mirror of
https://github.com/catlog22/Claude-Code-Workflow.git
synced 2026-03-01 11:13:25 +08:00
feat: add CLI settings export/import functionality
- Implemented exportSettings and importSettings APIs for CLI settings. - Added hooks useExportSettings and useImportSettings for managing export/import operations in the frontend. - Updated SettingsPage to include buttons for exporting and importing CLI settings. - Enhanced backend to handle export and import requests, including validation and conflict resolution. - Introduced new data structures for exported settings and import options. - Updated localization files to support new export/import features. - Refactored CLI tool configurations to remove hardcoded model defaults, allowing dynamic model retrieval.
This commit is contained in:
catlog22
@@ -1,20 +1,20 @@
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---
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name: planex-executor
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description: |
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Execution agent for PlanEx pipeline. Loads solutions, routes to
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configurable backends (agent/codex/gemini CLI), runs tests, commits.
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Processes all tasks within a single wave assignment.
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Execution agent for PlanEx pipeline. Loads solutions from artifact files
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(with CLI fallback), routes to configurable backends (agent/codex/gemini CLI),
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runs tests, commits. Processes all tasks within a single assignment.
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color: green
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skill: team-planex
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---
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# PlanEx Executor
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加载 solution → 根据 execution_method 路由到对应后端（Agent/Codex/Gemini）→ 测试验证 → 提交。每次被 spawn 时处理一个 wave 的所有 exec tasks，按依赖顺序执行。
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从中间产物文件加载 solution（兼容 CLI fallback）→ 根据 execution_method 路由到对应后端（Agent/Codex/Gemini）→ 测试验证 → 提交。每次被 spawn 时处理分配的 exec tasks，按依赖顺序执行。
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## Core Capabilities
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1. **Solution Loading**: 从 issue system 加载 bound solution plan
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1. **Solution Loading**: 从中间产物文件加载 bound solution plan（兼容 CLI fallback）
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2. **Multi-Backend Routing**: 根据 execution_method 选择 agent/codex/gemini 后端
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3. **Test Verification**: 实现后运行测试验证
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4. **Commit Management**: 每个 solution 完成后 git commit
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@@ -209,9 +209,22 @@ for (const task of sorted) {
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const issueId = task.issue_id
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const taskStartTime = Date.now()
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// --- Load solution ---
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const solJson = shell(`ccw issue solution ${issueId} --json`)
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const solution = JSON.parse(solJson)
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// --- Load solution (dual-mode: artifact file first, CLI fallback) ---
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let solution
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const solutionFile = task.solution_file
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if (solutionFile) {
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try {
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const solutionData = JSON.parse(read_file(solutionFile))
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solution = solutionData.bound ? solutionData : { bound: solutionData }
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} catch {
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// Fallback to CLI
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const solJson = shell(`ccw issue solution ${issueId} --json`)
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solution = JSON.parse(solJson)
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}
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} else {
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const solJson = shell(`ccw issue solution ${issueId} --json`)
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solution = JSON.parse(solJson)
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}
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if (!solution.bound) {
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recordTaskStart(issueId, task.title, 'N/A', '')
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@@ -2,22 +2,23 @@
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name: planex-planner
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description: |
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Planning lead for PlanEx pipeline. Decomposes requirements into issues,
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generates solutions via issue-plan-agent, forms execution queues via
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issue-queue-agent, outputs wave-structured data for orchestrator dispatch.
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generates solutions via issue-plan-agent, performs inline conflict check,
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writes solution artifacts. Per-issue output for orchestrator dispatch.
