexlens/semantic/install', { method: 'POST' });
+    var response = await fetch('/api/codexlens/semantic/install', {
+      method: 'POST',
+      headers: { 'Content-Type': 'application/json' },
+      body: JSON.stringify({ gpuMode: gpuMode })
+    });
    var result = await response.json();

    if (result.success) {
-      showRefreshToast(t('codexlens.depsInstalled'), 'success');
+      showRefreshToast(t('codexlens.depsInstalled') + ' (' + modeLabels[gpuMode] + ')', 'success');
      await loadSemanticDepsStatus();
      await loadModelList();
    } else {
@@ -400,10 +553,164 @@ async function installSemanticDeps() {
  }
 }

+/**
+ * Install semantic dependencies (legacy, defaults to CPU)
+ */
+async function installSemanticDeps() {
+  await installSemanticDepsWithGpu();
+}
+
 // ============================================================
 // MODEL MANAGEMENT
 // ============================================================

+/**
+ * Build manual download guide HTML
+ */
+function buildManualDownloadGuide() {
+  var modelData = [
+    { profile: 'code', name: 'jinaai/jina-embeddings-v2-base-code', size: '~150 MB' },
+    { profile: 'fast', name: 'BAAI/bge-small-en-v1.5', size: '~80 MB' },
+    { profile: 'balanced', name: 'mixedbread-ai/mxbai-embed-large-v1', size: '~600 MB' },
+    { profile: 'multilingual', name: 'intfloat/multilingual-e5-large', size: '~1 GB' }
+  ];
+
+  var html =
+    '<div class="mt-4 border-t pt-4">' +
+      '<button class="flex items-center gap-2 text-sm text-muted-foreground hover:text-foreground w-full" onclick="toggleManualDownloadGuide()" id="manualDownloadToggle">' +
+        '<i data-lucide="chevron-right" class="w-4 h-4 transition-transform" id="manualDownloadChevron"></i>' +
+        '<i data-lucide="terminal" class="w-4 h-4"></i>' +
+        '<span>' + (t('codexlens.manualDownloadGuide') || 'Manual Download Guide') + '</span>' +
+      '</button>' +
+      '<div id="manualDownloadContent" class="hidden mt-3 space-y-3">' +
+        // Method 1: CLI
+        '<div class="bg-muted/50 rounded-lg p-3 space-y-2">' +
+          '<div class="flex items-center gap-2 text-sm font-medium">' +
+            '<span class="inline-flex items-center justify-center w-5 h-5 rounded-full bg-primary/20 text-primary text-xs">1</span>' +
+            '<span>' + (t('codexlens.cliMethod') || 'Command Line (Recommended)') + '</span>' +
+          '</div>' +
+          '<div class="text-xs text-muted-foreground mb-2">' +
+            (t('codexlens.cliMethodDesc') || 'Run in terminal with progress display:') +
+          '</div>' +
+          '<div class="space-y-1">';
+
+  modelData.forEach(function(m) {
+    html +=
+          '<div class="flex items-center justify-between bg-background rounded px-2 py-1.5">' +
+            '<code class="text-xs font-mono">codexlens model-download ' + m.profile + '</code>' +
+            '<button class="text-xs text-primary hover:underline" onclick="copyToClipboard(\'codexlens model-download ' + m.profile + '\')">' +
+              '<i data-lucide="copy" class="w-3 h-3"></i>' +
+            '</button>' +
+          '</div>';
+  });
+
+  html +=
+          '</div>' +
+        '</div>' +
+
+        // Method 2: Python
+        '<div class="bg-muted/50 rounded-lg p-3 space-y-2">' +
+          '<div class="flex items-center gap-2 text-sm font-medium">' +
+            '<span class="inline-flex items-center justify-center w-5 h-5 rounded-full bg-primary/20 text-primary text-xs">2</span>' +
+            '<span>' + (t('codexlens.pythonMethod') || 'Python Script') + '</span>' +
+          '</div>' +
+          '<div class="text-xs text-muted-foreground mb-2">' +
+            (t('codexlens.pythonMethodDesc') || 'Pre-download model using Python:') +
+          '</div>' +
+          '<div class="bg-background rounded p-2">' +
+            '<pre class="text-xs font-mono whitespace-pre-wrap">' +
+'# Install fastembed first\n' +
+'pip install fastembed\n\n' +
+'# Download model (choose one)\n' +
+'from fastembed import TextEmbedding\n\n' +
+'# Code model (recommended for code search)\n' +
+'model = TextEmbedding("jinaai/jina-embeddings-v2-base-code")\n\n' +
+'# Fast model (lightweight)\n' +
+'# model = TextEmbedding("BAAI/bge-small-en-v1.5")' +
+            '</pre>' +
+          '</div>' +
+        '</div>' +
+
+        // Method 3: Hugging Face Hub
+        '<div class="bg-muted/50 rounded-lg p-3 space-y-2">' +
+          '<div class="flex items-center gap-2 text-sm font-medium">' +
+            '<span class="inline-flex items-center justify-center w-5 h-5 rounded-full bg-primary/20 text-primary text-xs">3</span>' +
+            '<span>' + (t('codexlens.hfHubMethod') || 'Hugging Face Hub CLI') + '</span>' +
+          '</div>' +
+          '<div class="text-xs text-muted-foreground mb-2">' +
+            (t('codexlens.hfHubMethodDesc') || 'Download using huggingface-cli with resume support:') +
+          '</div>' +
+          '<div class="bg-background rounded p-2 space-y-2">' +
+            '<pre class="text-xs font-mono whitespace-pre-wrap">' +
+'# Install huggingface_hub\n' +
+'pip install huggingface_hub\n\n' +
+'# Download model (supports resume on failure)\n' +
+'huggingface-cli download jinaai/jina-embeddings-v2-base-code' +
+            '</pre>' +
+          '</div>' +
+        '</div>' +
+
+        // Model Links
+        '<div class="bg-muted/50 rounded-lg p-3 space-y-2">' +
+          '<div class="flex items-center gap-2 text-sm font-medium">' +
+            '<i data-lucide="external-link" class="w-4 h-4"></i>' +
+            '<span>' + (t('codexlens.modelLinks') || 'Direct Model Links') + '</span>' +
+          '</div>' +
+          '<div class="grid grid-cols-2 gap-2">';
+
+  modelData.forEach(function(m) {
+    html +=
+            '<a href="https://huggingface.co/' + m.name + '" target="_blank" class="flex items-center justify-between bg-background rounded px-2 py-1.5 hover:bg-muted transition-colors">' +
+              '<span class="text-xs font-medium">' + m.profile + '</span>' +
+              '<span class="text-xs text-muted-foreground">' + m.size + '</span>' +
+            '</a>';
+  });
+
+  html +=
+          '</div>' +
+        '</div>' +
+
+        // Cache location info
+        '<div class="text-xs text-muted-foreground bg-muted/30 rounded p-2">' +
+          '<div class="flex items-start gap-1.5">' +
+            '<i data-lucide="info" class="w-3.5 h-3.5 mt-0.5 flex-shrink-0"></i>' +
+            '<div>' +
+              '<strong>' + (t('codexlens.cacheLocation') || 'Cache Location') + ':</strong><br>' +
+              '<code class="text-xs">Windows: %LOCALAPPDATA%\\Temp\\fastembed_cache</code><br>' +
+              '<code class="text-xs">Linux/Mac: ~/.cache/fastembed</code>' +
+            '</div>' +
+          '</div>' +
+        '</div>' +
+      '</div>' +
+    '</div>';
+
+  return html;
+}
+
+/**
+ * Toggle manual download guide visibility
+ */
+function toggleManualDownloadGuide() {
+  var content = document.getElementById('manualDownloadContent');
+  var chevron = document.getElementById('manualDownloadChevron');
+
+  if (content && chevron) {
+    content.classList.toggle('hidden');
+    chevron.style.transform = content.classList.contains('hidden') ? '' : 'rotate(90deg)';
+  }
+}
+
+/**
+ * Copy text to clipboard
+ */
+function copyToClipboard(text) {
+  navigator.clipboard.writeText(text).then(function() {
+    showRefreshToast(t('common.copied') || 'Copied to clipboard', 'success');
+  }).catch(function(err) {
+    console.error('Failed to copy:', err);
+  });
+}
+
 /**
 * Load model list
 */
@@ -476,6 +783,10 @@ async function loadModelList() {
    });

    html += '</div>';
+
+    // Add manual download guide section
+    html += buildManualDownloadGuide();
+
    container.innerHTML = html;
    if (window.lucide) lucide.createIcons();
  } catch (err) {
@@ -485,18 +796,94 @@ async function loadModelList() {
 }

 /**
- * Download model
+ * Download model with progress simulation and manual download info
 */
 async function downloadModel(profile) {
  var modelCard = document.getElementById('model-' + profile);
  if (!modelCard) return;

  var originalHTML = modelCard.innerHTML;
+
+  // Get model info for size estimation
+  var modelSizes = {
+    'fast': { size: 80, time: '1-2' },
+    'code': { size: 150, time: '2-5' },
+    'multilingual': { size: 1000, time: '5-15' },
+    'balanced': { size: 600, time: '3-10' }
+  };
+
+  var modelInfo = modelSizes[profile] || { size: 100, time: '2-5' };
+
+  // Show detailed download UI with progress simulation
  modelCard.innerHTML =
-    '<div class="flex items-center justify-center p-3">' +
-      '<span class="text-sm text-muted-foreground animate-pulse">' + t('codexlens.downloading') + '</span>' +
+    '<div class="p-3 space-y-3">' +
+      '<div class="flex items-center gap-2">' +
+        '<div class="animate-spin w-4 h-4 border-2 border-primary border-t-transparent rounded-full flex-shrink-0"></div>' +
+        '<span class="text-sm font-medium">' + (t('codexlens.downloadingModel') || 'Downloading') + ' ' + profile + '</span>' +
+      '</div>' +
+      '<div class="space-y-1">' +
+        '<div class="h-2 bg-muted rounded-full overflow-hidden">' +
+          '<div id="model-progress-' + profile + '" class="h-full bg-primary transition-all duration-1000 ease-out model-download-progress" style="width: 0%"></div>' +
+        '</div>' +
+        '<div class="flex justify-between text-xs text-muted-foreground">' +
+          '<span id="model-status-' + profile + '">' + (t('codexlens.connectingToHuggingFace') || 'Connecting to Hugging Face...') + '</span>' +
+          '<span>~' + modelInfo.size + ' MB</span>' +
+        '</div>' +
+      '</div>' +
+      '<div class="text-xs text-muted-foreground bg-muted/50 rounded p-2 space-y-1">' +
+        '<div class="flex items-start gap-1">' +
+          '<i data-lucide="info" class="w-3 h-3 mt-0.5 flex-shrink-0"></i>' +
+          '<span>' + (t('codexlens.downloadTimeEstimate') || 'Estimated time') + ': ' + modelInfo.time + ' ' + (t('common.minutes') || 'minutes') + '</span>' +
+        '</div>' +
+        '<div class="flex items-start gap-1">' +
+          '<i data-lucide="terminal" class="w-3 h-3 mt-0.5 flex-shrink-0"></i>' +
+          '<span>' + (t('codexlens.manualDownloadHint') || 'Manual download') + ': <code class="bg-background px-1 rounded">codexlens model-download ' + profile + '</code></span>' +
+        '</div>' +
+      '</div>' +
+      '<button class="text-xs text-muted-foreground hover:text-foreground underline" onclick="cancelModelDownload(\'' + profile + '\')">' +
+        (t('common.cancel') || 'Cancel') +
+      '</button>' +
    '</div>';

+  if (window.lucide) lucide.createIcons();
+
+  // Start progress simulation
+  var progressBar = document.getElementById('model-progress-' + profile);
+  var statusText = document.getElementById('model-status-' + profile);
+  var simulatedProgress = 0;
+  var progressInterval = null;
+  var downloadAborted = false;
+
+  // Store abort controller for cancellation
+  window['modelDownloadAbort_' + profile] = function() {
+    downloadAborted = true;
+    if (progressInterval) clearInterval(progressInterval);
+  };
+
+  // Simulate progress based on model size
+  var progressStages = [
+    { percent: 10, msg: t('codexlens.downloadingModelFiles') || 'Downloading model files...' },
+    { percent: 30, msg: t('codexlens.downloadingWeights') || 'Downloading model weights...' },
+    { percent: 60, msg: t('codexlens.downloadingTokenizer') || 'Downloading tokenizer...' },
+    { percent: 80, msg: t('codexlens.verifyingModel') || 'Verifying model...' },
+    { percent: 95, msg: t('codexlens.finalizingDownload') || 'Finalizing...' }
+  ];
+
+  var stageIndex = 0;
+  var baseInterval = Math.max(2000, modelInfo.size * 30); // Slower for larger models
+
+  progressInterval = setInterval(function() {
+    if (downloadAborted) return;
+
+    if (stageIndex < progressStages.length) {
+      var stage = progressStages[stageIndex];
+      simulatedProgress = stage.percent;
+      if (progressBar) progressBar.style.width = simulatedProgress + '%';
+      if (statusText) statusText.textContent = stage.msg;
+      stageIndex++;
+    }
+  }, baseInterval);
+
  try {
    var response = await fetch('/api/codexlens/models/download', {
      method: 'POST',
@@ -504,20 +891,99 @@ async function downloadModel(profile) {
      body: JSON.stringify({ profile: profile })
    });

+    // Clear simulation
+    if (progressInterval) clearInterval(progressInterval);
+
+    if (downloadAborted) {
+      modelCard.innerHTML = originalHTML;
+      if (window.lucide) lucide.createIcons();
+      return;
+    }
+
    var result = await response.json();

    if (result.success) {
+      // Show completion
+      if (progressBar) progressBar.style.width = '100%';
+      if (statusText) statusText.textContent = t('codexlens.downloadComplete') || 'Download complete!';
+
      showRefreshToast(t('codexlens.modelDownloaded') + ': ' + profile, 'success');
-      await loadModelList();
+
+      // Refresh model list after short delay
+      setTimeout(function() {
+        loadModelList();
+      }, 500);
    } else {
      showRefreshToast(t('codexlens.modelDownloadFailed') + ': ' + result.error, 'error');
-      modelCard.innerHTML = originalHTML;
-      if (window.lucide) lucide.createIcons();
+      showModelDownloadError(modelCard, profile, result.error, originalHTML);
    }
  } catch (err) {
+    if (progressInterval) clearInterval(progressInterval);
    showRefreshToast(t('common.error') + ': ' + err.message, 'error');
-    modelCard.innerHTML = originalHTML;
-    if (window.lucide) lucide.createIcons();
+    showModelDownloadError(modelCard, profile, err.message, originalHTML);
+  }
+
+  // Cleanup abort function
+  delete window['modelDownloadAbort_' + profile];
+}
+
+/**
+ * Show model download error with manual download instructions
+ */
+function showModelDownloadError(modelCard, profile, error, originalHTML) {
+  var modelNames = {
+    'fast': 'BAAI/bge-small-en-v1.5',
+    'code': 'jinaai/jina-embeddings-v2-base-code',
+    'multilingual': 'intfloat/multilingual-e5-large',
+    'balanced': 'mixedbread-ai/mxbai-embed-large-v1'
+  };
+
+  var modelName = modelNames[profile] || profile;
+  var hfUrl = 'https://huggingface.co/' + modelName;
+
+  modelCard.innerHTML =
+    '<div class="p-3 space-y-3">' +
+      '<div class="flex items-start gap-2 text-destructive">' +
+        '<i data-lucide="alert-circle" class="w-4 h-4 mt-0.5 flex-shrink-0"></i>' +
+        '<div class="text-sm">' +
+          '<div class="font-medium">' + (t('codexlens.downloadFailed') || 'Download failed') + '</div>' +
+          '<div class="text-xs text-muted-foreground mt-1">' + error + '</div>' +
+        '</div>' +
+      '</div>' +
+      '<div class="bg-muted/50 rounded p-2 space-y-2 text-xs">' +
+        '<div class="font-medium">' + (t('codexlens.manualDownloadOptions') || 'Manual download options') + ':</div>' +
+        '<div class="space-y-1.5">' +
+          '<div class="flex items-start gap-1">' +
+            '<span class="text-muted-foreground">1.</span>' +
+            '<span>' + (t('codexlens.cliDownload') || 'CLI') + ': <code class="bg-background px-1 rounded">codexlens model-download ' + profile + '</code></span>' +
+          '</div>' +
+          '<div class="flex items-start gap-1">' +
+            '<span class="text-muted-foreground">2.</span>' +
+            '<span>' + (t('codexlens.huggingfaceDownload') || 'Hugging Face') + ': <a href="' + hfUrl + '" target="_blank" class="text-primary hover:underline">' + modelName + '</a></span>' +
+          '</div>' +
+        '</div>' +
+      '</div>' +
+      '<div class="flex gap-2">' +
+        '<button class="btn-sm btn-outline flex-1" onclick="loadModelList()">' +
+          '<i data-lucide="refresh-cw" class="w-3 h-3"></i> ' + (t('common.refresh') || 'Refresh') +
+        '</button>' +
+        '<button class="btn-sm btn-primary flex-1" onclick="downloadModel(\'' + profile + '\')">' +
+          '<i data-lucide="download" class="w-3 h-3"></i> ' + (t('common.retry') || 'Retry') +
+        '</button>' +
+      '</div>' +
+    '</div>';
+
+  if (window.lucide) lucide.createIcons();
+}
+
+/**
+ * Cancel model download
+ */
+function cancelModelDownload(profile) {
+  if (window['modelDownloadAbort_' + profile]) {
+    window['modelDownloadAbort_' + profile]();
+    showRefreshToast(t('codexlens.downloadCanceled') || 'Download canceled', 'info');
+    loadModelList();
  }
 }

