mirror of
https://github.com/catlog22/Claude-Code-Workflow.git
synced 2026-02-28 09:23:08 +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
@@ -1,6 +1,6 @@
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# Role: planner
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需求拆解 → issue 创建 → 方案设计 → 队列编排 → EXEC 任务派发。内部调用 issue-plan-agent 和 issue-queue-agent，并通过 Wave Pipeline 持续推进。planner 同时承担 lead 角色（无独立 coordinator）。
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需求拆解 → issue 创建 → 方案设计 → 冲突检查 → EXEC 任务逐个派发。内部调用 issue-plan-agent（单 issue），通过 inline files_touched 冲突检查替代 issue-queue-agent，每完成一个 issue 立即派发 EXEC-* 任务。planner 同时承担 lead 角色（无独立 coordinator）。
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## Role Identity
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@@ -16,8 +16,8 @@
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- 仅处理 `PLAN-*` 前缀的任务
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- 所有输出必须带 `[planner]` 标识
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- 完成每个 wave 的 queue 后**立即创建 EXEC-\* 任务**
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- 不等待 executor 完成当前 wave，直接进入下一 wave 规划
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- 每完成一个 issue 的 solution 后**立即创建 EXEC-\* 任务**并发送 `issue_ready` 信号
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- 不等待 executor，持续推进下一个 issue
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### MUST NOT
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@@ -30,8 +30,8 @@
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| Type | Direction | Trigger | Description |
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|------|-----------|---------|-------------|
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| `wave_ready` | planner → executor | Wave queue 完成 + EXEC 任务已创建 | 新 wave 可执行 |
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| `queue_ready` | planner → executor | 单个 issue 的 queue 就绪 | 增量通知 |
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| `issue_ready` | planner → executor | 单个 issue solution + EXEC 任务已创建 | 逐 issue 节拍信号 |
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| `wave_ready` | planner → executor | 一组 issues 全部派发完毕 | wave 汇总信号 |
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| `all_planned` | planner → executor | 所有 wave 规划完毕 | 最终信号 |
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| `error` | planner → executor | 阻塞性错误 | 规划失败 |
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@@ -41,8 +41,7 @@
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| Agent Type | Purpose |
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|------------|---------|
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| `issue-plan-agent` | Closed-loop planning: ACE exploration + solution generation + binding |
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| `issue-queue-agent` | Solution ordering + conflict detection → execution queue |
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| `issue-plan-agent` | Closed-loop planning: ACE exploration + solution generation + binding (单 issue 粒度) |
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### CLI Capabilities
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@@ -167,188 +166,217 @@ if (inputType === 'plan_file') {
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Issue IDs 已就绪，直接进入 solution 规划。
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#### Path D: execution-plan.json → 波次感知处理
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#### Path D: execution-plan.json → 波次感知逐 issue 处理
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```javascript
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if (inputType === 'execution_plan') {
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const projectRoot = Bash('cd . && pwd').trim()
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const waves = executionPlan.waves
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const dispatchedSolutions = []
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// sessionDir 从 planner prompt 中的 sessionDir 变量获取
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const execution_method = args.match(/execution_method:\s*(\S+)/)?.[1] || 'Auto'
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const code_review = args.match(/code_review:\s*(\S+)/)?.[1] || 'Skip'
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let waveNum = 0
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for (const wave of waves) {
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waveNum++
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const waveIssues = wave.issue_ids
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// Step 1: issue-plan-agent 生成 solutions
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const planResult = Task({
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subagent_type: "issue-plan-agent",
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run_in_background: false,
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description: `Plan solutions for wave ${waveNum}: ${wave.label}`,
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prompt: `
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issue_ids: ${JSON.stringify(waveIssues)}
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for (const issueId of wave.issue_ids) {
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// Step 1: 单 issue 规划
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const planResult = Task({
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subagent_type: "issue-plan-agent",
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run_in_background: false,
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description: `Plan solution for ${issueId}`,
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prompt: `issue_ids: ["${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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- Issues come from req-plan decomposition (tags: req-plan)
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- Respect inter-issue dependencies: ${JSON.stringify(executionPlan.issue_dependencies)}
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`
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- Respect dependencies: ${JSON.stringify(executionPlan.issue_dependencies)}`
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})
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// Step 2: 获取 solution + 写中间产物
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const solJson = Bash(`ccw issue solution ${issueId} --json`)
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const solution = JSON.parse(solJson)
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const solutionFile = `${sessionDir}/artifacts/solutions/${issueId}.json`
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Write({
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file_path: solutionFile,
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content: JSON.stringify({
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session_id: sessionId, issue_id: issueId, ...solution,
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execution_config: { execution_method, code_review },
