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
2026-02-25 21:40:24 +08:00
parent 4c2bf31525
commit b2b8688d26
24 changed files with 1287 additions and 651 deletions

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@@ -6,7 +6,7 @@ allowed-tools: TeamCreate(*), TeamDelete(*), SendMessage(*), TaskCreate(*), Task
# Team PlanEx
2 成员边规划边执行团队。通过 Wave Pipeline波次流水线实现 planner 和 executor 并行工作planner 完成一个 wave 的 queue 后立即创建 EXEC-* 任务,同时进入下一 wave 规划。所有成员通过 `--role=xxx` 路由。
2 成员边规划边执行团队。通过逐 Issue 节拍流水线实现 planner 和 executor 并行工作planner 完成一个 issue 的 solution 后立即创建 EXEC-* 任务含中间产物文件路径executor 从文件加载 solution 开始实现。所有成员通过 `--role=xxx` 路由。
## Architecture Overview
@@ -63,7 +63,7 @@ Read(VALID_ROLES[role].file)
| Role | Task Prefix | Responsibility | Reuses Agent | Role File |
|------|-------------|----------------|--------------|-----------|
| `planner` | PLAN-* | 需求拆解 → issue 创建 → 方案设计 → 队列编排 → EXEC 任务派发 | issue-plan-agent, issue-queue-agent | [roles/planner.md](roles/planner.md) |
| `planner` | PLAN-* | 需求拆解 → issue 创建 → 方案设计 → 冲突检查 → EXEC 任务逐个派发 | issue-plan-agent | [roles/planner.md](roles/planner.md) |
| `executor` | EXEC-* | 加载 solution → 代码实现 → 测试 → 提交 | code-developer | [roles/executor.md](roles/executor.md) |
## Input Types
@@ -93,7 +93,7 @@ mcp__ccw-tools__team_msg({ summary: `[${role}] ...` })
|------|------|
| 需求拆解 (issue 创建) | ❌ 直接编写/修改代码 |
| 方案设计 (issue-plan-agent) | ❌ 调用 code-developer |
| 队列编排 (issue-queue-agent) | ❌ 运行测试 |
| 冲突检查 (inline files_touched) | ❌ 运行测试 |
| 创建 EXEC-* 任务 | ❌ git commit |
| 监控进度 (消息总线) | |
@@ -113,6 +113,7 @@ mcp__ccw-tools__team_msg({ summary: `[${role}] ...` })
const TEAM_CONFIG = {
name: "planex",
sessionDir: ".workflow/.team/PEX-{slug}-{date}/",
artifactsDir: ".workflow/.team/PEX-{slug}-{date}/artifacts/",
issueDataDir: ".workflow/issues/"
}
```
@@ -135,7 +136,7 @@ mcp__ccw-tools__team_msg({
| Role | Types |
|------|-------|
| planner | `wave_ready`, `queue_ready`, `all_planned`, `error` |
| planner | `wave_ready`, `issue_ready`, `all_planned`, `error` |
| executor | `impl_complete`, `impl_failed`, `wave_done`, `error` |
### CLI Fallback
@@ -161,22 +162,22 @@ TaskUpdate({ taskId: task.id, status: 'in_progress' })
// Phase 5: Report + Loop
```
## Wave Pipeline
## Wave Pipeline (逐 Issue 节拍)
```
Wave 1: planner 创建 issues + 规划 solutions + 形成 queue
↓ (queue ready → 创建 EXEC-* 任务)
Wave 1 执行: executor 开始实现 ←→ planner 继续规划 Wave 2
Wave 2 执行: executor 实现 Wave 2 ←→ planner 规划 Wave 3
...
Final: planner 发送 all_planned → executor 完成剩余 EXEC-* → 结束
Issue 1: planner 规划 solution → 写中间产物 → 冲突检查 → 创建 EXEC-* → issue_ready
↓ (executor 立即开始)
Issue 2: planner 规划 solution → 写中间产物 → 冲突检查 → 创建 EXEC-* → issue_ready
↓ (executor 并行消费)
Issue N: ...