@@ -876,16 +1342,315 @@ async function cancelCodexLensIndexing() {

 /**
 * Install CodexLens
+ * Note: Uses CodexLens-specific install wizard from cli-status.js
+ * which calls /api/codexlens/bootstrap (Python venv), not the generic
+ * CLI install that uses npm install -g (NPM packages)
 */
-function installCodexLens() {
-  openCliInstallWizard('codexlens');
+function installCodexLensFromManager() {
+  // Use the CodexLens-specific install wizard from cli-status.js
+  if (typeof openCodexLensInstallWizard === 'function') {
+    openCodexLensInstallWizard();
+  } else {
+    // Fallback: inline install wizard if cli-status.js not loaded
+    showCodexLensInstallDialog();
+  }
+}
+
+/**
+ * Fallback install dialog when cli-status.js is not loaded
+ */
+function showCodexLensInstallDialog() {
+  var modal = document.createElement('div');
+  modal.id = 'codexlensInstallModalFallback';
+  modal.className = 'fixed inset-0 bg-black/50 flex items-center justify-center z-50';
+  modal.innerHTML =
+    '<div class="bg-card rounded-lg shadow-xl w-full max-w-md mx-4 overflow-hidden">' +
+      '<div class="p-6">' +
+        '<div class="flex items-center gap-3 mb-4">' +
+          '<div class="w-10 h-10 rounded-full bg-primary/10 flex items-center justify-center">' +
+            '<i data-lucide="database" class="w-5 h-5 text-primary"></i>' +
+          '</div>' +
+          '<div>' +
+            '<h3 class="text-lg font-semibold">' + t('codexlens.installCodexLens') + '</h3>' +
+            '<p class="text-sm text-muted-foreground">' + t('codexlens.installDesc') + '</p>' +
+          '</div>' +
+        '</div>' +
+        '<div class="space-y-4">' +
+          '<div class="bg-muted/50 rounded-lg p-4">' +
+            '<h4 class="font-medium mb-2">' + t('codexlens.whatWillBeInstalled') + '</h4>' +
+            '<ul class="text-sm space-y-2 text-muted-foreground">' +
+              '<li class="flex items-start gap-2">' +
+                '<i data-lucide="check" class="w-4 h-4 text-success mt-0.5"></i>' +
+                '<span><strong>' + t('codexlens.pythonVenv') + '</strong> - ' + t('codexlens.pythonVenvDesc') + '</span>' +
+              '</li>' +
+              '<li class="flex items-start gap-2">' +
+                '<i data-lucide="check" class="w-4 h-4 text-success mt-0.5"></i>' +
+                '<span><strong>' + t('codexlens.codexlensPackage') + '</strong> - ' + t('codexlens.codexlensPackageDesc') + '</span>' +
+              '</li>' +
+              '<li class="flex items-start gap-2">' +
+                '<i data-lucide="check" class="w-4 h-4 text-success mt-0.5"></i>' +
+                '<span><strong>SQLite FTS5</strong> - ' + t('codexlens.sqliteFtsDesc') + '</span>' +
+              '</li>' +
+            '</ul>' +
+          '</div>' +
+          '<div class="bg-primary/5 border border-primary/20 rounded-lg p-3">' +
+            '<div class="flex items-start gap-2">' +
+              '<i data-lucide="info" class="w-4 h-4 text-primary mt-0.5"></i>' +
+              '<div class="text-sm text-muted-foreground">' +
+                '<p class="font-medium text-foreground">' + t('codexlens.installLocation') + '</p>' +
+                '<p class="mt-1"><code class="bg-muted px-1 rounded">~/.codexlens/venv</code></p>' +
+                '<p class="mt-1">' + t('codexlens.installTime') + '</p>' +
+              '</div>' +
+            '</div>' +
+          '</div>' +
+          '<div id="codexlensInstallProgressFallback" class="hidden">' +
+            '<div class="flex items-center gap-3">' +
+              '<div class="animate-spin w-5 h-5 border-2 border-primary border-t-transparent rounded-full"></div>' +
+              '<span class="text-sm" id="codexlensInstallStatusFallback">' + t('codexlens.startingInstall') + '</span>' +
+            '</div>' +
+            '<div class="mt-2 h-2 bg-muted rounded-full overflow-hidden">' +
+              '<div id="codexlensInstallProgressBarFallback" class="h-full bg-primary transition-all duration-300" style="width: 0%"></div>' +
+            '</div>' +
+          '</div>' +
+        '</div>' +
+      '</div>' +
+      '<div class="border-t border-border p-4 flex justify-end gap-3 bg-muted/30">' +
+        '<button class="btn-outline px-4 py-2" onclick="closeCodexLensInstallDialogFallback()">' + t('common.cancel') + '</button>' +
+        '<button id="codexlensInstallBtnFallback" class="btn-primary px-4 py-2" onclick="startCodexLensInstallFallback()">' +
+          '<i data-lucide="download" class="w-4 h-4 mr-2"></i>' +
+          t('codexlens.installNow') +
+        '</button>' +
+      '</div>' +
+    '</div>';
+
+  document.body.appendChild(modal);
+  if (window.lucide) lucide.createIcons();
+}
+
+function closeCodexLensInstallDialogFallback() {
+  var modal = document.getElementById('codexlensInstallModalFallback');
+  if (modal) modal.remove();
+}
+
+async function startCodexLensInstallFallback() {
+  var progressDiv = document.getElementById('codexlensInstallProgressFallback');
+  var installBtn = document.getElementById('codexlensInstallBtnFallback');
+  var statusText = document.getElementById('codexlensInstallStatusFallback');
+  var progressBar = document.getElementById('codexlensInstallProgressBarFallback');
+
+  progressDiv.classList.remove('hidden');
+  installBtn.disabled = true;
+  installBtn.innerHTML = '<span class="animate-pulse">' + t('codexlens.installing') + '</span>';
+
+  var stages = [
+    { progress: 10, text: t('codexlens.creatingVenv') },
+    { progress: 30, text: t('codexlens.installingPip') },
+    { progress: 50, text: t('codexlens.installingPackage') },
+    { progress: 70, text: t('codexlens.settingUpDeps') },
+    { progress: 90, text: t('codexlens.finalizing') }
+  ];
+
+  var currentStage = 0;
+  var progressInterval = setInterval(function() {
+    if (currentStage < stages.length) {
+      statusText.textContent = stages[currentStage].text;
+      progressBar.style.width = stages[currentStage].progress + '%';
+      currentStage++;
+    }
+  }, 1500);
+
+  try {
+    var response = await fetch('/api/codexlens/bootstrap', {
+      method: 'POST',
+      headers: { 'Content-Type': 'application/json' },
+      body: JSON.stringify({})
+    });
+
+    clearInterval(progressInterval);
+    var result = await response.json();
+
+    if (result.success) {
+      progressBar.style.width = '100%';
+      statusText.textContent = t('codexlens.installComplete');
+
+      setTimeout(function() {
+        closeCodexLensInstallDialogFallback();
+        showRefreshToast(t('codexlens.installSuccess'), 'success');
+        // Refresh the page to update status
+        if (typeof loadCodexLensStatus === 'function') {
+          loadCodexLensStatus().then(function() {
+            if (typeof renderCodexLensManager === 'function') renderCodexLensManager();
+          });
+        } else {
+          location.reload();
+        }
+      }, 1000);
+    } else {
+      statusText.textContent = t('common.error') + ': ' + result.error;
+      progressBar.classList.add('bg-destructive');
+      installBtn.disabled = false;
+      installBtn.innerHTML = '<i data-lucide="refresh-cw" class="w-4 h-4 mr-2"></i> ' + t('common.retry');
+      if (window.lucide) lucide.createIcons();
+    }
+  } catch (err) {
+    clearInterval(progressInterval);
+    statusText.textContent = t('common.error') + ': ' + err.message;
+    progressBar.classList.add('bg-destructive');
+    installBtn.disabled = false;
+    installBtn.innerHTML = '<i data-lucide="refresh-cw" class="w-4 h-4 mr-2"></i> ' + t('common.retry');
+    if (window.lucide) lucide.createIcons();
+  }
 }

 /**
 * Uninstall CodexLens
+ * Note: Uses CodexLens-specific uninstall wizard from cli-status.js
+ * which calls /api/codexlens/uninstall (Python venv), not the generic
+ * CLI uninstall that uses /api/cli/uninstall (NPM packages)
 */
-function uninstallCodexLens() {
-  openCliUninstallWizard('codexlens');
+function uninstallCodexLensFromManager() {
+  // Use the CodexLens-specific uninstall wizard from cli-status.js
+  if (typeof openCodexLensUninstallWizard === 'function') {
+    openCodexLensUninstallWizard();
+  } else {
+    // Fallback: inline uninstall wizard if cli-status.js not loaded
+    showCodexLensUninstallDialog();
+  }
+}
+
+/**
+ * Fallback uninstall dialog when cli-status.js is not loaded
+ */
+function showCodexLensUninstallDialog() {
+  var modal = document.createElement('div');
+  modal.id = 'codexlensUninstallModalFallback';
+  modal.className = 'fixed inset-0 bg-black/50 flex items-center justify-center z-50';
+  modal.innerHTML =
+    '<div class="bg-card rounded-lg shadow-xl w-full max-w-md mx-4 overflow-hidden">' +
+      '<div class="p-6">' +
+        '<div class="flex items-center gap-3 mb-4">' +
+          '<div class="w-10 h-10 rounded-full bg-destructive/10 flex items-center justify-center">' +
+            '<i data-lucide="trash-2" class="w-5 h-5 text-destructive"></i>' +
+          '</div>' +
+          '<div>' +
+            '<h3 class="text-lg font-semibold">' + t('codexlens.uninstall') + '</h3>' +
+            '<p class="text-sm text-muted-foreground">' + t('codexlens.uninstallDesc') + '</p>' +
+          '</div>' +
+        '</div>' +
+        '<div class="space-y-4">' +
+          '<div class="bg-destructive/5 border border-destructive/20 rounded-lg p-4">' +
+            '<h4 class="font-medium text-destructive mb-2">' + t('codexlens.whatWillBeRemoved') + '</h4>' +
+            '<ul class="text-sm space-y-2 text-muted-foreground">' +
+              '<li class="flex items-start gap-2">' +
+                '<i data-lucide="x" class="w-4 h-4 text-destructive mt-0.5"></i>' +
+                '<span>' + t('codexlens.removeVenv') + '</span>' +
+              '</li>' +
+              '<li class="flex items-start gap-2">' +
+                '<i data-lucide="x" class="w-4 h-4 text-destructive mt-0.5"></i>' +
+                '<span>' + t('codexlens.removeData') + '</span>' +
+              '</li>' +
+              '<li class="flex items-start gap-2">' +
+                '<i data-lucide="x" class="w-4 h-4 text-destructive mt-0.5"></i>' +
+                '<span>' + t('codexlens.removeConfig') + '</span>' +
+              '</li>' +
+            '</ul>' +
+          '</div>' +
+          '<div id="codexlensUninstallProgressFallback" class="hidden">' +
+            '<div class="flex items-center gap-3">' +
+              '<div class="animate-spin w-5 h-5 border-2 border-destructive border-t-transparent rounded-full"></div>' +
+              '<span class="text-sm" id="codexlensUninstallStatusFallback">' + t('codexlens.removing') + '</span>' +
+            '</div>' +
+            '<div class="mt-2 h-2 bg-muted rounded-full overflow-hidden">' +
+              '<div id="codexlensUninstallProgressBarFallback" class="h-full bg-destructive transition-all duration-300" style="width: 0%"></div>' +
+            '</div>' +
+          '</div>' +
+        '</div>' +
+      '</div>' +
+      '<div class="border-t border-border p-4 flex justify-end gap-3 bg-muted/30">' +
+        '<button class="btn-outline px-4 py-2" onclick="closeCodexLensUninstallDialogFallback()">' + t('common.cancel') + '</button>' +
+        '<button id="codexlensUninstallBtnFallback" class="btn-destructive px-4 py-2" onclick="startCodexLensUninstallFallback()">' +
+          '<i data-lucide="trash-2" class="w-4 h-4 mr-2"></i>' +
+          t('codexlens.uninstall') +
+        '</button>' +
+      '</div>' +
+    '</div>';
+
+  document.body.appendChild(modal);
+  if (window.lucide) lucide.createIcons();
+}
+
+function closeCodexLensUninstallDialogFallback() {
+  var modal = document.getElementById('codexlensUninstallModalFallback');
+  if (modal) modal.remove();
+}
+
+async function startCodexLensUninstallFallback() {
+  var progressDiv = document.getElementById('codexlensUninstallProgressFallback');
+  var uninstallBtn = document.getElementById('codexlensUninstallBtnFallback');
+  var statusText = document.getElementById('codexlensUninstallStatusFallback');
+  var progressBar = document.getElementById('codexlensUninstallProgressBarFallback');
+
+  progressDiv.classList.remove('hidden');
+  uninstallBtn.disabled = true;
+  uninstallBtn.innerHTML = '<span class="animate-pulse">' + t('codexlens.uninstalling') + '</span>';
+
+  var stages = [
+    { progress: 25, text: t('codexlens.removingVenv') },
+    { progress: 50, text: t('codexlens.removingData') },
+    { progress: 75, text: t('codexlens.removingConfig') },
+    { progress: 90, text: t('codexlens.finalizing') }
+  ];
+
+  var currentStage = 0;
+  var progressInterval = setInterval(function() {
+    if (currentStage < stages.length) {
+      statusText.textContent = stages[currentStage].text;
+      progressBar.style.width = stages[currentStage].progress + '%';
+      currentStage++;
+    }
+  }, 500);
+
+  try {
+    var response = await fetch('/api/codexlens/uninstall', {
+      method: 'POST',
+      headers: { 'Content-Type': 'application/json' },
+      body: JSON.stringify({})
+    });
+
+    clearInterval(progressInterval);
+    var result = await response.json();
+
+    if (result.success) {
+      progressBar.style.width = '100%';
+      statusText.textContent = t('codexlens.uninstallComplete');
+
+      setTimeout(function() {
+        closeCodexLensUninstallDialogFallback();
+        showRefreshToast(t('codexlens.uninstallSuccess'), 'success');
+        // Refresh the page to update status
+        if (typeof loadCodexLensStatus === 'function') {
+          loadCodexLensStatus().then(function() {
+            if (typeof renderCodexLensManager === 'function') renderCodexLensManager();
+          });
+        } else {
+          location.reload();
+        }
+      }, 1000);
+    } else {
+      statusText.textContent = t('common.error') + ': ' + result.error;
+      progressBar.classList.add('bg-destructive');
+      uninstallBtn.disabled = false;
+      uninstallBtn.innerHTML = '<i data-lucide="refresh-cw" class="w-4 h-4 mr-2"></i> ' + t('common.retry');
+      if (window.lucide) lucide.createIcons();
+    }
+  } catch (err) {
+    clearInterval(progressInterval);
+    statusText.textContent = t('common.error') + ': ' + err.message;
+    progressBar.classList.add('bg-destructive');
+    uninstallBtn.disabled = false;
+    uninstallBtn.innerHTML = '<i data-lucide="refresh-cw" class="w-4 h-4 mr-2"></i> ' + t('common.retry');
+    if (window.lucide) lucide.createIcons();
+  }
 }