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timestamp: new Date().toISOString()
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}, null, 2)
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})
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// Step 3: inline 冲突检查
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const blockedBy = inlineConflictCheck(issueId, solution, dispatchedSolutions)
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// Step 4: 创建 EXEC-* 任务
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const execTask = TaskCreate({
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subject: `EXEC-W${waveNum}-${issueId}: 实现 ${solution.bound?.title || issueId}`,
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description: `## 执行任务\n**Wave**: ${waveNum}\n**Issue**: ${issueId}\n**solution_file**: ${solutionFile}\n**execution_method**: ${execution_method}\n**code_review**: ${code_review}`,
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activeForm: `实现 ${issueId}`,
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owner: "executor"
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})
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if (blockedBy.length > 0) {
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TaskUpdate({ taskId: execTask.id, addBlockedBy: blockedBy })
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}
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// Step 5: 累积 + 节拍信号
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dispatchedSolutions.push({ issueId, solution, execTaskId: execTask.id })
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mcp__ccw-tools__team_msg({
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operation: "log", team: "planex", from: "planner", to: "executor",
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type: "issue_ready",
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summary: `[planner] issue_ready: ${issueId}`,
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ref: solutionFile
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})
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SendMessage({
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type: "message", recipient: "executor",
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content: `## [planner] Issue Ready: ${issueId}\n**solution_file**: ${solutionFile}\n**EXEC task**: ${execTask.subject}`,
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summary: `[planner] issue_ready: ${issueId}`
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})
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}
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// wave 级汇总
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mcp__ccw-tools__team_msg({
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operation: "log", team: "planex", from: "planner", to: "executor",
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type: "wave_ready",
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summary: `[planner] Wave ${waveNum} fully dispatched: ${wave.issue_ids.length} issues`
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})
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// Step 2: issue-queue-agent 形成 queue
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const queueResult = Task({
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subagent_type: "issue-queue-agent",
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run_in_background: false,
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description: `Form queue for wave ${waveNum}: ${wave.label}`,
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prompt: `
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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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- Respect wave dependencies: ${JSON.stringify(wave.depends_on_waves)}
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- Output execution queue
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`
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})
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// Step 3: → Phase 4 (Wave Dispatch) - create EXEC-* tasks
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// Continue to next wave without waiting for executor
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}
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// After all waves → Phase 5 (Report + Finalize)
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}
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```
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**关键差异**: 波次分组来自 `executionPlan.waves`，而非固定 batch=5。Progressive 模式下 L0(Wave 1) → L1(Wave 2)，Direct 模式下 parallel_group 映射为 wave。
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**关键差异**: 波次分组来自 `executionPlan.waves`，但每个 issue 独立规划 + 即时派发。Progressive 模式下 L0(Wave 1) → L1(Wave 2)，Direct 模式下 parallel_group 映射为 wave。
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#### Wave 规划（Path A/B/C 汇聚）
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#### Wave 规划（Path A/B/C 汇聚）— 逐 issue 派发
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将 issueIds 按波次分组规划（Path D 使用独立的波次逻辑，不走此路径）：
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将 issueIds 逐个规划并即时派发（Path D 使用独立的波次逻辑，不走此路径）：
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```javascript
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if (inputType !== 'execution_plan') {
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// Path A/B/C: 固定 batch=5 分组
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const projectRoot = Bash('cd . && pwd').trim()
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const dispatchedSolutions = []
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const execution_method = args.match(/execution_method:\s*(\S+)/)?.[1] || 'Auto'
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const code_review = args.match(/code_review:\s*(\S+)/)?.[1] || 'Skip'
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let waveNum = 1 // 简化：不再按 WAVE_SIZE=5 分组，全部视为一个逻辑 wave
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// 按批次分组（每 wave 最多 5 个 issues）
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const WAVE_SIZE = 5
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const 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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let waveNum = 0
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for (const waveIssues of waves) {
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waveNum++
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// Step 1: 调用 issue-plan-agent 生成 solutions
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const planResult = Task({
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subagent_type: "issue-plan-agent",
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run_in_background: false,
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description: `Plan solutions for wave ${waveNum}`,
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prompt: `
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issue_ids: ${JSON.stringify(waveIssues)}