Final: planner 发送 all_planned → executor 完成剩余 EXEC-* → 结束
```
**波次规则**:
- planner 每完成一个 wave 的 queue 后,立即创建 EXEC-* 任务供 executor 消费
- planner 不等待 executor 完成当前 wave直接进入下一 wave
- executor 持续轮询并消费可用的 EXEC-* 任务
**节拍规则**:
- planner 每完成一个 issue 的 solution 后,**立即**创建 EXEC-* 任务并发送 `issue_ready` 信号
- solution 写入中间产物文件(`artifacts/solutions/{issueId}.json`EXEC-* 任务包含 `solution_file` 路径
- executor 从文件加载 solution无需再调 `ccw issue solution`fallback 兼容旧模式
- planner 不等待 executor持续推进下一个 issue
- 当 planner 发送 `all_planned` 消息后executor 完成所有剩余任务即可结束
## Execution Method Selection
@@ -265,6 +266,13 @@ Skill(skill="team-planex", args="-y --text '添加日志'")
// 1. 创建团队
TeamCreate({ team_name: teamName })
// 1.5 初始化 sessionDir + artifacts 目录
const slug = (issueIds[0] || 'batch').replace(/[^a-zA-Z0-9-]/g, '')
const dateStr = new Date().toISOString().slice(0,10).replace(/-/g,'')
const sessionId = `PEX-${slug}-${dateStr}`
const sessionDir = `.workflow/.team/${sessionId}`
Bash(`mkdir -p "${sessionDir}/artifacts/solutions"`)
// 2. 解析输入参数
const issueIds = args.match(/ISS-\d{8}-\d{6}/g) || []
const textMatch = args.match(/--text\s+['"]([^'"]+)['"]/)
@@ -298,11 +306,17 @@ executor 的执行方式已确定: ${executionConfig.executionMethod}
execution_method: ${executionConfig.executionMethod}
code_review: ${executionConfig.codeReviewTool}
## 中间产物(必须)
sessionDir: ${sessionDir}
每个 issue 的 solution 写入: ${sessionDir}/artifacts/solutions/{issueId}.json
EXEC-* 任务 description 必须包含 solution_file 字段指向该文件
每完成一个 issue 立即发送 issue_ready 消息并创建 EXEC-* 任务
## 角色准则(强制)
- 你只能处理 PLAN-* 前缀的任务
- 所有输出必须带 [planner] 标识前缀
- 完成wave 后立即创建 EXEC-* 任务供 executor 消费
- EXEC-* 任务 description 中必须包含 execution_method 字段
- 完成issue 的 solution 后立即创建 EXEC-* 任务(逐 issue 派发,不等 wave 完成)
- EXEC-* 任务 description 中必须包含 execution_method 和 solution_file 字段
## 消息总线(必须)
每次 SendMessage 前,先调用 mcp__ccw-tools__team_msg 记录。
@@ -327,6 +341,10 @@ Task({
代码审查: ${executionConfig.codeReviewTool}
(每个 EXEC-* 任务 description 中可能包含 execution_method 覆盖)
## Solution 加载
优先从 EXEC-* 任务 description 中的 solution_file 路径读取 solution JSON 文件
无 solution_file 时 fallback 到 ccw issue solution 命令
## 角色准则(强制)
- 你只能处理 EXEC-* 前缀的任务
- 所有输出必须带 [executor] 标识前缀
@@ -351,7 +369,7 @@ Task({
| Unknown --role value | Error with available role list |
| Missing --role arg | Enter orchestration mode |
| Role file not found | Error with expected path (roles/{name}.md) |
| Planner wave failure | Retry once, then report error and halt pipeline |
| Planner issue planning failure | Retry once, then report error and skip to next issue |
| Executor impl failure | Report to planner, continue with next EXEC-* task |
| No EXEC-* tasks yet | Executor idles, polls for new tasks |
| Pipeline stall | Planner monitors — if executor blocked > 2 tasks, escalate to user |

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@@ -72,7 +72,7 @@
```javascript
// 从任务描述中解析 execution_method
function resolveExecutor(taskDesc, solutionTaskCount) {
const methodMatch = taskDesc.match(/execution_method:\s*(Agent|Codex|Gemini|Auto)/i)
const methodMatch = taskDesc.match(/execution_method[:\s]*\s*(Agent|Codex|Gemini|Auto)/i)
const method = methodMatch ? methodMatch[1] : 'Auto'