 /**
--- a/ccw/src/templates/dashboard-js/views/hook-manager.js
+++ b/ccw/src/templates/dashboard-js/views/hook-manager.js
@@ -449,8 +449,23 @@ function isHookTemplateInstalled(templateId) {
  const template = HOOK_TEMPLATES[templateId];
  if (!template) return false;

-  // Build expected command string
-  const templateCmd = template.command + (template.args ? ' ' + template.args.join(' ') : '');
+  // Define unique patterns for each template type (more specific than just command)
+  const uniquePatterns = {
+    'session-context': 'hook session-context',
+    'codexlens-update': 'codexlens update',
+    'ccw-notify': 'api/hook',
+    'log-tool': 'tool-usage.log',
+    'lint-check': 'eslint',
+    'git-add': 'git add',
+    'memory-file-read': 'memory track --type file --action read',
+    'memory-file-write': 'memory track --type file --action write',
+    'memory-prompt-track': 'memory track --type topic',
+    'skill-context-auto': 'skill-context-auto'
+  };
+
+  // Use unique pattern if defined, otherwise fall back to command + args
+  const searchPattern = uniquePatterns[templateId] ||
+    (template.command + (template.args ? ' ' + template.args.join(' ') : ''));

  // Check project hooks
  const projectHooks = hookConfig.project?.hooks?.[template.event];
@@ -459,7 +474,7 @@ function isHookTemplateInstalled(templateId) {
    if (hookList.some(h => {
      // Check both old format (h.command) and new format (h.hooks[0].command)
      const cmd = h.hooks?.[0]?.command || h.command || '';
-      return cmd.includes(template.command);
+      return cmd.includes(searchPattern);
    })) return true;
  }

@@ -469,7 +484,7 @@ function isHookTemplateInstalled(templateId) {
    const hookList = Array.isArray(globalHooks) ? globalHooks : [globalHooks];
    if (hookList.some(h => {
      const cmd = h.hooks?.[0]?.command || h.command || '';
-      return cmd.includes(template.command);
+      return cmd.includes(searchPattern);
    })) return true;
  }

@@ -512,7 +527,7 @@ async function uninstallHookTemplate(templateId) {

  // Define unique patterns for each template type
  const uniquePatterns = {
-    'session-context': 'api/hook/session-context',
+    'session-context': 'hook session-context',
    'codexlens-update': 'codexlens update',
    'ccw-notify': 'api/hook',
    'log-tool': 'tool-usage.log',
--- a/ccw/src/templates/dashboard-js/views/mcp-manager.js
+++ b/ccw/src/templates/dashboard-js/views/mcp-manager.js
@@ -42,17 +42,41 @@ function getCcwEnabledToolsCodex() {

 // Get current CCW_PROJECT_ROOT from config
 function getCcwProjectRoot() {
+  // Try project config first, then global config
  const currentPath = projectPath;
  const projectData = mcpAllProjects[currentPath] || {};
-  const ccwConfig = projectData.mcpServers?.['ccw-tools'];
-  return ccwConfig?.env?.CCW_PROJECT_ROOT || '';
+  const projectCcwConfig = projectData.mcpServers?.['ccw-tools'];
+  if (projectCcwConfig?.env?.CCW_PROJECT_ROOT) {
+    return projectCcwConfig.env.CCW_PROJECT_ROOT;
+  }
+  // Fallback to global config
+  const globalCcwConfig = mcpUserServers?.['ccw-tools'];
+  return globalCcwConfig?.env?.CCW_PROJECT_ROOT || '';
 }

 // Get current CCW_ALLOWED_DIRS from config
 function getCcwAllowedDirs() {
+  // Try project config first, then global config
  const currentPath = projectPath;
  const projectData = mcpAllProjects[currentPath] || {};
-  const ccwConfig = projectData.mcpServers?.['ccw-tools'];
+  const projectCcwConfig = projectData.mcpServers?.['ccw-tools'];
+  if (projectCcwConfig?.env?.CCW_ALLOWED_DIRS) {
+    return projectCcwConfig.env.CCW_ALLOWED_DIRS;
+  }
+  // Fallback to global config
+  const globalCcwConfig = mcpUserServers?.['ccw-tools'];
+  return globalCcwConfig?.env?.CCW_ALLOWED_DIRS || '';
+}
+
+// Get current CCW_PROJECT_ROOT from Codex config
+function getCcwProjectRootCodex() {
+  const ccwConfig = codexMcpServers?.['ccw-tools'];
+  return ccwConfig?.env?.CCW_PROJECT_ROOT || '';
+}
+
+// Get current CCW_ALLOWED_DIRS from Codex config
+function getCcwAllowedDirsCodex() {
+  const ccwConfig = codexMcpServers?.['ccw-tools'];
  return ccwConfig?.env?.CCW_ALLOWED_DIRS || '';
 }

@@ -260,7 +284,7 @@ async function renderMcpManager() {
                      <input type="text"
                             class="ccw-project-root-input flex-1 px-2 py-1 text-xs bg-background border border-border rounded focus:outline-none focus:ring-1 focus:ring-primary"
                             placeholder="${projectPath || t('mcp.useCurrentDir')}"
-                             value="${getCcwProjectRoot()}">
+                             value="${getCcwProjectRootCodex()}">
                      <button class="p-1 text-muted-foreground hover:text-foreground"
                              onclick="setCcwProjectRootToCurrent()"
                              title="${t('mcp.useCurrentProject')}">
@@ -272,7 +296,7 @@ async function renderMcpManager() {
                      <input type="text"
                             class="ccw-allowed-dirs-input flex-1 px-2 py-1 text-xs bg-background border border-border rounded focus:outline-none focus:ring-1 focus:ring-primary"
                             placeholder="${t('mcp.allowedDirsPlaceholder')}"
-                             value="${getCcwAllowedDirs()}">
+                             value="${getCcwAllowedDirsCodex()}">
                    </div>
                  </div>
                </div>
--- a/ccw/src/templates/dashboard-js/views/rules-manager.js
+++ b/ccw/src/templates/dashboard-js/views/rules-manager.js
@@ -638,9 +638,26 @@ function addRulePath() {

 function removeRulePath(index) {
  ruleCreateState.paths.splice(index, 1);
-  // Re-render paths list
-  closeRuleCreateModal();
-  openRuleCreateModal();
+
+  // Re-render paths list without closing modal
+  const pathsList = document.getElementById('rulePathsList');
+  if (pathsList) {
+    pathsList.innerHTML = ruleCreateState.paths.map((path, idx) => `
+      <div class="flex gap-2">
+        <input type="text" class="rule-path-input flex-1 px-3 py-2 bg-background border border-border rounded-lg text-sm focus:outline-none focus:ring-2 focus:ring-primary"
+               placeholder="src/**/*.ts"
+               value="${path}"
+               data-index="${idx}">
+        ${idx > 0 ? `
+          <button class="px-3 py-2 text-destructive hover:bg-destructive/10 rounded-lg transition-colors"
+                  onclick="removeRulePath(${idx})">
+            <i data-lucide="x" class="w-4 h-4"></i>
+          </button>
+        ` : ''}
+      </div>
+    `).join('');
+    if (typeof lucide !== 'undefined') lucide.createIcons();
+  }
 }

 function switchRuleCreateMode(mode) {
@@ -674,9 +691,21 @@ function switchRuleCreateMode(mode) {
    if (contentSection) contentSection.style.display = 'block';
  }

-  // Re-render modal to update button states
-  closeRuleCreateModal();
-  openRuleCreateModal();
+  // Update mode button styles without re-rendering
+  const modeButtons = document.querySelectorAll('#ruleCreateModal .mode-btn');
+  modeButtons.forEach(btn => {
+    const btnText = btn.querySelector('.font-medium')?.textContent || '';
+    const isInput = btnText.includes(t('rules.manualInput'));
+    const isCliGenerate = btnText.includes(t('rules.cliGenerate'));
+
+    if ((isInput && mode === 'input') || (isCliGenerate && mode === 'cli-generate')) {
+      btn.classList.remove('border-border', 'hover:border-primary/50');
+      btn.classList.add('border-primary', 'bg-primary/10');
+    } else {
+      btn.classList.remove('border-primary', 'bg-primary/10');
+      btn.classList.add('border-border', 'hover:border-primary/50');
+    }
+  });
 }

 function switchRuleGenerationType(type) {
--- a/ccw/src/templates/dashboard-js/views/skills-manager.js
+++ b/ccw/src/templates/dashboard-js/views/skills-manager.js
@@ -153,10 +153,11 @@ function renderSkillCard(skill, location) {
  const locationIcon = location === 'project' ? 'folder' : 'user';
  const locationClass = location === 'project' ? 'text-primary' : 'text-indigo';
  const locationBg = location === 'project' ? 'bg-primary/10' : 'bg-indigo/10';
+  const folderName = skill.folderName || skill.name;

  return `
    <div class="skill-card bg-card border border-border rounded-lg p-4 hover:shadow-md transition-all cursor-pointer"
-         onclick="showSkillDetail('${escapeHtml(skill.name)}', '${location}')">
+         onclick="showSkillDetail('${escapeHtml(folderName)}', '${location}')">
      <div class="flex items-start justify-between mb-3">
        <div class="flex items-center gap-3">
          <div class="w-10 h-10 ${locationBg} rounded-lg flex items-center justify-center">
@@ -198,6 +199,7 @@ function renderSkillCard(skill, location) {
 function renderSkillDetailPanel(skill) {
  const hasAllowedTools = skill.allowedTools && skill.allowedTools.length > 0;
  const hasSupportingFiles = skill.supportingFiles && skill.supportingFiles.length > 0;
+  const folderName = skill.folderName || skill.name;

  return `
    <div class="skill-detail-panel fixed top-0 right-0 w-1/2 max-w-xl h-full bg-card border-l border-border shadow-lg z-50 flex flex-col">
@@ -243,20 +245,54 @@ function renderSkillDetailPanel(skill) {
            </div>
          ` : ''}

-          <!-- Supporting Files -->
-          ${hasSupportingFiles ? `
-            <div>
-              <h4 class="text-sm font-semibold text-foreground mb-2">${t('skills.supportingFiles')}</h4>
-              <div class="space-y-2">
-                ${skill.supportingFiles.map(file => `
-                  <div class="flex items-center gap-2 p-2 bg-muted/50 rounded-lg">
-                    <i data-lucide="file-text" class="w-4 h-4 text-muted-foreground"></i>
-                    <span class="text-sm font-mono text-foreground">${escapeHtml(file)}</span>
-                  </div>
-                `).join('')}
+          <!-- Skill Files (SKILL.md + Supporting Files) -->
+          <div>
+            <h4 class="text-sm font-semibold text-foreground mb-2">${t('skills.files') || 'Files'}</h4>
+            <div class="space-y-2">
+              <!-- SKILL.md (main file) -->
+              <div class="flex items-center justify-between p-2 bg-primary/5 border border-primary/20 rounded-lg cursor-pointer hover:bg-primary/10 transition-colors"
+                   onclick="viewSkillFile('${escapeHtml(folderName)}', 'SKILL.md', '${skill.location}')">
+                <div class="flex items-center gap-2">
+                  <i data-lucide="file-text" class="w-4 h-4 text-primary"></i>
+                  <span class="text-sm font-mono text-foreground font-medium">SKILL.md</span>
+                </div>
+                <div class="flex items-center gap-1">
+                  <button class="p-1 text-primary hover:bg-primary/20 rounded transition-colors"
+                          onclick="event.stopPropagation(); editSkillFile('${escapeHtml(folderName)}', 'SKILL.md', '${skill.location}')"
+                          title="${t('common.edit')}">
+                    <i data-lucide="edit-2" class="w-3.5 h-3.5"></i>
+                  </button>
+                </div>
              </div>
+              ${hasSupportingFiles ? skill.supportingFiles.map(file => {
+                const isDir = file.endsWith('/');
+                const dirName = isDir ? file.slice(0, -1) : file;
+                return `
+              <!-- Supporting file: ${escapeHtml(file)} -->
+              <div class="skill-file-item" data-path="${escapeHtml(dirName)}">
+                <div class="flex items-center justify-between p-2 bg-muted/50 rounded-lg cursor-pointer hover:bg-muted transition-colors"
+                     onclick="${isDir ? `toggleSkillFolder('${escapeHtml(folderName)}', '${escapeHtml(dirName)}', '${skill.location}', this)` : `viewSkillFile('${escapeHtml(folderName)}', '${escapeHtml(file)}', '${skill.location}')`}">
+                  <div class="flex items-center gap-2">
+                    <i data-lucide="${isDir ? 'folder' : 'file-text'}" class="w-4 h-4 text-muted-foreground ${isDir ? 'folder-icon' : ''}"></i>
+                    <span class="text-sm font-mono text-foreground">${escapeHtml(isDir ? dirName : file)}</span>
+                    ${isDir ? '<i data-lucide="chevron-right" class="w-3 h-3 text-muted-foreground folder-chevron transition-transform"></i>' : ''}
+                  </div>
+                  ${!isDir ? `
+                  <div class="flex items-center gap-1">
+                    <button class="p-1 text-muted-foreground hover:text-foreground hover:bg-muted rounded transition-colors"
+                            onclick="event.stopPropagation(); editSkillFile('${escapeHtml(folderName)}', '${escapeHtml(file)}', '${skill.location}')"
+                            title="${t('common.edit')}">
+                      <i data-lucide="edit-2" class="w-3.5 h-3.5"></i>
+                    </button>
+                  </div>
+                  ` : ''}
+                </div>
+                <div class="folder-contents hidden ml-4 mt-1 space-y-1"></div>
+              </div>
+              `;
+              }).join('') : ''}
            </div>
-          ` : ''}
+          </div>

          <!-- Path -->
          <div>
@@ -269,12 +305,12 @@ function renderSkillDetailPanel(skill) {
      <!-- Actions -->
      <div class="px-5 py-4 border-t border-border flex justify-between">
        <button class="px-4 py-2 text-sm text-destructive hover:bg-destructive/10 rounded-lg transition-colors flex items-center gap-2"
-                onclick="deleteSkill('${escapeHtml(skill.name)}', '${skill.location}')">
+                onclick="deleteSkill('${escapeHtml(folderName)}', '${skill.location}')">
          <i data-lucide="trash-2" class="w-4 h-4"></i>
          ${t('common.delete')}
        </button>
        <button class="px-4 py-2 text-sm bg-primary text-primary-foreground rounded-lg hover:opacity-90 transition-opacity flex items-center gap-2"
-                onclick="editSkill('${escapeHtml(skill.name)}', '${skill.location}')">
+                onclick="editSkill('${escapeHtml(folderName)}', '${skill.location}')">
          <i data-lucide="edit" class="w-4 h-4"></i>
          ${t('common.edit')}
        </button>
@@ -525,7 +561,7 @@ function openSkillCreateModal() {
        </div>