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for (const issueId of issueIds) {
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// Step 1: 单 issue 规划
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const planResult = Task({
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subagent_type: "issue-plan-agent",
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run_in_background: false,
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description: `Plan solution for ${issueId}`,
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prompt: `issue_ids: ["${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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- For multiple solutions, select the most pragmatic one
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`
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})
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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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})
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// Step 2: 调用 issue-queue-agent 形成 queue
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const queueResult = Task({
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subagent_type: "issue-queue-agent",
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run_in_background: false,
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description: `Form queue for wave ${waveNum}`,
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prompt: `
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issue_ids: ${JSON.stringify(waveIssues)}
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project_root: "${projectRoot}"
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// Step 2: 获取 solution + 写中间产物
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const solJson = Bash(`ccw issue solution ${issueId} --json`)
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const solution = JSON.parse(solJson)
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const solutionFile = `${sessionDir}/artifacts/solutions/${issueId}.json`
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Write({
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file_path: solutionFile,
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content: JSON.stringify({
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session_id: sessionId, issue_id: issueId, ...solution,
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execution_config: { execution_method, code_review },
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timestamp: new Date().toISOString()
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}, null, 2)
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})
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## Requirements
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- Order solutions by dependency (DAG)
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- Detect conflicts between solutions
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- Output execution queue
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`
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})
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// Step 3: inline 冲突检查
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const blockedBy = inlineConflictCheck(issueId, solution, dispatchedSolutions)
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// Step 3: → Phase 4 (Wave Dispatch)
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}
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// Step 4: 创建 EXEC-* 任务
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const execTask = TaskCreate({
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subject: `EXEC-W${waveNum}-${issueId}: 实现 ${solution.bound?.title || issueId}`,
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description: `## 执行任务\n**Wave**: ${waveNum}\n**Issue**: ${issueId}\n**solution_file**: ${solutionFile}\n**execution_method**: ${execution_method}\n**code_review**: ${code_review}`,
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activeForm: `实现 ${issueId}`,
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owner: "executor"
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})
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if (blockedBy.length > 0) {
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TaskUpdate({ taskId: execTask.id, addBlockedBy: blockedBy })
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}
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// Step 5: 累积 + 节拍信号
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dispatchedSolutions.push({ issueId, solution, execTaskId: execTask.id })
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mcp__ccw-tools__team_msg({
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operation: "log", team: "planex", from: "planner", to: "executor",
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type: "issue_ready",
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summary: `[planner] issue_ready: ${issueId}`,
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ref: solutionFile
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})
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SendMessage({
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type: "message", recipient: "executor",
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content: `## [planner] Issue Ready: ${issueId}\n**solution_file**: ${solutionFile}\n**EXEC task**: ${execTask.subject}`,
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summary: `[planner] issue_ready: ${issueId}`
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})
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}
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} // end if (inputType !== 'execution_plan')
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```
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### Phase 4: Wave Dispatch
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### Phase 4: Inline Conflict Check + Wave Summary
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每个 wave 的 queue 完成后，**立即创建 EXEC-\* 任务**供 executor 消费。
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EXEC-* 任务创建已在 Phase 3 逐 issue 完成，Phase 4 仅负责 inline 冲突检查函数定义和 wave 汇总。
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#### Inline Conflict Check 函数
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```javascript
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// Read the generated queue
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const queuePath = `.workflow/issues/queue/execution-queue.json`
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const queue = JSON.parse(Read(queuePath))
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// Inline conflict check — 替代 issue-queue-agent
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// 基于 files_touched 重叠检测 + 显式依赖
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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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// Create EXEC-* tasks from queue entries
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const execTasks = []