if (method.toLowerCase() === 'auto') {
@@ -165,9 +165,20 @@ if (!issueId) {
return
}
// Load solution plan
const solJson = Bash(`ccw issue solution ${issueId} --json`)
const solution = JSON.parse(solJson)
// Load solution plan — dual mode: file-first, CLI fallback
const solutionFileMatch = task.description.match(/solution_file[:\s]*\s*(\S+\.json)/)
let solution
if (solutionFileMatch) {
// 新模式:从中间产物文件加载
const solutionData = JSON.parse(Read(solutionFileMatch[1]))
// 保持 solution.bound 结构兼容
solution = solutionData.bound ? solutionData : { bound: solutionData }
} else {
// 兼容模式:从 ccw issue solution 加载
const solJson = Bash(`ccw issue solution ${issueId} --json`)
solution = JSON.parse(solJson)
}
if (!solution.bound) {
mcp__ccw-tools__team_msg({

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@@ -1,6 +1,6 @@
# Role: planner
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
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
## Role Identity
@@ -16,8 +16,8 @@
- 仅处理 `PLAN-*` 前缀的任务
- 所有输出必须带 `[planner]` 标识
- 完成wave 的 queue 后**立即创建 EXEC-\* 任务**
- 不等待 executor 完成当前 wave直接进入下一 wave 规划
- 完成issue 的 solution 后**立即创建 EXEC-\* 任务**并发送 `issue_ready` 信号
- 不等待 executor,持续推进下一个 issue
### MUST NOT
@@ -30,8 +30,8 @@
| Type | Direction | Trigger | Description |
|------|-----------|---------|-------------|
| `wave_ready` | planner → executor | Wave queue 完成 + EXEC 任务已创建 | 新 wave 可执行 |
| `queue_ready` | planner → executor | 单个 issue 的 queue 就绪 | 增量通知 |
| `issue_ready` | planner → executor | 单个 issue solution + EXEC 任务已创建 | 逐 issue 节拍信号 |
| `wave_ready` | planner → executor | 一组 issues 全部派发完毕 | wave 汇总信号 |
| `all_planned` | planner → executor | 所有 wave 规划完毕 | 最终信号 |
| `error` | planner → executor | 阻塞性错误 | 规划失败 |
@@ -41,8 +41,7 @@
| Agent Type | Purpose |
|------------|---------|
| `issue-plan-agent` | Closed-loop planning: ACE exploration + solution generation + binding |
| `issue-queue-agent` | Solution ordering + conflict detection → execution queue |
| `issue-plan-agent` | Closed-loop planning: ACE exploration + solution generation + binding (单 issue 粒度) |
### CLI Capabilities
@@ -167,188 +166,217 @@ if (inputType === 'plan_file') {
Issue IDs 已就绪,直接进入 solution 规划。
#### Path D: execution-plan.json → 波次感知处理
#### Path D: execution-plan.json → 波次感知逐 issue 处理
```javascript
if (inputType === 'execution_plan') {
const projectRoot = Bash('cd . && pwd').trim()
const waves = executionPlan.waves
const dispatchedSolutions = []
// sessionDir 从 planner prompt 中的 sessionDir 变量获取
const execution_method = args.match(/execution_method:\s*(\S+)/)?.[1] || 'Auto'
const code_review = args.match(/code_review:\s*(\S+)/)?.[1] || 'Skip'
let waveNum = 0
for (const wave of waves) {
waveNum++
const waveIssues = wave.issue_ids
// Step 1: issue-plan-agent 生成 solutions
const planResult = Task({
subagent_type: "issue-plan-agent",
run_in_background: false,
description: `Plan solutions for wave ${waveNum}: ${wave.label}`,
prompt: `
issue_ids: ${JSON.stringify(waveIssues)}
for (const issueId of wave.issue_ids) {
// Step 1: 单 issue 规划
const planResult = Task({
subagent_type: "issue-plan-agent",