        <!-- Footer -->
-        <div class="flex items-center justify-end gap-3 px-6 py-4 border-t border-border">
+        <div id="skillModalFooter" class="flex items-center justify-end gap-3 px-6 py-4 border-t border-border">
          <button class="px-4 py-2 text-sm text-muted-foreground hover:text-foreground transition-colors"
                  onclick="closeSkillCreateModal()">
            ${t('common.cancel')}
@@ -588,16 +624,76 @@ function selectSkillLocation(location) {

 function switchSkillCreateMode(mode) {
  skillCreateState.mode = mode;
-  // Re-render modal
-  closeSkillCreateModal();
-  openSkillCreateModal();
+
+  // Toggle visibility of mode sections
+  const importSection = document.getElementById('skillImportMode');
+  const cliGenerateSection = document.getElementById('skillCliGenerateMode');
+  const footerContainer = document.getElementById('skillModalFooter');
+
+  if (importSection) importSection.style.display = mode === 'import' ? 'block' : 'none';
+  if (cliGenerateSection) cliGenerateSection.style.display = mode === 'cli-generate' ? 'block' : 'none';
+
+  // Update mode button styles
+  const modeButtons = document.querySelectorAll('#skillCreateModal .mode-btn');
+  modeButtons.forEach(btn => {
+    const btnText = btn.querySelector('.font-medium')?.textContent || '';
+    const isImport = btnText.includes(t('skills.importFolder'));
+    const isCliGenerate = btnText.includes(t('skills.cliGenerate'));
+
+    if ((isImport && mode === 'import') || (isCliGenerate && mode === 'cli-generate')) {
+      btn.classList.remove('border-border', 'hover:border-primary/50');
+      btn.classList.add('border-primary', 'bg-primary/10');
+    } else {
+      btn.classList.remove('border-primary', 'bg-primary/10');
+      btn.classList.add('border-border', 'hover:border-primary/50');
+    }
+  });
+
+  // Update footer buttons
+  if (footerContainer) {
+    if (mode === 'import') {
+      footerContainer.innerHTML = `
+        <button class="px-4 py-2 text-sm text-muted-foreground hover:text-foreground transition-colors"
+                onclick="closeSkillCreateModal()">
+          ${t('common.cancel')}
+        </button>
+        <button class="px-4 py-2 text-sm bg-primary/10 text-primary rounded-lg hover:bg-primary/20 transition-colors"
+                onclick="validateSkillImport()">
+          ${t('skills.validate')}
+        </button>
+        <button class="px-4 py-2 text-sm bg-primary text-primary-foreground rounded-lg hover:opacity-90 transition-opacity"
+                onclick="createSkill()">
+          ${t('skills.import')}
+        </button>
+      `;
+    } else {
+      footerContainer.innerHTML = `
+        <button class="px-4 py-2 text-sm text-muted-foreground hover:text-foreground transition-colors"
+                onclick="closeSkillCreateModal()">
+          ${t('common.cancel')}
+        </button>
+        <button class="px-4 py-2 text-sm bg-primary text-primary-foreground rounded-lg hover:opacity-90 transition-opacity flex items-center gap-2"
+                onclick="createSkill()">
+          <i data-lucide="sparkles" class="w-4 h-4"></i>
+          ${t('skills.generate')}
+        </button>
+      `;
+    }
+    if (typeof lucide !== 'undefined') lucide.createIcons();
+  }
 }

 function switchSkillGenerationType(type) {
  skillCreateState.generationType = type;
-  // Re-render modal
-  closeSkillCreateModal();
-  openSkillCreateModal();
+
+  // Toggle visibility of description area
+  const descriptionArea = document.getElementById('skillDescriptionArea');
+  if (descriptionArea) {
+    descriptionArea.style.display = type === 'description' ? 'block' : 'none';
+  }
+
+  // Update generation type button styles (only the description button is active, template is disabled)
+  // No need to update button styles since template button is disabled
 }

 function browseSkillFolder() {
@@ -817,3 +913,271 @@ async function createSkill() {
    }
  }
 }
+
+
+// ========== Skill File View/Edit Functions ==========
+
+var skillFileEditorState = {
+  skillName: '',
+  fileName: '',
+  location: '',
+  content: '',
+  isEditing: false
+};
+
+async function viewSkillFile(skillName, fileName, location) {
+  try {
+    const response = await fetch(
+      '/api/skills/' + encodeURIComponent(skillName) + '/file?filename=' + encodeURIComponent(fileName) +
+      '&location=' + location + '&path=' + encodeURIComponent(projectPath)
+    );
+
+    if (!response.ok) {
+      const error = await response.json();
+      throw new Error(error.error || 'Failed to load file');
+    }
+
+    const data = await response.json();
+
+    skillFileEditorState = {
+      skillName,
+      fileName,
+      location,
+      content: data.content,
+      isEditing: false
+    };
+
+    renderSkillFileModal();
+  } catch (err) {
+    console.error('Failed to load skill file:', err);
+    if (window.showToast) {
+      showToast(err.message || t('skills.fileLoadError') || 'Failed to load file', 'error');
+    }
+  }
+}
+
+function editSkillFile(skillName, fileName, location) {
+  viewSkillFile(skillName, fileName, location).then(() => {
+    skillFileEditorState.isEditing = true;
+    renderSkillFileModal();
+  });
+}
+
+function renderSkillFileModal() {
+  // Remove existing modal if any
+  const existingModal = document.getElementById('skillFileModal');
+  if (existingModal) existingModal.remove();
+
+  const { skillName, fileName, content, isEditing, location } = skillFileEditorState;
+
+  const modalHtml = `
+    <div class="modal-overlay fixed inset-0 bg-black/50 z-[60] flex items-center justify-center" onclick="closeSkillFileModal(event)">
+      <div class="modal-dialog bg-card rounded-lg shadow-lg w-full max-w-4xl max-h-[90vh] mx-4 flex flex-col" onclick="event.stopPropagation()">
+        <!-- Header -->
+        <div class="flex items-center justify-between px-6 py-4 border-b border-border">
+          <div class="flex items-center gap-3">
+            <i data-lucide="file-text" class="w-5 h-5 text-primary"></i>
+            <div>
+              <h3 class="text-lg font-semibold text-foreground font-mono">${escapeHtml(fileName)}</h3>
+              <p class="text-xs text-muted-foreground">${escapeHtml(skillName)} / ${location}</p>
+            </div>
+          </div>
+          <div class="flex items-center gap-2">
+            ${!isEditing ? `
+              <button class="px-3 py-1.5 text-sm bg-primary/10 text-primary rounded-lg hover:bg-primary/20 transition-colors flex items-center gap-1"
+                      onclick="toggleSkillFileEdit()">
+                <i data-lucide="edit-2" class="w-4 h-4"></i>
+                ${t('common.edit')}
+              </button>
+            ` : ''}
+            <button class="w-8 h-8 flex items-center justify-center text-xl text-muted-foreground hover:text-foreground hover:bg-hover rounded"
+                    onclick="closeSkillFileModal()">&times;</button>
+          </div>
+        </div>
+
+        <!-- Content -->
+        <div class="flex-1 overflow-hidden p-4">
+          ${isEditing ? `
+            <textarea id="skillFileContent"
+                      class="w-full h-full min-h-[400px] px-4 py-3 bg-background border border-border rounded-lg text-sm font-mono focus:outline-none focus:ring-2 focus:ring-primary resize-none"
+                      spellcheck="false">${escapeHtml(content)}</textarea>
+          ` : `
+            <div class="w-full h-full min-h-[400px] overflow-auto">
+              <pre class="px-4 py-3 bg-muted/30 rounded-lg text-sm font-mono whitespace-pre-wrap break-words">${escapeHtml(content)}</pre>
+            </div>
+          `}
+        </div>
+
+        <!-- Footer -->
+        ${isEditing ? `
+          <div class="flex items-center justify-end gap-3 px-6 py-4 border-t border-border">
+            <button class="px-4 py-2 text-sm text-muted-foreground hover:text-foreground transition-colors"
+                    onclick="cancelSkillFileEdit()">
+              ${t('common.cancel')}
+            </button>
+            <button class="px-4 py-2 text-sm bg-primary text-primary-foreground rounded-lg hover:opacity-90 transition-opacity flex items-center gap-2"
+                    onclick="saveSkillFile()">
+              <i data-lucide="save" class="w-4 h-4"></i>
+              ${t('common.save')}
+            </button>
+          </div>
+        ` : ''}
+      </div>
+    </div>
+  `;
+
+  const modalContainer = document.createElement('div');
+  modalContainer.id = 'skillFileModal';
+  modalContainer.innerHTML = modalHtml;
+  document.body.appendChild(modalContainer);
+
+  if (typeof lucide !== 'undefined') lucide.createIcons();
+}
+
+function closeSkillFileModal(event) {
+  if (event && event.target !== event.currentTarget) return;
+  const modal = document.getElementById('skillFileModal');
+  if (modal) modal.remove();
+  skillFileEditorState = { skillName: '', fileName: '', location: '', content: '', isEditing: false };
+}
+
+function toggleSkillFileEdit() {
+  skillFileEditorState.isEditing = true;
+  renderSkillFileModal();
+}
+
+function cancelSkillFileEdit() {
+  skillFileEditorState.isEditing = false;
+  renderSkillFileModal();
+}
+
+async function saveSkillFile() {
+  const contentTextarea = document.getElementById('skillFileContent');
+  if (!contentTextarea) return;
+
+  const newContent = contentTextarea.value;
+  const { skillName, fileName, location } = skillFileEditorState;
+
+  try {
+    const response = await fetch('/api/skills/' + encodeURIComponent(skillName) + '/file', {
+      method: 'POST',
+      headers: { 'Content-Type': 'application/json' },
+      body: JSON.stringify({
+        fileName,
+        content: newContent,
+        location,
+        projectPath
+      })
+    });
+
+    if (!response.ok) {
+      const error = await response.json();
+      throw new Error(error.error || 'Failed to save file');
+    }
+
+    // Update state and close edit mode
+    skillFileEditorState.content = newContent;
+    skillFileEditorState.isEditing = false;
+    renderSkillFileModal();
+
+    // Refresh skill detail if SKILL.md was edited
+    if (fileName === 'SKILL.md') {
+      await loadSkillsData();
+      // Reload current skill detail
+      if (selectedSkill) {
+        await showSkillDetail(skillName, location);
+      }
+    }
+
+    if (window.showToast) {
+      showToast(t('skills.fileSaved') || 'File saved successfully', 'success');
+    }
+  } catch (err) {
+    console.error('Failed to save skill file:', err);
+    if (window.showToast) {
+      showToast(err.message || t('skills.fileSaveError') || 'Failed to save file', 'error');
+    }
+  }
+}
+
+
+
+// ========== Skill Folder Expansion Functions ==========
+
+var expandedFolders = new Set();
+
+async function toggleSkillFolder(skillName, subPath, location, element) {
+  const fileItem = element.closest('.skill-file-item');
+  if (!fileItem) return;
+
+  const contentsDiv = fileItem.querySelector('.folder-contents');
+  const chevron = element.querySelector('.folder-chevron');
+  const folderIcon = element.querySelector('.folder-icon');
+  const folderKey = `${skillName}:${subPath}:${location}`;
+
+  if (expandedFolders.has(folderKey)) {
+    // Collapse folder
+    expandedFolders.delete(folderKey);
+    contentsDiv.classList.add('hidden');
+    contentsDiv.innerHTML = '';
+    if (chevron) chevron.style.transform = '';
+    if (folderIcon) folderIcon.setAttribute('data-lucide', 'folder');
+    if (typeof lucide !== 'undefined') lucide.createIcons();
+  } else {
+    // Expand folder
+    try {
+      const response = await fetch(
+        '/api/skills/' + encodeURIComponent(skillName) + '/dir?subpath=' + encodeURIComponent(subPath) +
+        '&location=' + location + '&path=' + encodeURIComponent(projectPath)
+      );
+
+      if (!response.ok) {
+        const error = await response.json();
+        throw new Error(error.error || 'Failed to load folder');
+      }
+
+      const data = await response.json();
+
+      expandedFolders.add(folderKey);
+      if (chevron) chevron.style.transform = 'rotate(90deg)';
+      if (folderIcon) folderIcon.setAttribute('data-lucide', 'folder-open');
+
+      // Render folder contents
+      contentsDiv.innerHTML = data.files.map(file => {
+        const filePath = file.path;
+        const isDir = file.isDirectory;
+        return `
+          <div class="skill-file-item" data-path="${escapeHtml(filePath)}">
+            <div class="flex items-center justify-between p-2 bg-muted/30 rounded-lg cursor-pointer hover:bg-muted/50 transition-colors"
+                 onclick="${isDir ? `toggleSkillFolder('${escapeHtml(skillName)}', '${escapeHtml(filePath)}', '${location}', this)` : `viewSkillFile('${escapeHtml(skillName)}', '${escapeHtml(filePath)}', '${location}')`}">
+              <div class="flex items-center gap-2">
+                <i data-lucide="${isDir ? 'folder' : 'file-text'}" class="w-4 h-4 text-muted-foreground ${isDir ? 'folder-icon' : ''}"></i>
+                <span class="text-sm font-mono text-foreground">${escapeHtml(file.name)}</span>
+                ${isDir ? '<i data-lucide="chevron-right" class="w-3 h-3 text-muted-foreground folder-chevron transition-transform"></i>' : ''}
+              </div>
+              ${!isDir ? `
+              <div class="flex items-center gap-1">
+                <button class="p-1 text-muted-foreground hover:text-foreground hover:bg-muted rounded transition-colors"
+                        onclick="event.stopPropagation(); editSkillFile('${escapeHtml(skillName)}', '${escapeHtml(filePath)}', '${location}')"
+                        title="${t('common.edit')}">
+                  <i data-lucide="edit-2" class="w-3.5 h-3.5"></i>
+                </button>
+              </div>
+              ` : ''}
+            </div>
+            <div class="folder-contents hidden ml-4 mt-1 space-y-1"></div>
+          </div>
+        `;
+      }).join('');
+
+      contentsDiv.classList.remove('hidden');
+      if (typeof lucide !== 'undefined') lucide.createIcons();
+    } catch (err) {
+      console.error('Failed to load folder contents:', err);
+      if (window.showToast) {
+        showToast(err.message || 'Failed to load folder', 'error');
+      }
+    }
+  }
+}
+
--- a/ccw/src/tools/cli-executor.ts
+++ b/ccw/src/tools/cli-executor.ts
@@ -5,6 +5,7 @@

 import { z } from 'zod';
 import type { ToolSchema, ToolResult } from '../types/tool.js';
+import type { HistoryIndexEntry } from './cli-history-store.js';
 import { spawn, ChildProcess } from 'child_process';
 import { existsSync, mkdirSync, readFileSync, writeFileSync, unlinkSync, readdirSync, statSync } from 'fs';
 import { join, relative } from 'path';
@@ -1982,6 +1983,7 @@ export async function getEnrichedConversation(baseDir: string, ccwId: string) {

 /**
 * Get history with native session info
+ * Supports recursive querying of child projects
 */
 export async function getHistoryWithNativeInfo(baseDir: string, options?: {
  limit?: number;
@@ -1990,9 +1992,75 @@ export async function getHistoryWithNativeInfo(baseDir: string, options?: {
  status?: string | null;
  category?: ExecutionCategory | null;
  search?: string | null;
+  recursive?: boolean;
 }) {
-  const store = await getSqliteStore(baseDir);
-  return store.getHistoryWithNativeInfo(options || {});
+  const { limit = 50, recursive = false, ...queryOptions } = options || {};
+
+  // Non-recursive mode: query single project
+  if (!recursive) {
+    const store = await getSqliteStore(baseDir);
+    return store.getHistoryWithNativeInfo({ limit, ...queryOptions });
+  }
+
+  // Recursive mode: aggregate data from parent and all child projects
+  const { scanChildProjectsAsync } = await import('../config/storage-paths.js');
+  const childProjects = await scanChildProjectsAsync(baseDir);
+
+  // Use the same type as store.getHistoryWithNativeInfo returns
+  type ExecutionWithNativeAndSource = HistoryIndexEntry & {
+    hasNativeSession: boolean;
+    nativeSessionId?: string;
+    nativeSessionPath?: string;
+  };
+
+  const allExecutions: ExecutionWithNativeAndSource[] = [];
+  let totalCount = 0;
+
+  // Query parent project
+  try {
+    const parentStore = await getSqliteStore(baseDir);
+    const parentResult = parentStore.getHistoryWithNativeInfo({ limit, ...queryOptions });
+    totalCount += parentResult.total;
+
+    for (const exec of parentResult.executions) {
+      allExecutions.push({ ...exec, sourceDir: baseDir });
+    }
+  } catch (error) {
+    if (process.env.DEBUG) {
+      console.error(`[CLI History] Failed to query parent project ${baseDir}:`, error);
+    }
+  }
+
+  // Query all child projects
+  for (const child of childProjects) {
+    try {
+      const childStore = await getSqliteStore(child.projectPath);
+      const childResult = childStore.getHistoryWithNativeInfo({ limit, ...queryOptions });
+      totalCount += childResult.total;
+
+      for (const exec of childResult.executions) {
+        allExecutions.push({ ...exec, sourceDir: child.projectPath });
+      }
+    } catch (error) {
+      if (process.env.DEBUG) {
+        console.error(`[CLI History] Failed to query child project ${child.projectPath}:`, error);
+      }
+    }
+  }
+
+  // Sort by updated_at descending and apply limit
+  allExecutions.sort((a, b) => {
+    const timeA = a.updated_at ? new Date(a.updated_at).getTime() : new Date(a.timestamp).getTime();
+    const timeB = b.updated_at ? new Date(b.updated_at).getTime() : new Date(b.timestamp).getTime();
+    return timeB - timeA;
+  });
+  const limitedExecutions = allExecutions.slice(0, limit);
+
+  return {
+    total: totalCount,
+    count: limitedExecutions.length,
+    executions: limitedExecutions
+  };
 }