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color: blue
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skill: team-planex
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---
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# PlanEx Planner
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需求拆解 → issue 创建 → 方案设计 → 队列编排 → 输出 wave 数据。内部 spawn issue-plan-agent 和 issue-queue-agent 子代理，通过 Wave Pipeline 持续推进。每完成一个 wave 立即输出 WAVE_READY，等待 orchestrator send_input 继续下一 wave。
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需求拆解 → issue 创建 → 方案设计 → inline 冲突检查 → 写中间产物 → 逐 issue 输出。内部 spawn issue-plan-agent 子代理，每完成一个 issue 的 solution 立即输出 ISSUE_READY，等待 orchestrator send_input 继续下一 issue。
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## Core Capabilities
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1. **Requirement Decomposition**: 将需求文本/plan 文件拆解为独立 issues
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2. **Solution Planning**: 通过 issue-plan-agent 为每个 issue 生成 solution
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3. **Queue Formation**: 通过 issue-queue-agent 排序 solutions 并检测冲突
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4. **Wave Output**: 每个 wave 完成后输出结构化 WAVE_READY 数据
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3. **Inline Conflict Check**: 基于 files_touched 重叠检测 + 显式依赖排序
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4. **Solution Artifacts**: 将 solution 写入中间产物文件供 executor 加载
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5. **Per-Issue Output**: 每个 issue 完成后立即输出 ISSUE_READY 数据
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## Execution Process
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@@ -32,7 +33,8 @@ skill: team-planex
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- **Goal**: What to achieve
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- **Input**: Issue IDs / text / plan file
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- **Execution Config**: execution_method + code_review settings
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- **Deliverables**: WAVE_READY + ALL_PLANNED structured output
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- **Session Dir**: Path for writing solution artifacts
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- **Deliverables**: ISSUE_READY + ALL_PLANNED structured output
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### Step 2: Input Parsing & Issue Creation
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@@ -40,6 +42,8 @@ Parse the input from TASK ASSIGNMENT and create issues as needed.
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```javascript
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const input = taskAssignment.input
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const sessionDir = taskAssignment.session_dir
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const executionConfig = taskAssignment.execution_config
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// 1) 已有 Issue IDs
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const issueIds = input.match(/ISS-\d{8}-\d{6}/g) || []
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@@ -47,7 +51,6 @@ const issueIds = input.match(/ISS-\d{8}-\d{6}/g) || []
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// 2) 文本输入 → 创建 issue
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const textMatch = input.match(/text:\s*(.+)/)
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if (textMatch && issueIds.length === 0) {
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// Use ccw issue create CLI to create issue from text
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const result = shell(`ccw issue create --data '{"title":"${textMatch[1]}","description":"${textMatch[1]}"}' --json`)
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const newIssue = JSON.parse(result)
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issueIds.push(newIssue.id)
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@@ -58,11 +61,10 @@ const planMatch = input.match(/plan_file:\s*(\S+)/)
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if (planMatch && issueIds.length === 0) {
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const planContent = read_file(planMatch[1])
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// Check if execution-plan.json from req-plan-with-file
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try {
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const content = JSON.parse(planContent)
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if (content.waves && content.issue_ids) {
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// execution-plan format: use wave structure directly
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// execution-plan format: use issue_ids directly
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executionPlan = content
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issueIds = content.issue_ids
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}
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@@ -77,30 +79,20 @@ if (planMatch && issueIds.length === 0) {
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}
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```
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### Step 3: Wave-Based Solution Planning
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### Step 3: Per-Issue Solution Planning & Artifact Writing
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Group issues into waves, spawn sub-agents for each wave.
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Process each issue individually: plan → write artifact → conflict check → output ISSUE_READY.
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```javascript
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const projectRoot = shell('cd . && pwd').trim()
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const dispatchedSolutions = []
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// Group into waves (max 5 per wave, or use execution-plan wave structure)
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const WAVE_SIZE = 5
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let waves
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if (executionPlan) {
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waves = executionPlan.waves.map(w => w.issue_ids)
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} else {
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waves = []
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for (let i = 0; i < issueIds.length; i += WAVE_SIZE) {
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waves.push(issueIds.slice(i, i + WAVE_SIZE))
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}
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}
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shell(`mkdir -p "${sessionDir}/artifacts/solutions"`)
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let waveNum = 0
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for (const waveIssues of waves) {
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waveNum++
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for (let i = 0; i < issueIds.length; i++) {
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const issueId = issueIds[i]
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// --- Step 3a: Spawn issue-plan-agent for solutions ---
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// --- Step 3a: Spawn issue-plan-agent for single issue ---
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const planAgent = spawn_agent({
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message: `
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## TASK ASSIGNMENT
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@@ -112,116 +104,121 @@ for (const waveIssues of waves) {
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---
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Goal: Generate solutions for Wave ${waveNum} issues
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Goal: Generate solution for issue ${issueId}
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issue_ids: ${JSON.stringify(waveIssues)}
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issue_ids: ["${issueId}"]
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project_root: "${projectRoot}"
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## Requirements
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- Generate solutions for each issue
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- Auto-bind single solutions
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- Generate solution for this issue
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- Auto-bind single solution
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- For multiple solutions, select the most pragmatic one
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## Deliverables
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Structured output with solution bindings per issue.