run_in_background: false,
description: `Plan solution for ${issueId}`,
prompt: `issue_ids: ["${issueId}"]
project_root: "${projectRoot}"
## Requirements
- Generate solutions for each issue
- Auto-bind single solutions
- Generate solution for this issue
- Auto-bind single solution
- Issues come from req-plan decomposition (tags: req-plan)
- Respect inter-issue dependencies: ${JSON.stringify(executionPlan.issue_dependencies)}
`
- Respect dependencies: ${JSON.stringify(executionPlan.issue_dependencies)}`
})
// Step 2: 获取 solution + 写中间产物
const solJson = Bash(`ccw issue solution ${issueId} --json`)
const solution = JSON.parse(solJson)
const solutionFile = `${sessionDir}/artifacts/solutions/${issueId}.json`
Write({
file_path: solutionFile,
content: JSON.stringify({
session_id: sessionId, issue_id: issueId, ...solution,
execution_config: { execution_method, code_review },
timestamp: new Date().toISOString()
}, null, 2)
})
// Step 3: inline 冲突检查
const blockedBy = inlineConflictCheck(issueId, solution, dispatchedSolutions)
// Step 4: 创建 EXEC-* 任务
const execTask = TaskCreate({
subject: `EXEC-W${waveNum}-${issueId}: 实现 ${solution.bound?.title || issueId}`,
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}`,
activeForm: `实现 ${issueId}`,
owner: "executor"
})
if (blockedBy.length > 0) {
TaskUpdate({ taskId: execTask.id, addBlockedBy: blockedBy })
}
// Step 5: 累积 + 节拍信号
dispatchedSolutions.push({ issueId, solution, execTaskId: execTask.id })
mcp__ccw-tools__team_msg({
operation: "log", team: "planex", from: "planner", to: "executor",
type: "issue_ready",
summary: `[planner] issue_ready: ${issueId}`,
ref: solutionFile
})
SendMessage({
type: "message", recipient: "executor",
content: `## [planner] Issue Ready: ${issueId}\n**solution_file**: ${solutionFile}\n**EXEC task**: ${execTask.subject}`,
summary: `[planner] issue_ready: ${issueId}`
})
}
// wave 级汇总
mcp__ccw-tools__team_msg({
operation: "log", team: "planex", from: "planner", to: "executor",
type: "wave_ready",
summary: `[planner] Wave ${waveNum} fully dispatched: ${wave.issue_ids.length} issues`
})
// Step 2: issue-queue-agent 形成 queue
const queueResult = Task({
subagent_type: "issue-queue-agent",
run_in_background: false,
description: `Form queue for wave ${waveNum}: ${wave.label}`,
prompt: `
issue_ids: ${JSON.stringify(waveIssues)}
project_root: "${projectRoot}"
## Requirements
- Order solutions by dependency (DAG)
- Detect conflicts between solutions
- Respect wave dependencies: ${JSON.stringify(wave.depends_on_waves)}
- Output execution queue
`
})
// Step 3: → Phase 4 (Wave Dispatch) - create EXEC-* tasks
// Continue to next wave without waiting for executor
}
// After all waves → Phase 5 (Report + Finalize)
}
```
**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。
**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。
#### Wave 规划Path A/B/C 汇聚)
#### Wave 规划Path A/B/C 汇聚)— 逐 issue 派发
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):
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):
```javascript
if (inputType !== 'execution_plan') {
// Path A/B/C: 固定 batch=5 分组
const projectRoot = Bash('cd . && pwd').trim()