 // Export types
--- a/ccw/src/tools/codex-lens.ts
+++ b/ccw/src/tools/codex-lens.ts
@@ -75,6 +75,8 @@ interface ReadyStatus {
 interface SemanticStatus {
  available: boolean;
  backend?: string;
+  accelerator?: string;
+  providers?: string[];
  error?: string;
 }

@@ -190,18 +192,39 @@ async function checkSemanticStatus(): Promise<SemanticStatus> {
    return { available: false, error: 'CodexLens not installed' };
  }

-  // Check semantic module availability
+  // Check semantic module availability and accelerator info
  return new Promise((resolve) => {
    const checkCode = `
 import sys
+import json
 try:
    from codexlens.semantic import SEMANTIC_AVAILABLE, SEMANTIC_BACKEND
-    if SEMANTIC_AVAILABLE:
-        print(f"available:{SEMANTIC_BACKEND}")
-    else:
-        print("unavailable")
+    result = {"available": SEMANTIC_AVAILABLE, "backend": SEMANTIC_BACKEND if SEMANTIC_AVAILABLE else None}
+
+    # Get ONNX providers for accelerator info
+    try:
+        import onnxruntime
+        providers = onnxruntime.get_available_providers()
+        result["providers"] = providers
+
+        # Determine accelerator type
+        if "CUDAExecutionProvider" in providers or "TensorrtExecutionProvider" in providers:
+            result["accelerator"] = "CUDA"
+        elif "DmlExecutionProvider" in providers:
+            result["accelerator"] = "DirectML"
+        elif "CoreMLExecutionProvider" in providers:
+            result["accelerator"] = "CoreML"
+        elif "ROCMExecutionProvider" in providers:
+            result["accelerator"] = "ROCm"
+        else:
+            result["accelerator"] = "CPU"
+    except:
+        result["providers"] = []
+        result["accelerator"] = "CPU"
+
+    print(json.dumps(result))
 except Exception as e:
-    print(f"error:{e}")
+    print(json.dumps({"available": False, "error": str(e)}))
 `;
    const child = spawn(VENV_PYTHON, ['-c', checkCode], {
      stdio: ['ignore', 'pipe', 'pipe'],
@@ -220,12 +243,16 @@ except Exception as e:

    child.on('close', (code) => {
      const output = stdout.trim();
-      if (output.startsWith('available:')) {
-        const backend = output.split(':')[1];
-        resolve({ available: true, backend });
-      } else if (output === 'unavailable') {
-        resolve({ available: false, error: 'Semantic dependencies not installed' });
-      } else {
+      try {
+        const result = JSON.parse(output);
+        resolve({
+          available: result.available || false,
+          backend: result.backend,
+          accelerator: result.accelerator || 'CPU',
+          providers: result.providers || [],
+          error: result.error
+        });
+      } catch {
        resolve({ available: false, error: output || stderr || 'Unknown error' });
      }
    });
@@ -237,10 +264,66 @@ except Exception as e:
 }

 /**
- * Install semantic search dependencies (fastembed, ONNX-based, ~200MB)
+ * GPU acceleration mode for semantic search
+ */
+type GpuMode = 'cpu' | 'cuda' | 'directml';
+
+/**
+ * Detect available GPU acceleration
+ * @returns Detected GPU mode and info
+ */
+async function detectGpuSupport(): Promise<{ mode: GpuMode; available: GpuMode[]; info: string }> {
+  const available: GpuMode[] = ['cpu'];
+  let detectedInfo = 'CPU only';
+
+  // Check for NVIDIA GPU (CUDA)
+  try {
+    if (process.platform === 'win32') {
+      execSync('nvidia-smi', { stdio: 'pipe' });
+      available.push('cuda');
+      detectedInfo = 'NVIDIA GPU detected (CUDA available)';
+    } else {
+      execSync('which nvidia-smi', { stdio: 'pipe' });
+      available.push('cuda');
+      detectedInfo = 'NVIDIA GPU detected (CUDA available)';
+    }
+  } catch {
+    // NVIDIA not available
+  }
+
+  // On Windows, DirectML is always available if DirectX 12 is supported
+  if (process.platform === 'win32') {
+    try {
+      // Check for DirectX 12 support via dxdiag or registry
+      // DirectML works on most modern Windows 10/11 systems
+      available.push('directml');
+      if (available.includes('cuda')) {
+        detectedInfo = 'NVIDIA GPU detected (CUDA & DirectML available)';
+      } else {
+        detectedInfo = 'DirectML available (Windows GPU acceleration)';
+      }
+    } catch {
+      // DirectML check failed
+    }
+  }
+
+  // Recommend best available mode
+  let recommendedMode: GpuMode = 'cpu';
+  if (process.platform === 'win32' && available.includes('directml')) {
+    recommendedMode = 'directml'; // DirectML is easier on Windows (no CUDA toolkit needed)
+  } else if (available.includes('cuda')) {
+    recommendedMode = 'cuda';
+  }
+
+  return { mode: recommendedMode, available, info: detectedInfo };
+}
+
+/**
+ * Install semantic search dependencies with optional GPU acceleration
+ * @param gpuMode - GPU acceleration mode: 'cpu', 'cuda', or 'directml'
 * @returns Bootstrap result
 */
-async function installSemantic(): Promise<BootstrapResult> {
+async function installSemantic(gpuMode: GpuMode = 'cpu'): Promise<BootstrapResult> {
  // First ensure CodexLens is installed
  const venvStatus = await checkVenvStatus();
  if (!venvStatus.ready) {
@@ -252,42 +335,106 @@ async function installSemantic(): Promise<BootstrapResult> {
      ? join(CODEXLENS_VENV, 'Scripts', 'pip.exe')
      : join(CODEXLENS_VENV, 'bin', 'pip');

-  return new Promise((resolve) => {
-    console.log('[CodexLens] Installing semantic search dependencies (fastembed)...');
-    console.log('[CodexLens] Using ONNX-based fastembed backend (~200MB)');
+  // IMPORTANT: Uninstall all onnxruntime variants first to prevent conflicts
+  // Having multiple onnxruntime packages causes provider detection issues
+  const onnxVariants = ['onnxruntime', 'onnxruntime-gpu', 'onnxruntime-directml'];
+  console.log(`[CodexLens] Cleaning up existing ONNX Runtime packages...`);

-    const child = spawn(pipPath, ['install', 'numpy>=1.24', 'fastembed>=0.2'], {
+  for (const pkg of onnxVariants) {
+    try {
+      execSync(`"${pipPath}" uninstall ${pkg} -y`, { stdio: 'pipe' });
+      console.log(`[CodexLens] Removed ${pkg}`);
+    } catch {
+      // Package not installed, ignore
+    }
+  }
+
+  // Build package list based on GPU mode
+  const packages = ['numpy>=1.24', 'fastembed>=0.5', 'hnswlib>=0.8.0'];
+
+  let modeDescription = 'CPU (ONNX Runtime)';
+  let onnxPackage = 'onnxruntime>=1.18.0'; // Default CPU
+
+  if (gpuMode === 'cuda') {
+    onnxPackage = 'onnxruntime-gpu>=1.18.0';
+    modeDescription = 'NVIDIA CUDA GPU acceleration';
+  } else if (gpuMode === 'directml') {
+    onnxPackage = 'onnxruntime-directml>=1.18.0';
+    modeDescription = 'Windows DirectML GPU acceleration';
+  }
+
+  return new Promise((resolve) => {
+    console.log(`[CodexLens] Installing semantic search dependencies...`);
+    console.log(`[CodexLens] Mode: ${modeDescription}`);
+    console.log(`[CodexLens] ONNX Runtime: ${onnxPackage}`);
+    console.log(`[CodexLens] Packages: ${packages.join(', ')}`);
+
+    // Install ONNX Runtime first with force-reinstall to ensure clean state
+    const installOnnx = spawn(pipPath, ['install', '--force-reinstall', onnxPackage], {
      stdio: ['ignore', 'pipe', 'pipe'],
-      timeout: 600000, // 10 minutes for potential model download
+      timeout: 600000, // 10 minutes for GPU packages
    });

-    let stdout = '';
-    let stderr = '';
+    let onnxStdout = '';
+    let onnxStderr = '';

-    child.stdout.on('data', (data) => {
-      stdout += data.toString();
-      // Log progress
+    installOnnx.stdout.on('data', (data) => {
+      onnxStdout += data.toString();
      const line = data.toString().trim();
-      if (line.includes('Downloading') || line.includes('Installing') || line.includes('Collecting')) {
+      if (line.includes('Downloading') || line.includes('Installing')) {
        console.log(`[CodexLens] ${line}`);
      }
    });

-    child.stderr.on('data', (data) => {
-      stderr += data.toString();
+    installOnnx.stderr.on('data', (data) => {
+      onnxStderr += data.toString();
    });

-    child.on('close', (code) => {
-      if (code === 0) {
-        console.log('[CodexLens] Semantic dependencies installed successfully');
-        resolve({ success: true });
-      } else {
-        resolve({ success: false, error: `Installation failed: ${stderr || stdout}` });
+    installOnnx.on('close', (onnxCode) => {
+      if (onnxCode !== 0) {
+        resolve({ success: false, error: `Failed to install ${onnxPackage}: ${onnxStderr || onnxStdout}` });
+        return;
      }
+
+      console.log(`[CodexLens] ${onnxPackage} installed successfully`);
+
+      // Now install remaining packages
+      const child = spawn(pipPath, ['install', ...packages], {
+        stdio: ['ignore', 'pipe', 'pipe'],
+        timeout: 600000,
+      });
+
+      let stdout = '';
+      let stderr = '';
+
+      child.stdout.on('data', (data) => {
+        stdout += data.toString();
+        const line = data.toString().trim();
+        if (line.includes('Downloading') || line.includes('Installing') || line.includes('Collecting')) {
+          console.log(`[CodexLens] ${line}`);
+        }
+      });
+
+      child.stderr.on('data', (data) => {
+        stderr += data.toString();
+      });
+
+      child.on('close', (code) => {
+        if (code === 0) {
+          console.log(`[CodexLens] Semantic dependencies installed successfully (${gpuMode} mode)`);
+          resolve({ success: true, message: `Installed with ${modeDescription}` });
+        } else {
+          resolve({ success: false, error: `Installation failed: ${stderr || stdout}` });
+        }
+      });
+
+      child.on('error', (err) => {
+        resolve({ success: false, error: `Failed to run pip: ${err.message}` });
+      });
    });

-    child.on('error', (err) => {
-      resolve({ success: false, error: `Failed to run pip: ${err.message}` });
+    installOnnx.on('error', (err) => {
+      resolve({ success: false, error: `Failed to install ONNX Runtime: ${err.message}` });
    });
  });
 }
@@ -1126,7 +1273,8 @@ function isIndexingInProgress(): boolean {
 export type { ProgressInfo, ExecuteOptions };

 // Export for direct usage
-export { ensureReady, executeCodexLens, checkVenvStatus, bootstrapVenv, checkSemanticStatus, installSemantic, uninstallCodexLens, cancelIndexing, isIndexingInProgress };
+export { ensureReady, executeCodexLens, checkVenvStatus, bootstrapVenv, checkSemanticStatus, installSemantic, detectGpuSupport, uninstallCodexLens, cancelIndexing, isIndexingInProgress };
+export type { GpuMode };

 // Backward-compatible export for tests
 export const codexLensTool = {
--- a/ccw/src/tools/smart-search.ts
+++ b/ccw/src/tools/smart-search.ts
@@ -244,6 +244,7 @@ interface SearchMetadata {
  warning?: string;
  note?: string;
  index_status?: 'indexed' | 'not_indexed' | 'partial';
+  fallback?: string;  // Fallback mode used (e.g., 'fuzzy')
  fallback_history?: string[];
  suggested_weights?: Record<string, number>;
  // Tokenization metadata (ripgrep mode)
@@ -774,6 +775,7 @@ async function executeRipgrepMode(params: Params): Promise<SearchResult> {

    let stdout = '';
    let stderr = '';
+    let resultLimitReached = false;

    child.stdout.on('data', (data) => {
      stdout += data.toString();
@@ -786,8 +788,16 @@ async function executeRipgrepMode(params: Params): Promise<SearchResult> {
    child.on('close', (code) => {
      const results: ExactMatch[] = [];
      const lines = stdout.split('\n').filter((line) => line.trim());
+      // Limit total results to prevent memory overflow (--max-count only limits per-file)
+      const effectiveLimit = maxResults > 0 ? maxResults : 500;

      for (const line of lines) {
+        // Stop collecting if we've reached the limit
+        if (results.length >= effectiveLimit) {
+          resultLimitReached = true;
+          break;
+        }
+
        try {
          const item = JSON.parse(line);

@@ -817,6 +827,15 @@ async function executeRipgrepMode(params: Params): Promise<SearchResult> {
      const scoredResults = tokens.length > 1 ? scoreByTokenMatch(results, tokens) : results;

      if (code === 0 || code === 1 || (isWindowsDeviceError && scoredResults.length > 0)) {
+        // Build warning message for various conditions
+        const warnings: string[] = [];
+        if (resultLimitReached) {
+          warnings.push(`Result limit reached (${effectiveLimit}). Use a more specific query or increase limit.`);
+        }
+        if (isWindowsDeviceError) {
+          warnings.push('Some Windows device files were skipped');
+        }
+
        resolve({
          success: true,
          results: scoredResults,
@@ -827,7 +846,7 @@ async function executeRipgrepMode(params: Params): Promise<SearchResult> {
            query,
            tokens: tokens.length > 1 ? tokens : undefined,  // Include tokens in metadata for debugging
            tokenized: tokens.length > 1,
-            ...(isWindowsDeviceError && { warning: 'Some Windows device files were skipped' }),
+            ...(warnings.length > 0 && { warning: warnings.join('; ') }),
          },
        });
      } else if (isWindowsDeviceError && results.length === 0) {
@@ -923,6 +942,46 @@ async function executeCodexLensExactMode(params: Params): Promise<SearchResult>
    // Keep empty results
  }

+  // Fallback to fuzzy mode if exact returns no results
+  if (results.length === 0) {
+    const fuzzyArgs = ['search', query, '--limit', maxResults.toString(), '--mode', 'fuzzy', '--json'];
+    if (enrich) {
+      fuzzyArgs.push('--enrich');
+    }
+    const fuzzyResult = await executeCodexLens(fuzzyArgs, { cwd: path });
+
+    if (fuzzyResult.success) {
+      try {
+        const parsed = JSON.parse(stripAnsi(fuzzyResult.output || '{}'));
+        const data = parsed.result?.results || parsed.results || parsed;
+        results = (Array.isArray(data) ? data : []).map((item: any) => ({
+          file: item.path || item.file,
+          score: item.score || 0,
+          content: item.excerpt || item.content || '',
+          symbol: item.symbol || null,
+        }));
+      } catch {
+        // Keep empty results
+      }
+
+      if (results.length > 0) {
+        return {
+          success: true,
+          results,
+          metadata: {
+            mode: 'exact',
+            backend: 'codexlens',
+            count: results.length,
+            query,
+            warning: indexStatus.warning,
+            note: 'No exact matches found, showing fuzzy results',
+            fallback: 'fuzzy',
+          },
+        };
+      }
+    }
+  }
+
  return {
    success: true,
    results,
--- a/codex-lens/pyproject.toml
+++ b/codex-lens/pyproject.toml
@@ -31,6 +31,24 @@ semantic = [
    "hnswlib>=0.8.0",
 ]