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for (const entry of queue.queue) {
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const execTask = TaskCreate({
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subject: `EXEC-W${waveNum}-${entry.issue_id}: 实现 ${entry.title || entry.issue_id}`,
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description: `## 执行任务
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**Wave**: ${waveNum}
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**Issue**: ${entry.issue_id}
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**Solution**: ${entry.solution_id}
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**Priority**: ${entry.priority || 'normal'}
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**Dependencies**: ${entry.depends_on?.join(', ') || 'none'}
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加载 solution plan 并实现代码。完成后运行测试、提交。`,
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activeForm: `实现 ${entry.issue_id}`,
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owner: "executor"
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})
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execTasks.push(execTask)
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}
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// Set up dependency chains between EXEC tasks (based on queue DAG)
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for (const entry of queue.queue) {
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if (entry.depends_on?.length > 0) {
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const thisTask = execTasks.find(t => t.subject.includes(entry.issue_id))
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const depTasks = entry.depends_on.map(depId =>
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execTasks.find(t => t.subject.includes(depId))
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).filter(Boolean)
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if (thisTask && depTasks.length > 0) {
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TaskUpdate({
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taskId: thisTask.id,
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addBlockedBy: depTasks.map(t => t.id)
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})
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// 1. 文件冲突检测
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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.execTaskId)
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}
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}
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// 2. 显式依赖
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const explicitDeps = solution.bound?.dependencies?.on_issues || []
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for (const depId of explicitDeps) {
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const depTask = dispatchedSolutions.find(d => d.issueId === depId)
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if (depTask && !blockedBy.includes(depTask.execTaskId)) {
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blockedBy.push(depTask.execTaskId)
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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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// Notify executor: wave ready
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#### Wave Summary Signal
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Phase 3 循环完成后发送汇总信号（Path A/B/C 在全部 issue 完成后，Path D 在每个 wave 完成后）：
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```javascript
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// Wave summary — 已在 Phase 3 循环中由每个 wave 末尾发送
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// Path A/B/C: 全部 issue 完成后发送一次
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mcp__ccw-tools__team_msg({
|
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operation: "log",
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team: "planex",
|
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from: "planner",
|
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to: "executor",
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operation: "log", team: "planex", from: "planner", to: "executor",
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type: "wave_ready",
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summary: `[planner] Wave ${waveNum} ready: ${execTasks.length} EXEC tasks created`
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summary: `[planner] Wave ${waveNum} fully dispatched: ${issueIds.length} issues`
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})
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SendMessage({
|
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type: "message",
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recipient: "executor",
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content: `## [planner] Wave ${waveNum} Ready
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**Issues**: ${waveIssues.join(', ')}
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**EXEC Tasks Created**: ${execTasks.length}
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**Queue**: ${queuePath}
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Executor 可以开始实现。`,
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type: "message", recipient: "executor",
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content: `## [planner] Wave ${waveNum} Complete\n所有 issues 已逐个派发完毕，共 ${dispatchedSolutions.length} 个 EXEC 任务。`,
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summary: `[planner] wave_ready: wave ${waveNum}`
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})
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// 不等待 executor 完成，继续下一 wave → back to Phase 3 loop
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```
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|
||||
### Phase 5: Report + Finalize
|
||||
@@ -443,9 +471,10 @@ function parsePlanPhases(planContent) {
|
||||
| No PLAN-* tasks available | Idle, wait for orchestrator |
|
||||
| Issue creation failure | Retry once with simplified text, then report error |
|
||||
| issue-plan-agent failure | Retry once, then report error and skip to next issue |
|
||||
| issue-queue-agent failure | Retry once, then create EXEC tasks without DAG ordering |
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||||
| Inline conflict check failure | Skip conflict detection, create EXEC task without blockedBy |
|
||||
| Plan file not found | Report error with expected path |
|
||||
| execution-plan.json parse failure | Fallback to plan_file parsing (Path B) |
|
||||
| execution-plan.json missing waves | Report error, suggest re-running req-plan |
|
||||
| Empty input (no issues, no text, no plan) | AskUserQuestion for clarification |
|
||||
| Solution artifact write failure | Log warning, create EXEC task without solution_file (executor fallback) |
|
||||
| Wave partially failed | Report partial success, continue with successful issues |
|
||||
|
||||
Reference in New Issue
Block a user