const dispatchedSolutions = []
const execution_method = args.match(/execution_method:\s*(\S+)/)?.[1] || 'Auto'
const code_review = args.match(/code_review:\s*(\S+)/)?.[1] || 'Skip'
let waveNum = 1 // 简化:不再按 WAVE_SIZE=5 分组,全部视为一个逻辑 wave
// 按批次分组(每 wave 最多 5 个 issues
const WAVE_SIZE = 5
const waves = []
for (let i = 0; i < issueIds.length; i += WAVE_SIZE) {
waves.push(issueIds.slice(i, i + WAVE_SIZE))
}
let waveNum = 0
for (const waveIssues of waves) {
waveNum++
// Step 1: 调用 issue-plan-agent 生成 solutions
const planResult = Task({
subagent_type: "issue-plan-agent",
run_in_background: false,
description: `Plan solutions for wave ${waveNum}`,
prompt: `
issue_ids: ${JSON.stringify(waveIssues)}
for (const issueId of issueIds) {
// Step 1: 单 issue 规划
const planResult = Task({
subagent_type: "issue-plan-agent",
run_in_background: false,
description: `Plan solution for ${issueId}`,
prompt: `issue_ids: ["${issueId}"]
project_root: "${projectRoot}"
## Requirements
- Generate solutions for each issue
- Auto-bind single solutions
- For multiple solutions, select the most pragmatic one
`
})
- Generate solution for this issue
- Auto-bind single solution
- For multiple solutions, select the most pragmatic one`
})
// Step 2: 调用 issue-queue-agent 形成 queue
const queueResult = Task({
subagent_type: "issue-queue-agent",
run_in_background: false,
description: `Form queue for wave ${waveNum}`,
prompt: `
issue_ids: ${JSON.stringify(waveIssues)}
project_root: "${projectRoot}"
// Step 2: 获取 solution + 写中间产物
const solJson = Bash(`ccw issue solution ${issueId} --json`)
const solution = JSON.parse(solJson)
const solutionFile = `${sessionDir}/artifacts/solutions/${issueId}.json`
Write({
file_path: solutionFile,
content: JSON.stringify({
session_id: sessionId, issue_id: issueId, ...solution,
execution_config: { execution_method, code_review },
timestamp: new Date().toISOString()
}, null, 2)
})
## Requirements
- Order solutions by dependency (DAG)
- Detect conflicts between solutions
- Output execution queue
`
})
// Step 3: inline 冲突检查
const blockedBy = inlineConflictCheck(issueId, solution, dispatchedSolutions)
// Step 3: → Phase 4 (Wave Dispatch)
}
// Step 4: 创建 EXEC-* 任务
const execTask = TaskCreate({
subject: `EXEC-W${waveNum}-${issueId}: 实现 ${solution.bound?.title || issueId}`,
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}`,
activeForm: `实现 ${issueId}`,
owner: "executor"
})
if (blockedBy.length > 0) {
TaskUpdate({ taskId: execTask.id, addBlockedBy: blockedBy })
}
// Step 5: 累积 + 节拍信号
dispatchedSolutions.push({ issueId, solution, execTaskId: execTask.id })
mcp__ccw-tools__team_msg({
operation: "log", team: "planex", from: "planner", to: "executor",
type: "issue_ready",
summary: `[planner] issue_ready: ${issueId}`,
ref: solutionFile
})
SendMessage({
type: "message", recipient: "executor",
content: `## [planner] Issue Ready: ${issueId}\n**solution_file**: ${solutionFile}\n**EXEC task**: ${execTask.subject}`,
summary: `[planner] issue_ready: ${issueId}`
})
}
} // end if (inputType !== 'execution_plan')
```
### Phase 4: Wave Dispatch
### Phase 4: Inline Conflict Check + Wave Summary
每个 wave 的 queue 完成后,**立即创建 EXEC-\* 任务**供 executor 消费