+# GPU acceleration for semantic search (NVIDIA CUDA)
+# Install with: pip install codexlens[semantic-gpu]
+semantic-gpu = [
+    "numpy>=1.24",
+    "fastembed>=0.2",
+    "hnswlib>=0.8.0",
+    "onnxruntime-gpu>=1.15.0",  # CUDA support
+]
+
+# GPU acceleration for Windows (DirectML - supports NVIDIA/AMD/Intel)
+# Install with: pip install codexlens[semantic-directml]
+semantic-directml = [
+    "numpy>=1.24",
+    "fastembed>=0.2",
+    "hnswlib>=0.8.0",
+    "onnxruntime-directml>=1.15.0",  # DirectML support
+]
+
 # Encoding detection for non-UTF8 files
 encoding = [
    "chardet>=5.0",
--- a/codex-lens/src/codex_lens.egg-info/PKG-INFO
+++ b/codex-lens/src/codex_lens.egg-info/PKG-INFO
@@ -18,6 +18,17 @@ Requires-Dist: pathspec>=0.11
 Provides-Extra: semantic
 Requires-Dist: numpy>=1.24; extra == "semantic"
 Requires-Dist: fastembed>=0.2; extra == "semantic"
+Requires-Dist: hnswlib>=0.8.0; extra == "semantic"
+Provides-Extra: semantic-gpu
+Requires-Dist: numpy>=1.24; extra == "semantic-gpu"
+Requires-Dist: fastembed>=0.2; extra == "semantic-gpu"
+Requires-Dist: hnswlib>=0.8.0; extra == "semantic-gpu"
+Requires-Dist: onnxruntime-gpu>=1.15.0; extra == "semantic-gpu"
+Provides-Extra: semantic-directml
+Requires-Dist: numpy>=1.24; extra == "semantic-directml"
+Requires-Dist: fastembed>=0.2; extra == "semantic-directml"
+Requires-Dist: hnswlib>=0.8.0; extra == "semantic-directml"
+Requires-Dist: onnxruntime-directml>=1.15.0; extra == "semantic-directml"
 Provides-Extra: encoding
 Requires-Dist: chardet>=5.0; extra == "encoding"
 Provides-Extra: full
--- a/codex-lens/src/codex_lens.egg-info/SOURCES.txt
+++ b/codex-lens/src/codex_lens.egg-info/SOURCES.txt
@@ -11,8 +11,11 @@ src/codexlens/entities.py
 src/codexlens/errors.py
 src/codexlens/cli/__init__.py
 src/codexlens/cli/commands.py
+src/codexlens/cli/embedding_manager.py
 src/codexlens/cli/model_manager.py
 src/codexlens/cli/output.py
+src/codexlens/indexing/__init__.py
+src/codexlens/indexing/symbol_extractor.py
 src/codexlens/parsers/__init__.py
 src/codexlens/parsers/encoding.py
 src/codexlens/parsers/factory.py
@@ -20,15 +23,16 @@ src/codexlens/parsers/tokenizer.py
 src/codexlens/parsers/treesitter_parser.py
 src/codexlens/search/__init__.py
 src/codexlens/search/chain_search.py
+src/codexlens/search/enrichment.py
 src/codexlens/search/hybrid_search.py
 src/codexlens/search/query_parser.py
 src/codexlens/search/ranking.py
 src/codexlens/semantic/__init__.py
+src/codexlens/semantic/ann_index.py
 src/codexlens/semantic/chunker.py
 src/codexlens/semantic/code_extractor.py
 src/codexlens/semantic/embedder.py
-src/codexlens/semantic/graph_analyzer.py
-src/codexlens/semantic/llm_enhancer.py
+src/codexlens/semantic/gpu_support.py
 src/codexlens/semantic/vector_store.py
 src/codexlens/storage/__init__.py
 src/codexlens/storage/dir_index.py
@@ -42,38 +46,38 @@ src/codexlens/storage/sqlite_utils.py
 src/codexlens/storage/migrations/__init__.py
 src/codexlens/storage/migrations/migration_001_normalize_keywords.py
 src/codexlens/storage/migrations/migration_002_add_token_metadata.py
-src/codexlens/storage/migrations/migration_003_code_relationships.py
 src/codexlens/storage/migrations/migration_004_dual_fts.py
 src/codexlens/storage/migrations/migration_005_cleanup_unused_fields.py
-tests/test_chain_search_engine.py
+tests/test_ann_index.py
 tests/test_cli_hybrid_search.py
 tests/test_cli_output.py
 tests/test_code_extractor.py
 tests/test_config.py
 tests/test_dual_fts.py
 tests/test_encoding.py
+tests/test_enrichment.py
 tests/test_entities.py
 tests/test_errors.py
 tests/test_file_cache.py
-tests/test_graph_analyzer.py
-tests/test_graph_cli.py
-tests/test_graph_storage.py
 tests/test_hybrid_chunker.py
 tests/test_hybrid_search_e2e.py
 tests/test_incremental_indexing.py
-tests/test_llm_enhancer.py
 tests/test_parser_integration.py
 tests/test_parsers.py
 tests/test_performance_optimizations.py
+tests/test_pure_vector_search.py
 tests/test_query_parser.py
+tests/test_result_grouping.py
 tests/test_rrf_fusion.py
 tests/test_schema_cleanup_migration.py
+tests/test_search_comparison.py
 tests/test_search_comprehensive.py
 tests/test_search_full_coverage.py
 tests/test_search_performance.py
 tests/test_semantic.py
 tests/test_semantic_search.py
 tests/test_storage.py
+tests/test_symbol_extractor.py
 tests/test_token_chunking.py
 tests/test_token_storage.py
 tests/test_tokenizer.py
--- a/codex-lens/src/codex_lens.egg-info/requires.txt
+++ b/codex-lens/src/codex_lens.egg-info/requires.txt
@@ -16,3 +16,16 @@ tiktoken>=0.5.0
 [semantic]
 numpy>=1.24
 fastembed>=0.2
+hnswlib>=0.8.0
+
+[semantic-directml]
+numpy>=1.24
+fastembed>=0.2
+hnswlib>=0.8.0
+onnxruntime-directml>=1.15.0
+
+[semantic-gpu]
+numpy>=1.24
+fastembed>=0.2
+hnswlib>=0.8.0
+onnxruntime-gpu>=1.15.0
--- a/codex-lens/src/codexlens/cli/commands.py
+++ b/codex-lens/src/codexlens/cli/commands.py
@@ -35,8 +35,17 @@ from .output import (
 app = typer.Typer(help="CodexLens CLI — local code indexing and search.")


-def _configure_logging(verbose: bool) -> None:
-    level = logging.DEBUG if verbose else logging.INFO
+def _configure_logging(verbose: bool, json_mode: bool = False) -> None:
+    """Configure logging level.
+
+    In JSON mode, suppress INFO logs to keep stderr clean for error parsing.
+    Only WARNING and above are shown to avoid mixing logs with JSON output.
+    """
+    if json_mode and not verbose:
+        # In JSON mode, suppress INFO logs to keep stderr clean
+        level = logging.WARNING
+    else:
+        level = logging.DEBUG if verbose else logging.INFO
    logging.basicConfig(level=level, format="%(levelname)s %(message)s")


@@ -95,7 +104,7 @@ def init(
    If semantic search dependencies are installed, automatically generates embeddings
    after indexing completes. Use --no-embeddings to skip this step.
    """
-    _configure_logging(verbose)
+    _configure_logging(verbose, json_mode)
    config = Config()
    languages = _parse_languages(language)
    base_path = path.expanduser().resolve()
@@ -314,7 +323,7 @@ def search(
      # Force hybrid mode
      codexlens search "authentication" --mode hybrid
    """
-    _configure_logging(verbose)
+    _configure_logging(verbose, json_mode)
    search_path = path.expanduser().resolve()

    # Validate mode
@@ -487,7 +496,7 @@ def symbol(
    verbose: bool = typer.Option(False, "--verbose", "-v", help="Enable debug logging."),
 ) -> None:
    """Look up symbols by name and optional kind."""
-    _configure_logging(verbose)
+    _configure_logging(verbose, json_mode)
    search_path = path.expanduser().resolve()

    registry: RegistryStore | None = None
@@ -538,7 +547,7 @@ def inspect(
    verbose: bool = typer.Option(False, "--verbose", "-v", help="Enable debug logging."),
 ) -> None:
    """Analyze a single file and display symbols."""
-    _configure_logging(verbose)
+    _configure_logging(verbose, json_mode)
    config = Config()
    factory = ParserFactory(config)

@@ -588,7 +597,7 @@ def status(
    verbose: bool = typer.Option(False, "--verbose", "-v", help="Enable debug logging."),
 ) -> None:
    """Show index status and configuration."""
-    _configure_logging(verbose)
+    _configure_logging(verbose, json_mode)

    registry: RegistryStore | None = None
    try:
@@ -648,7 +657,7 @@ def status(
            # Embedding manager not available
            pass
        except Exception as e:
-            logger.debug(f"Failed to get embeddings status: {e}")
+            logging.debug(f"Failed to get embeddings status: {e}")

        stats = {
            "index_root": str(index_root),
@@ -737,7 +746,7 @@ def projects(
    - show <path>: Show details for a specific project
    - remove <path>: Remove a project from the registry
    """
-    _configure_logging(verbose)
+    _configure_logging(verbose, json_mode)

    registry: RegistryStore | None = None
    try:
@@ -892,7 +901,7 @@ def config(
    Config keys:
    - index_dir: Directory to store indexes (default: ~/.codexlens/indexes)
    """
-    _configure_logging(verbose)
+    _configure_logging(verbose, json_mode)

    config_file = Path.home() / ".codexlens" / "config.json"

@@ -1057,7 +1066,7 @@ def migrate(
    This is a safe operation that preserves all existing data.
    Progress is shown during migration.
    """
-    _configure_logging(verbose)
+    _configure_logging(verbose, json_mode)
    base_path = path.expanduser().resolve()

    registry: RegistryStore | None = None
@@ -1183,7 +1192,7 @@ def clean(
    With path, removes that project's indexes.
    With --all, removes all indexes (use with caution).
    """
-    _configure_logging(verbose)
+    _configure_logging(verbose, json_mode)

    try:
        mapper = PathMapper()
@@ -1329,7 +1338,7 @@ def semantic_list(
    Shows files that have LLM-generated summaries and keywords.
    Results are aggregated from all index databases in the project.
    """
-    _configure_logging(verbose)
+    _configure_logging(verbose, json_mode)
    base_path = path.expanduser().resolve()

    registry: Optional[RegistryStore] = None
@@ -1798,7 +1807,7 @@ def embeddings_generate(
        codexlens embeddings-generate ~/.codexlens/indexes/project/_index.db  # Specific index
        codexlens embeddings-generate ~/projects/my-app --model fast --force  # Regenerate with fast model
    """
-    _configure_logging(verbose)
+    _configure_logging(verbose, json_mode)

    from codexlens.cli.embedding_manager import generate_embeddings, generate_embeddings_recursive

--- a/codex-lens/src/codexlens/cli/embedding_manager.py
+++ b/codex-lens/src/codexlens/cli/embedding_manager.py
@@ -20,8 +20,8 @@ except ImportError:
 logger = logging.getLogger(__name__)

 # Embedding batch size - larger values improve throughput on modern hardware
-# Default 64 balances memory usage and GPU/CPU utilization
-EMBEDDING_BATCH_SIZE = 64  # Increased from 8 for better performance
+# Benchmark: 256 gives ~2.35x speedup over 64 with DirectML GPU acceleration
+EMBEDDING_BATCH_SIZE = 256  # Optimized from 64 based on batch size benchmarks


 def _generate_chunks_from_cursor(
@@ -275,10 +275,25 @@ def generate_embeddings(
    total_chunks_created = 0
    total_files_processed = 0
    FILE_BATCH_SIZE = 100  # Process 100 files at a time
-    # EMBEDDING_BATCH_SIZE is defined at module level (default: 64)
+    # EMBEDDING_BATCH_SIZE is defined at module level (default: 256)

    try:
        with VectorStore(index_path) as vector_store:
+            # Check model compatibility with existing embeddings
+            if not force:
+                is_compatible, warning = vector_store.check_model_compatibility(
+                    model_profile, embedder.model_name, embedder.embedding_dim
+                )
+                if not is_compatible:
+                    return {
+                        "success": False,
+                        "error": warning,
+                    }
+
+            # Set/update model configuration for this index
+            vector_store.set_model_config(
+                model_profile, embedder.model_name, embedder.embedding_dim
+            )
            # Use bulk insert mode for efficient batch ANN index building
            # This defers ANN updates until end_bulk_insert() is called
            with vector_store.bulk_insert():
--- a/codex-lens/src/codexlens/cli/model_manager.py
+++ b/codex-lens/src/codexlens/cli/model_manager.py
@@ -14,34 +14,63 @@ except ImportError:


 # Model profiles with metadata
+# Note: 768d is max recommended dimension for optimal performance/quality balance
+# 1024d models are available but not recommended due to higher resource usage
+# cache_name: The actual Hugging Face repo name used by fastembed for ONNX caching
 MODEL_PROFILES = {
    "fast": {
        "model_name": "BAAI/bge-small-en-v1.5",
+        "cache_name": "qdrant/bge-small-en-v1.5-onnx-q",  # fastembed uses ONNX version
        "dimensions": 384,
        "size_mb": 80,
        "description": "Fast, lightweight, English-optimized",
        "use_case": "Quick prototyping, resource-constrained environments",
+        "recommended": True,
+    },
+    "base": {
+        "model_name": "BAAI/bge-base-en-v1.5",
+        "cache_name": "qdrant/bge-base-en-v1.5-onnx-q",  # fastembed uses ONNX version
+        "dimensions": 768,
+        "size_mb": 220,
+        "description": "General purpose, good balance of speed and quality",
+        "use_case": "General text search, documentation",
+        "recommended": True,
    },
    "code": {
        "model_name": "jinaai/jina-embeddings-v2-base-code",
+        "cache_name": "jinaai/jina-embeddings-v2-base-code",  # Uses original name
        "dimensions": 768,
        "size_mb": 150,
        "description": "Code-optimized, best for programming languages",
        "use_case": "Open source projects, code semantic search",
+        "recommended": True,
+    },
+    "minilm": {
+        "model_name": "sentence-transformers/all-MiniLM-L6-v2",
+        "cache_name": "qdrant/all-MiniLM-L6-v2-onnx",  # fastembed uses ONNX version
+        "dimensions": 384,
+        "size_mb": 90,
+        "description": "Popular lightweight model, good quality",
+        "use_case": "General purpose, low resource environments",
+        "recommended": True,
    },
    "multilingual": {
        "model_name": "intfloat/multilingual-e5-large",
+        "cache_name": "qdrant/multilingual-e5-large-onnx",  # fastembed uses ONNX version
        "dimensions": 1024,
        "size_mb": 1000,
-        "description": "Multilingual + code support",
+        "description": "Multilingual + code support (high resource usage)",
        "use_case": "Enterprise multilingual projects",
+        "recommended": False,  # 1024d not recommended
    },
    "balanced": {
        "model_name": "mixedbread-ai/mxbai-embed-large-v1",
+        "cache_name": "mixedbread-ai/mxbai-embed-large-v1",  # Uses original name
        "dimensions": 1024,
        "size_mb": 600,
-        "description": "High accuracy, general purpose",
+        "description": "High accuracy, general purpose (high resource usage)",
        "use_case": "High-quality semantic search, balanced performance",
+        "recommended": False,  # 1024d not recommended
    },
 }

@@ -65,6 +94,23 @@ def get_cache_dir() -> Path:
    return cache_dir


+def _get_model_cache_path(cache_dir: Path, info: Dict) -> Path:
+    """Get the actual cache path for a model.
+
+    fastembed uses ONNX versions of models with different names than the original.
+    This function returns the correct path based on the cache_name field.
+
+    Args:
+        cache_dir: The fastembed cache directory
+        info: Model profile info dictionary
+
+    Returns:
+        Path to the model cache directory
+    """
+    cache_name = info.get("cache_name", info["model_name"])
+    return cache_dir / f"models--{cache_name.replace('/', '--')}"
+
+
 def list_models() -> Dict[str, any]:
    """List available model profiles and their installation status.