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Structured output with solution binding.
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`
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})
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const planResult = wait({ ids: [planAgent], timeout_ms: 600000 })
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if (planResult.timed_out) {
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send_input({ id: planAgent, message: "Please finalize solutions and output current results." })
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send_input({ id: planAgent, message: "Please finalize solution and output results." })
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wait({ ids: [planAgent], timeout_ms: 120000 })
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}
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close_agent({ id: planAgent })
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// --- Step 3b: Spawn issue-queue-agent for ordering ---
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const queueAgent = spawn_agent({
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message: `
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## TASK ASSIGNMENT
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// --- Step 3b: Load solution + write artifact file ---
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const solJson = shell(`ccw issue solution ${issueId} --json`)
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const solution = JSON.parse(solJson)
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### MANDATORY FIRST STEPS (Agent Execute)
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1. **Read role definition**: ~/.codex/agents/issue-queue-agent.md (MUST read first)
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2. Read: .workflow/project-tech.json
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const solutionFile = `${sessionDir}/artifacts/solutions/${issueId}.json`
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write_file(solutionFile, JSON.stringify({
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issue_id: issueId,
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...solution,
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execution_config: {
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execution_method: executionConfig.executionMethod,
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code_review: executionConfig.codeReviewTool
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},
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timestamp: new Date().toISOString()
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}, null, 2))
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---
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// --- Step 3c: Inline conflict check ---
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const blockedBy = inlineConflictCheck(issueId, solution, dispatchedSolutions)
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Goal: Form execution queue for Wave ${waveNum}
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// --- Step 3d: Output ISSUE_READY for orchestrator ---
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dispatchedSolutions.push({ issueId, solution, solutionFile })
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issue_ids: ${JSON.stringify(waveIssues)}
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project_root: "${projectRoot}"
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## Requirements
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- Order solutions by dependency (DAG)
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- Detect conflicts between solutions
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- Output execution queue to .workflow/issues/queue/execution-queue.json
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## Deliverables
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Structured execution queue with dependency ordering.
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`
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})
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const queueResult = wait({ ids: [queueAgent], timeout_ms: 300000 })
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if (queueResult.timed_out) {
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send_input({ id: queueAgent, message: "Please finalize queue and output results." })
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wait({ ids: [queueAgent], timeout_ms: 60000 })
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}
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close_agent({ id: queueAgent })
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// --- Step 3c: Read queue and output WAVE_READY ---
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const queuePath = `.workflow/issues/queue/execution-queue.json`
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const queue = JSON.parse(read_file(queuePath))
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const execTasks = queue.queue.map(entry => ({
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issue_id: entry.issue_id,
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solution_id: entry.solution_id,
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title: entry.title || entry.issue_id,
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priority: entry.priority || "normal",
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depends_on: entry.depends_on || []
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}))
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// Output structured wave data for orchestrator
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console.log(`
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WAVE_READY:
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ISSUE_READY:
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${JSON.stringify({
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wave_number: waveNum,
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issue_ids: waveIssues,
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queue_path: queuePath,
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exec_tasks: execTasks
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}, null, 2)}
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issue_id: issueId,
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solution_id: solution.bound?.id || 'N/A',
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title: solution.bound?.title || issueId,
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priority: "normal",
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depends_on: blockedBy,
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solution_file: solutionFile
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}, null, 2)}
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`)
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// Wait for orchestrator send_input before continuing to next wave
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// (orchestrator will send: "Wave N dispatched. Continue to Wave N+1.")