@@ -84,13 +130,13 @@ def list_models() -> Dict[str, any]:
    for profile, info in MODEL_PROFILES.items():
        model_name = info["model_name"]

-        # Check if model is cached
+        # Check if model is cached using the actual cache name
        installed = False
        cache_size_mb = 0

        if cache_exists:
-            # Check for model directory in cache
-            model_cache_path = cache_dir / f"models--{model_name.replace('/', '--')}"
+            # Check for model directory in cache using correct cache_name
+            model_cache_path = _get_model_cache_path(cache_dir, info)
            if model_cache_path.exists():
                installed = True
                # Calculate cache size
@@ -144,7 +190,8 @@ def download_model(profile: str, progress_callback: Optional[callable] = None) -
            "error": f"Unknown profile: {profile}. Available: {', '.join(MODEL_PROFILES.keys())}",
        }

-    model_name = MODEL_PROFILES[profile]["model_name"]
+    info = MODEL_PROFILES[profile]
+    model_name = info["model_name"]

    try:
        # Download model by instantiating TextEmbedding
@@ -157,9 +204,9 @@ def download_model(profile: str, progress_callback: Optional[callable] = None) -
        if progress_callback:
            progress_callback(f"Model {model_name} downloaded successfully")

-        # Get cache info
+        # Get cache info using correct cache_name
        cache_dir = get_cache_dir()
-        model_cache_path = cache_dir / f"models--{model_name.replace('/', '--')}"
+        model_cache_path = _get_model_cache_path(cache_dir, info)

        cache_size = 0
        if model_cache_path.exists():
@@ -202,9 +249,10 @@ def delete_model(profile: str) -> Dict[str, any]:
            "error": f"Unknown profile: {profile}. Available: {', '.join(MODEL_PROFILES.keys())}",
        }

-    model_name = MODEL_PROFILES[profile]["model_name"]
+    info = MODEL_PROFILES[profile]
+    model_name = info["model_name"]
    cache_dir = get_cache_dir()
-    model_cache_path = cache_dir / f"models--{model_name.replace('/', '--')}"
+    model_cache_path = _get_model_cache_path(cache_dir, info)

    if not model_cache_path.exists():
        return {
@@ -259,9 +307,9 @@ def get_model_info(profile: str) -> Dict[str, any]:
    info = MODEL_PROFILES[profile]
    model_name = info["model_name"]

-    # Check installation status
+    # Check installation status using correct cache_name
    cache_dir = get_cache_dir()
-    model_cache_path = cache_dir / f"models--{model_name.replace('/', '--')}"
+    model_cache_path = _get_model_cache_path(cache_dir, info)
    installed = model_cache_path.exists()

    cache_size_mb = None
--- a/codex-lens/src/codexlens/search/chain_search.py
+++ b/codex-lens/src/codexlens/search/chain_search.py
@@ -396,7 +396,20 @@ class ChainSearchEngine:
        all_results = []
        stats = SearchStats()

-        executor = self._get_executor(options.max_workers)
+        # Force single-threaded execution for vector/hybrid search to avoid GPU crashes
+        # DirectML/ONNX have threading issues when multiple threads access GPU resources
+        effective_workers = options.max_workers
+        if options.enable_vector or options.hybrid_mode:
+            effective_workers = 1
+            self.logger.debug("Using single-threaded mode for vector search (GPU safety)")
+            # Pre-load embedder to avoid initialization overhead per-search
+            try:
+                from codexlens.semantic.embedder import get_embedder
+                get_embedder(profile="code", use_gpu=True)
+            except Exception:
+                pass  # Ignore pre-load failures
+
+        executor = self._get_executor(effective_workers)
        # Submit all search tasks
        future_to_path = {
            executor.submit(
--- a/codex-lens/src/codexlens/search/hybrid_search.py
+++ b/codex-lens/src/codexlens/search/hybrid_search.py
@@ -274,19 +274,32 @@ class HybridSearchEngine:
                )
                return []

-            # Auto-detect embedding dimension and select appropriate profile
-            detected_dim = vector_store.dimension
-            if detected_dim is None:
-                self.logger.info("Vector store dimension unknown, using default profile")
-                profile = "code"  # Default fallback
-            elif detected_dim == 384:
-                profile = "fast"
-            elif detected_dim == 768:
-                profile = "code"
-            elif detected_dim == 1024:
-                profile = "multilingual"  # or balanced, both are 1024
+            # Get stored model configuration (preferred) or auto-detect from dimension
+            model_config = vector_store.get_model_config()
+            if model_config:
+                profile = model_config["model_profile"]
+                self.logger.debug(
+                    "Using stored model config: %s (%s, %dd)",
+                    profile, model_config["model_name"], model_config["embedding_dim"]
+                )
            else:
-                profile = "code"  # Default fallback
+                # Fallback: auto-detect from embedding dimension
+                detected_dim = vector_store.dimension
+                if detected_dim is None:
+                    self.logger.info("Vector store dimension unknown, using default profile")
+                    profile = "code"  # Default fallback
+                elif detected_dim == 384:
+                    profile = "fast"
+                elif detected_dim == 768:
+                    profile = "code"
+                elif detected_dim == 1024:
+                    profile = "multilingual"  # or balanced, both are 1024
+                else:
+                    profile = "code"  # Default fallback
+                self.logger.debug(
+                    "No stored model config, auto-detected profile '%s' from dimension %s",
+                    profile, detected_dim
+                )

            # Use cached embedder (singleton) for performance
            embedder = get_embedder(profile=profile)
--- a/codex-lens/src/codexlens/semantic/init.py
+++ b/codex-lens/src/codexlens/semantic/init.py
@@ -2,38 +2,75 @@

 Install with: pip install codexlens[semantic]
 Uses fastembed (ONNX-based, lightweight ~200MB)
+
+GPU Acceleration:
+- Automatic GPU detection and usage when available
+- Supports CUDA (NVIDIA), TensorRT, DirectML (Windows), ROCm (AMD), CoreML (Apple)
+- Install GPU support: pip install onnxruntime-gpu (NVIDIA) or onnxruntime-directml (Windows)
 """

 from __future__ import annotations

 SEMANTIC_AVAILABLE = False
 SEMANTIC_BACKEND: str | None = None
+GPU_AVAILABLE = False
 _import_error: str | None = None

-def _detect_backend() -> tuple[bool, str | None, str | None]:
-    """Detect if fastembed is available."""
+
+def _detect_backend() -> tuple[bool, str | None, bool, str | None]:
+    """Detect if fastembed and GPU are available."""
    try:
        import numpy as np
    except ImportError as e:
-        return False, None, f"numpy not available: {e}"
+        return False, None, False, f"numpy not available: {e}"

    try:
        from fastembed import TextEmbedding
-        return True, "fastembed", None
+    except ImportError:
+        return False, None, False, "fastembed not available. Install with: pip install codexlens[semantic]"
+
+    # Check GPU availability
+    gpu_available = False
+    try:
+        from .gpu_support import is_gpu_available
+        gpu_available = is_gpu_available()
    except ImportError:
        pass

-    return False, None, "fastembed not available. Install with: pip install codexlens[semantic]"
+    return True, "fastembed", gpu_available, None
+

 # Initialize on module load
-SEMANTIC_AVAILABLE, SEMANTIC_BACKEND, _import_error = _detect_backend()
+SEMANTIC_AVAILABLE, SEMANTIC_BACKEND, GPU_AVAILABLE, _import_error = _detect_backend()
+

 def check_semantic_available() -> tuple[bool, str | None]:
    """Check if semantic search dependencies are available."""
    return SEMANTIC_AVAILABLE, _import_error

+
+def check_gpu_available() -> tuple[bool, str]:
+    """Check if GPU acceleration is available.
+
+    Returns:
+        Tuple of (is_available, status_message)
+    """
+    if not SEMANTIC_AVAILABLE:
+        return False, "Semantic search not available"
+
+    try:
+        from .gpu_support import is_gpu_available, get_gpu_summary
+        if is_gpu_available():
+            return True, get_gpu_summary()
+        return False, "No GPU detected (using CPU)"
+    except ImportError:
+        return False, "GPU support module not available"
+
+
 __all__ = [
    "SEMANTIC_AVAILABLE",
    "SEMANTIC_BACKEND",
+    "GPU_AVAILABLE",
    "check_semantic_available",
+    "check_gpu_available",
 ]
--- a/codex-lens/src/codexlens/semantic/embedder.py
+++ b/codex-lens/src/codexlens/semantic/embedder.py
@@ -1,22 +1,29 @@
-"""Embedder for semantic code search using fastembed."""
+"""Embedder for semantic code search using fastembed.
+
+Supports GPU acceleration via ONNX execution providers (CUDA, TensorRT, DirectML, ROCm, CoreML).
+GPU acceleration is automatic when available, with transparent CPU fallback.
+"""

 from __future__ import annotations

 import gc
+import logging
 import threading
 from typing import Dict, Iterable, List, Optional

 import numpy as np

 from . import SEMANTIC_AVAILABLE
+from .gpu_support import get_optimal_providers, is_gpu_available, get_gpu_summary

+logger = logging.getLogger(__name__)

 # Global embedder cache for singleton pattern
 _embedder_cache: Dict[str, "Embedder"] = {}
 _cache_lock = threading.Lock()


-def get_embedder(profile: str = "code") -> "Embedder":
+def get_embedder(profile: str = "code", use_gpu: bool = True) -> "Embedder":
    """Get or create a cached Embedder instance (thread-safe singleton).

    This function provides significant performance improvement by reusing
@@ -25,27 +32,38 @@ def get_embedder(profile: str = "code") -> "Embedder":

    Args:
        profile: Model profile ("fast", "code", "multilingual", "balanced")
+        use_gpu: If True, use GPU acceleration when available (default: True)

    Returns:
        Cached Embedder instance for the given profile
    """
    global _embedder_cache

+    # Cache key includes GPU preference to support mixed configurations
+    cache_key = f"{profile}:{'gpu' if use_gpu else 'cpu'}"
+
    # Fast path: check cache without lock
-    if profile in _embedder_cache:
-        return _embedder_cache[profile]
+    if cache_key in _embedder_cache:
+        return _embedder_cache[cache_key]

    # Slow path: acquire lock for initialization
    with _cache_lock:
        # Double-check after acquiring lock
-        if profile in _embedder_cache:
-            return _embedder_cache[profile]
+        if cache_key in _embedder_cache:
+            return _embedder_cache[cache_key]

        # Create new embedder and cache it
-        embedder = Embedder(profile=profile)
+        embedder = Embedder(profile=profile, use_gpu=use_gpu)
        # Pre-load model to ensure it's ready
        embedder._load_model()
-        _embedder_cache[profile] = embedder
+        _embedder_cache[cache_key] = embedder
+
+        # Log GPU status on first embedder creation
+        if use_gpu and is_gpu_available():
+            logger.info(f"Embedder initialized with GPU: {get_gpu_summary()}")
+        elif use_gpu:
+            logger.debug("GPU not available, using CPU for embeddings")
+
        return embedder


@@ -96,13 +114,21 @@ class Embedder:
    DEFAULT_MODEL = "BAAI/bge-small-en-v1.5"
    DEFAULT_PROFILE = "fast"

-    def __init__(self, model_name: str | None = None, profile: str | None = None) -> None:
+    def __init__(
+        self,
+        model_name: str | None = None,
+        profile: str | None = None,
+        use_gpu: bool = True,
+        providers: List[str] | None = None,
+    ) -> None:
        """Initialize embedder with model or profile.

        Args:
            model_name: Explicit model name (e.g., "jinaai/jina-embeddings-v2-base-code")
            profile: Model profile shortcut ("fast", "code", "multilingual", "balanced")
                    If both provided, model_name takes precedence.
+            use_gpu: If True, use GPU acceleration when available (default: True)
+            providers: Explicit ONNX providers list (overrides use_gpu if provided)
        """
        if not SEMANTIC_AVAILABLE:
            raise ImportError(
@@ -118,6 +144,13 @@ class Embedder:
        else:
            self.model_name = self.DEFAULT_MODEL

+        # Configure ONNX execution providers
+        if providers is not None:
+            self._providers = providers
+        else:
+            self._providers = get_optimal_providers(use_gpu=use_gpu)
+
+        self._use_gpu = use_gpu
        self._model = None

    @property
@@ -125,13 +158,39 @@ class Embedder:
        """Get embedding dimension for current model."""
        return self.MODEL_DIMS.get(self.model_name, 768)  # Default to 768 if unknown

+    @property
+    def providers(self) -> List[str]:
+        """Get configured ONNX execution providers."""
+        return self._providers
+
+    @property
+    def is_gpu_enabled(self) -> bool:
+        """Check if GPU acceleration is enabled for this embedder."""
+        gpu_providers = {"CUDAExecutionProvider", "TensorrtExecutionProvider",
+                        "DmlExecutionProvider", "ROCMExecutionProvider", "CoreMLExecutionProvider"}
+        return any(p in gpu_providers for p in self._providers)
+
    def _load_model(self) -> None:
-        """Lazy load the embedding model."""
+        """Lazy load the embedding model with configured providers."""
        if self._model is not None:
            return

        from fastembed import TextEmbedding
-        self._model = TextEmbedding(model_name=self.model_name)
+
+        # fastembed supports 'providers' parameter for ONNX execution providers
+        try:
+            self._model = TextEmbedding(
+                model_name=self.model_name,
+                providers=self._providers,
+            )
+            logger.debug(f"Model loaded with providers: {self._providers}")
+        except TypeError:
+            # Fallback for older fastembed versions without providers parameter
+            logger.warning(
+                "fastembed version doesn't support 'providers' parameter. "
+                "Upgrade fastembed for GPU acceleration: pip install --upgrade fastembed"
+            )
+            self._model = TextEmbedding(model_name=self.model_name)

    def embed(self, texts: str | Iterable[str]) -> List[List[float]]:
        """Generate embeddings for one or more texts.
--- a/codex-lens/src/codexlens/semantic/gpu_support.py
+++ b/codex-lens/src/codexlens/semantic/gpu_support.py
@@ -0,0 +1,192 @@
+"""GPU acceleration support for semantic embeddings.
+
+This module provides GPU detection, initialization, and fallback handling
+for ONNX-based embedding generation.
+"""
+
+from __future__ import annotations
+
+import logging
+from dataclasses import dataclass
+from typing import List, Optional
+
+logger = logging.getLogger(__name__)
+
+
+@dataclass
+class GPUInfo:
+    """GPU availability and configuration info."""
+
+    gpu_available: bool = False
+    cuda_available: bool = False
+    gpu_count: int = 0
+    gpu_name: Optional[str] = None
+    onnx_providers: List[str] = None
+
+    def __post_init__(self):
+        if self.onnx_providers is None:
+            self.onnx_providers = ["CPUExecutionProvider"]
+
+
+_gpu_info_cache: Optional[GPUInfo] = None
+
+
+def detect_gpu(force_refresh: bool = False) -> GPUInfo:
+    """Detect available GPU resources for embedding acceleration.
+
+    Args:
+        force_refresh: If True, re-detect GPU even if cached.
+
+    Returns:
+        GPUInfo with detection results.
+    """
+    global _gpu_info_cache
+
+    if _gpu_info_cache is not None and not force_refresh:
+        return _gpu_info_cache
+
+    info = GPUInfo()
+
+    # Check PyTorch CUDA availability (most reliable detection)
+    try:
+        import torch
+        if torch.cuda.is_available():
+            info.cuda_available = True
+            info.gpu_available = True
+            info.gpu_count = torch.cuda.device_count()
+            if info.gpu_count > 0:
+                info.gpu_name = torch.cuda.get_device_name(0)
+            logger.debug(f"PyTorch CUDA detected: {info.gpu_count} GPU(s)")
+    except ImportError:
+        logger.debug("PyTorch not available for GPU detection")
+
+    # Check ONNX Runtime providers with validation
+    try:
+        import onnxruntime as ort
+        available_providers = ort.get_available_providers()
+
+        # Build provider list with priority order
+        providers = []
+
+        # Test each provider to ensure it actually works
+        def test_provider(provider_name: str) -> bool:
+            """Test if a provider actually works by creating a dummy session."""
+            try:
+                # Create a minimal ONNX model to test provider
+                import numpy as np
+                # Simple test: just check if provider can be instantiated
+                sess_options = ort.SessionOptions()
+                sess_options.log_severity_level = 4  # Suppress warnings
+                return True
+            except Exception:
+                return False
+
+        # CUDA provider (NVIDIA GPU) - check if CUDA runtime is available
+        if "CUDAExecutionProvider" in available_providers:
+            # Verify CUDA is actually usable by checking for cuBLAS
+            cuda_works = False
+            try:
+                import ctypes
+                # Try to load cuBLAS to verify CUDA installation
+                try:
+                    ctypes.CDLL("cublas64_12.dll")
+                    cuda_works = True
+                except OSError:
+                    try:
+                        ctypes.CDLL("cublas64_11.dll")
+                        cuda_works = True
+                    except OSError:
+                        pass
+            except Exception:
+                pass
+
+            if cuda_works:
+                providers.append("CUDAExecutionProvider")
+                info.gpu_available = True
+                logger.debug("ONNX CUDAExecutionProvider available and working")
+            else:
+                logger.debug("ONNX CUDAExecutionProvider listed but CUDA runtime not found")
+
+        # TensorRT provider (optimized NVIDIA inference)
+        if "TensorrtExecutionProvider" in available_providers:
+            # TensorRT requires additional libraries, skip for now
+            logger.debug("ONNX TensorrtExecutionProvider available (requires TensorRT SDK)")
+
+        # DirectML provider (Windows GPU - AMD/Intel/NVIDIA)
+        if "DmlExecutionProvider" in available_providers:
+            providers.append("DmlExecutionProvider")
+            info.gpu_available = True
+            logger.debug("ONNX DmlExecutionProvider available (DirectML)")
+
+        # ROCm provider (AMD GPU on Linux)
+        if "ROCMExecutionProvider" in available_providers:
+            providers.append("ROCMExecutionProvider")
+            info.gpu_available = True
+            logger.debug("ONNX ROCMExecutionProvider available (AMD)")
+
+        # CoreML provider (Apple Silicon)
+        if "CoreMLExecutionProvider" in available_providers:
+            providers.append("CoreMLExecutionProvider")
+            info.gpu_available = True
+            logger.debug("ONNX CoreMLExecutionProvider available (Apple)")
+
+        # Always include CPU as fallback
+        providers.append("CPUExecutionProvider")
+
+        info.onnx_providers = providers
+
+    except ImportError:
+        logger.debug("ONNX Runtime not available")
+        info.onnx_providers = ["CPUExecutionProvider"]
+
+    _gpu_info_cache = info
+    return info
+
+
+def get_optimal_providers(use_gpu: bool = True) -> List[str]:
+    """Get optimal ONNX execution providers based on availability.
+
+    Args:
+        use_gpu: If True, include GPU providers when available.
+                 If False, force CPU-only execution.
+
+    Returns:
+        List of provider names in priority order.
+    """
+    if not use_gpu:
+        return ["CPUExecutionProvider"]
+
+    gpu_info = detect_gpu()
+    return gpu_info.onnx_providers
+
+
+def is_gpu_available() -> bool:
+    """Check if any GPU acceleration is available."""
+    return detect_gpu().gpu_available
+
+
+def get_gpu_summary() -> str:
+    """Get human-readable GPU status summary."""
+    info = detect_gpu()
+
+    if not info.gpu_available:
+        return "GPU: Not available (using CPU)"
+
+    parts = []
+    if info.gpu_name:
+        parts.append(f"GPU: {info.gpu_name}")
+    if info.gpu_count > 1:
+        parts.append(f"({info.gpu_count} devices)")
+
+    # Show active providers (excluding CPU fallback)
+    gpu_providers = [p for p in info.onnx_providers if p != "CPUExecutionProvider"]
+    if gpu_providers:
+        parts.append(f"Providers: {', '.join(gpu_providers)}")
+
+    return " | ".join(parts) if parts else "GPU: Available"
+
+
+def clear_gpu_cache() -> None:
+    """Clear cached GPU detection info."""
+    global _gpu_info_cache
+    _gpu_info_cache = None
--- a/codex-lens/src/codexlens/semantic/vector_store.py
+++ b/codex-lens/src/codexlens/semantic/vector_store.py
@@ -116,6 +116,17 @@ class VectorStore:
                CREATE INDEX IF NOT EXISTS idx_chunks_file
                ON semantic_chunks(file_path)
            """)
+            # Model configuration table - tracks which model generated the embeddings
+            conn.execute("""
+                CREATE TABLE IF NOT EXISTS embeddings_config (
+                    id INTEGER PRIMARY KEY CHECK (id = 1),
+                    model_profile TEXT NOT NULL,
+                    model_name TEXT NOT NULL,
+                    embedding_dim INTEGER NOT NULL,
+                    created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
+                    updated_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP
+                )
+            """)
            conn.commit()

    def _init_ann_index(self) -> None:
@@ -932,6 +943,92 @@ class VectorStore:
            return self._ann_index.count()
        return 0

+    def get_model_config(self) -> Optional[Dict[str, Any]]:
+        """Get the model configuration used for embeddings in this store.
+
+        Returns:
+            Dictionary with model_profile, model_name, embedding_dim, or None if not set.
+        """
+        with sqlite3.connect(self.db_path) as conn:
+            row = conn.execute(
+                "SELECT model_profile, model_name, embedding_dim, created_at, updated_at "
+                "FROM embeddings_config WHERE id = 1"
+            ).fetchone()
+            if row:
+                return {
+                    "model_profile": row[0],
+                    "model_name": row[1],
+                    "embedding_dim": row[2],
+                    "created_at": row[3],
+                    "updated_at": row[4],
+                }
+        return None
+
+    def set_model_config(
+        self, model_profile: str, model_name: str, embedding_dim: int
+    ) -> None:
+        """Set the model configuration for embeddings in this store.
+
+        This should be called when generating new embeddings. If a different
+        model was previously used, this will update the configuration.
+
+        Args:
+            model_profile: Model profile name (fast, code, minilm, etc.)
+            model_name: Full model name (e.g., jinaai/jina-embeddings-v2-base-code)
+            embedding_dim: Embedding dimension (e.g., 768)
+        """
+        with sqlite3.connect(self.db_path) as conn:
+            conn.execute(
+                """
+                INSERT INTO embeddings_config (id, model_profile, model_name, embedding_dim)
+                VALUES (1, ?, ?, ?)
+                ON CONFLICT(id) DO UPDATE SET
+                    model_profile = excluded.model_profile,
+                    model_name = excluded.model_name,
+                    embedding_dim = excluded.embedding_dim,
+                    updated_at = CURRENT_TIMESTAMP
+                """,
+                (model_profile, model_name, embedding_dim)
+            )
+            conn.commit()
+
+    def check_model_compatibility(
+        self, model_profile: str, model_name: str, embedding_dim: int
+    ) -> Tuple[bool, Optional[str]]:
+        """Check if the given model is compatible with existing embeddings.
+
+        Args:
+            model_profile: Model profile to check
+            model_name: Model name to check
+            embedding_dim: Embedding dimension to check
+
+        Returns:
+            Tuple of (is_compatible, warning_message).
+            is_compatible is True if no existing config or configs match.
+            warning_message is a user-friendly message if incompatible.
+        """
+        existing = self.get_model_config()
+        if existing is None:
+            return True, None
+
+        # Check dimension first (most critical)
+        if existing["embedding_dim"] != embedding_dim:
+            return False, (
+                f"Dimension mismatch: existing embeddings use {existing['embedding_dim']}d "
+                f"({existing['model_profile']}), but requested model uses {embedding_dim}d "
+                f"({model_profile}). Use --force to regenerate all embeddings."
+            )
+
+        # Check model (different models with same dimension may have different semantic spaces)
+        if existing["model_profile"] != model_profile:
+            return False, (
+                f"Model mismatch: existing embeddings use '{existing['model_profile']}' "
+                f"({existing['model_name']}), but requested '{model_profile}' "
+                f"({model_name}). Use --force to regenerate all embeddings."
+            )
+
+        return True, None
+
    def close(self) -> None:
        """Close the vector store and release resources.

--- a/codex-lens/src/codexlens/storage/dir_index.py
+++ b/codex-lens/src/codexlens/storage/dir_index.py
@@ -1651,16 +1651,17 @@ class DirIndexStore:
            from codexlens.storage.sqlite_utils import check_trigram_support

            has_trigram = check_trigram_support(conn)
-            fuzzy_tokenizer = "trigram" if has_trigram else "unicode61 tokenchars '_-'"
+            fuzzy_tokenizer = "trigram" if has_trigram else "unicode61 tokenchars '_-.'"

            # Exact FTS table with unicode61 tokenizer
+            # Note: tokenchars includes '.' to properly tokenize qualified names like PortRole.FLOW
            conn.execute(
                """
                CREATE VIRTUAL TABLE IF NOT EXISTS files_fts_exact USING fts5(
                    name, full_path UNINDEXED, content,
                    content='files',
                    content_rowid='id',
-                    tokenize="unicode61 tokenchars '_-'"
+                    tokenize="unicode61 tokenchars '_-.'"
                )
                """
            )
--- a/codex-lens/src/codexlens/storage/migrations/migration_004_dual_fts.py
+++ b/codex-lens/src/codexlens/storage/migrations/migration_004_dual_fts.py
@@ -45,7 +45,7 @@ def upgrade(db_conn: Connection):
                f"Trigram tokenizer not available (requires SQLite >= 3.34), "
                f"using extended unicode61 tokenizer for fuzzy matching"
            )
-            fuzzy_tokenizer = "unicode61 tokenchars '_-'"
+            fuzzy_tokenizer = "unicode61 tokenchars '_-.'"

        # Start transaction
        cursor.execute("BEGIN TRANSACTION")
@@ -122,7 +122,8 @@ def upgrade(db_conn: Connection):
        # Drop old FTS table
        cursor.execute("DROP TABLE IF EXISTS files_fts")

-        # Create exact FTS table (unicode61 with underscores/hyphens as token chars)
+        # Create exact FTS table (unicode61 with underscores/hyphens/dots as token chars)
+        # Note: tokenchars includes '.' to properly tokenize qualified names like PortRole.FLOW
        log.info("Creating files_fts_exact table with unicode61 tokenizer...")
        cursor.execute(
            """
@@ -130,7 +131,7 @@ def upgrade(db_conn: Connection):
                name, full_path UNINDEXED, content,
                content='files',
                content_rowid='id',
-                tokenize="unicode61 tokenchars '_-'"
+                tokenize="unicode61 tokenchars '_-.'"
            )
            """
        )
--- a/package-lock.json
+++ b/package-lock.json
--- a/package.json
+++ b/package.json
@@ -1,11 +1,12 @@
 {
  "name": "claude-code-workflow",
-  "version": "6.2.0",
+  "version": "6.2.8",
  "description": "JSON-driven multi-agent development framework with intelligent CLI orchestration (Gemini/Qwen/Codex), context-first architecture, and automated workflow execution",
  "type": "module",
  "main": "ccw/src/index.js",
  "bin": {
-    "ccw": "./ccw/bin/ccw.js"
+    "ccw": "./ccw/bin/ccw.js",
+    "ccw-mcp": "./ccw/bin/ccw-mcp.js"
  },
  "scripts": {
    "start": "node ccw/bin/ccw.js",
@@ -28,6 +29,8 @@
    "node": ">=16.0.0"
  },
  "dependencies": {
+    "@modelcontextprotocol/sdk": "^1.0.4",
+    "better-sqlite3": "^11.7.0",
    "boxen": "^7.1.0",
    "chalk": "^5.3.0",
    "commander": "^11.0.0",
@@ -36,12 +39,13 @@
    "gradient-string": "^2.0.2",
    "inquirer": "^9.2.0",
    "open": "^9.1.0",
-    "ora": "^7.0.0"
+    "ora": "^7.0.0",
+    "zod": "^4.1.13"
  },
  "files": [
    "ccw/bin/",
+    "ccw/dist/",
    "ccw/src/",
-    "ccw/package.json",
    ".claude/agents/",
    ".claude/commands/",
    ".claude/output-styles/",
Author	SHA1	Message	Date
catlog22	86cefa7bda	bump version to 6.2.8 in package.json and package-lock.json	2025-12-23 09:49:55 +08:00
catlog22	fdac697f6e	refactor: 移除 ccw/package.json 文件并更新路径引用	2025-12-23 09:47:07 +08:00
catlog22	8203d690cb	fix: CodexLens model detection, hybrid search stability, and JSON logging - Fix model installation detection using fastembed ONNX cache names - Add embeddings_config table for model metadata tracking - Fix hybrid search segfault by using single-threaded GPU mode - Suppress INFO logs in JSON mode to prevent error display - Add model dropdown filtering to show only installed models 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>	2025-12-22 21:49:10 +08:00
catlog22	cf58dc0dd3	bump version to 6.2.6 in package.json	2025-12-22 20:17:38 +08:00
catlog22	6a69af3bf1	feat: 更新嵌入批处理大小至 256，以优化性能并提高 GPU 加速效率	2025-12-22 17:55:05 +08:00
catlog22	acdfbb4644	feat: Enhance CodexLens with GPU support and semantic status improvements - Added accelerator and providers fields to SemanticStatus interface. - Updated checkSemanticStatus function to retrieve ONNX providers and accelerator type. - Introduced detectGpuSupport function to identify available GPU modes (CUDA, DirectML). - Modified installSemantic function to support GPU acceleration modes and clean up ONNX Runtime installations. - Updated package requirements in PKG-INFO for semantic-gpu and semantic-directml extras. - Added new source files for GPU support and enrichment functionalities. - Updated tests to cover new features and ensure comprehensive testing.	2025-12-22 17:42:26 +08:00
catlog22	72f24bf535	feat: 更新版本号至 6.2.4，添加 GPU 加速支持和相关依赖	2025-12-22 14:15:36 +08:00
catlog22	ba23244876	feat: 更新版本号至 6.2.2，并添加 dist 目录到文件列表	2025-12-22 12:06:59 +08:00
catlog22	624f9f18b4	feat: 更新项目名称和版本号，提升版本管理清晰度	2025-12-22 10:29:32 +08:00
catlog22	17002345c9	feat: 更新钩子模板检查逻辑，支持基于唯一模式的命令匹配；在搜索元数据中添加回退模式字段	2025-12-22 10:25:53 +08:00
catlog22	f3f2051c45	feat: 优化项目和全局配置的获取逻辑，添加Codex配置支持	2025-12-22 10:16:58 +08:00
catlog22	e60d793c8c	fix: 修复 SmartSearch 的 ripgrep limit 和 FTS 分词器问题 - Ripgrep 模式: 添加总结果数量限制，防止返回超过 2MB 数据 - --max-count 只限制每个文件的匹配数，现在在收集结果时应用 limit - 达到限制时在 metadata 中添加 warning 提示 - FTS 分词器: 将点号(.)添加到 tokenchars，修复 PortRole.FLOW 等带点号标识符的精确搜索 - 更新 dir_index.py 和 migration_004_dual_fts.py 中的 tokenize 配置 - 需要重建索引才能生效 - Exact 模式: 添加 fuzzy 回退，当精确搜索无结果时自动尝试模糊搜索 - 回退时在 metadata 中标注 fallback: 'fuzzy' 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>	2025-12-22 09:50:29 +08:00