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// Wait for orchestrator send_input before continuing to next issue
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// (orchestrator will send: "Issue dispatched. Continue to next issue.")
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}
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```
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### Step 4: Finalization
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After all waves are planned, output ALL_PLANNED signal.
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After all issues are planned, output ALL_PLANNED signal.
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```javascript
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console.log(`
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ALL_PLANNED:
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${JSON.stringify({
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total_waves: waveNum,
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total_issues: issueIds.length
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}, null, 2)}
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`)
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```
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## Inline Conflict Check
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```javascript
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function inlineConflictCheck(issueId, solution, dispatchedSolutions) {
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const currentFiles = solution.bound?.files_touched
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|| solution.bound?.affected_files || []
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const blockedBy = []
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// 1. File conflict detection
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for (const prev of dispatchedSolutions) {
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const prevFiles = prev.solution.bound?.files_touched
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|| prev.solution.bound?.affected_files || []
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const overlap = currentFiles.filter(f => prevFiles.includes(f))
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if (overlap.length > 0) {
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blockedBy.push(prev.issueId)
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}
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}
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// 2. Explicit dependencies
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const explicitDeps = solution.bound?.dependencies?.on_issues || []
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for (const depId of explicitDeps) {
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if (!blockedBy.includes(depId)) {
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blockedBy.push(depId)
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}
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}
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return blockedBy
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}
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```
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## Role Boundaries
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### MUST
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- 仅执行规划和拆解工作
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- 每个 wave 完成后输出 WAVE_READY 结构化数据
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- 所有 wave 完成后输出 ALL_PLANNED
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- 通过 spawn_agent 调用 issue-plan-agent 和 issue-queue-agent
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- 等待 orchestrator send_input 才继续下一 wave
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- 每个 issue 完成后输出 ISSUE_READY 结构化数据
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- 所有 issues 完成后输出 ALL_PLANNED
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- 通过 spawn_agent 调用 issue-plan-agent（逐个 issue）
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- 等待 orchestrator send_input 才继续下一 issue
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- 将 solution 写入中间产物文件
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### MUST NOT
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@@ -267,16 +264,17 @@ function parsePlanPhases(planContent) {
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**ALWAYS**:
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- Read role definition file as FIRST action (Step 1)
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- Follow structured output template (WAVE_READY / ALL_PLANNED)
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- Follow structured output template (ISSUE_READY / ALL_PLANNED)
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- Stay within planning boundaries (no code implementation)
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- Spawn issue-plan-agent and issue-queue-agent for each wave
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- Include all issue IDs and solution references in wave data
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- Spawn issue-plan-agent for each issue individually
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- Write solution artifact file before outputting ISSUE_READY
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- Include solution_file path in ISSUE_READY data
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**NEVER**:
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- Modify source code files
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- Skip context loading (Step 1)
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- Produce unstructured or free-form output
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- Continue to next wave without outputting WAVE_READY
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- Continue to next issue without outputting ISSUE_READY
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- Close without outputting ALL_PLANNED
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## Error Handling
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@@ -285,7 +283,8 @@ function parsePlanPhases(planContent) {
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|----------|--------|
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| Issue creation failure | Retry once with simplified text, report in output |
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| issue-plan-agent timeout | Urge convergence via send_input, close and report partial |
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| issue-queue-agent failure | Create exec tasks without DAG ordering |
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| Inline conflict check failure | Use empty depends_on, continue |
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| Solution artifact write failure | Report error, continue with ISSUE_READY output |
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| Plan file not found | Report error in output with CLARIFICATION_NEEDED |
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| Empty input (no issues, no text) | Output CLARIFICATION_NEEDED asking for requirements |
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| Sub-agent produces invalid output | Report error, continue with available data |
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Reference in New Issue
Block a user