EXEC-* 任务创建已在 Phase 3 逐 issue 完成Phase 4 仅负责 inline 冲突检查函数定义和 wave 汇总
#### Inline Conflict Check 函数
```javascript
// Read the generated queue
const queuePath = `.workflow/issues/queue/execution-queue.json`
const queue = JSON.parse(Read(queuePath))
// Inline conflict check — 替代 issue-queue-agent
// 基于 files_touched 重叠检测 + 显式依赖
function inlineConflictCheck(issueId, solution, dispatchedSolutions) {
const currentFiles = solution.bound?.files_touched
|| solution.bound?.affected_files || []
const blockedBy = []
// Create EXEC-* tasks from queue entries
const execTasks = []
for (const entry of queue.queue) {
const execTask = TaskCreate({
subject: `EXEC-W${waveNum}-${entry.issue_id}: 实现 ${entry.title || entry.issue_id}`,
description: `## 执行任务
**Wave**: ${waveNum}
**Issue**: ${entry.issue_id}
**Solution**: ${entry.solution_id}
**Priority**: ${entry.priority || 'normal'}
**Dependencies**: ${entry.depends_on?.join(', ') || 'none'}
加载 solution plan 并实现代码。完成后运行测试、提交。`,
activeForm: `实现 ${entry.issue_id}`,
owner: "executor"
})
execTasks.push(execTask)
}
// Set up dependency chains between EXEC tasks (based on queue DAG)
for (const entry of queue.queue) {
if (entry.depends_on?.length > 0) {
const thisTask = execTasks.find(t => t.subject.includes(entry.issue_id))
const depTasks = entry.depends_on.map(depId =>
execTasks.find(t => t.subject.includes(depId))
).filter(Boolean)
if (thisTask && depTasks.length > 0) {
TaskUpdate({
taskId: thisTask.id,
addBlockedBy: depTasks.map(t => t.id)
})
// 1. 文件冲突检测
for (const prev of dispatchedSolutions) {
const prevFiles = prev.solution.bound?.files_touched
|| prev.solution.bound?.affected_files || []
const overlap = currentFiles.filter(f => prevFiles.includes(f))
if (overlap.length > 0) {
blockedBy.push(prev.execTaskId)
}
}
// 2. 显式依赖
const explicitDeps = solution.bound?.dependencies?.on_issues || []
for (const depId of explicitDeps) {
const depTask = dispatchedSolutions.find(d => d.issueId === depId)
if (depTask && !blockedBy.includes(depTask.execTaskId)) {
blockedBy.push(depTask.execTaskId)
}
}
return blockedBy
}
```
// Notify executor: wave ready
#### Wave Summary Signal
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):
```javascript
// Wave summary — 已在 Phase 3 循环中由每个 wave 末尾发送
// Path A/B/C: 全部 issue 完成后发送一次
mcp__ccw-tools__team_msg({
operation: "log",
team: "planex",
from: "planner",
to: "executor",
operation: "log", team: "planex", from: "planner", to: "executor",
type: "wave_ready",
summary: `[planner] Wave ${waveNum} ready: ${execTasks.length} EXEC tasks created`
summary: `[planner] Wave ${waveNum} fully dispatched: ${issueIds.length} issues`
})
SendMessage({
type: "message",
recipient: "executor",
content: `## [planner] Wave ${waveNum} Ready
**Issues**: ${waveIssues.join(', ')}
**EXEC Tasks Created**: ${execTasks.length}
**Queue**: ${queuePath}
Executor 可以开始实现。`,
type: "message", recipient: "executor",
content: `## [planner] Wave ${waveNum} Complete\n所有 issues 已逐个派发完毕,共 ${dispatchedSolutions.length} 个 EXEC 任务。`,
summary: `[planner] wave_ready: wave ${waveNum}`
})
// 不等待 executor 完成,继续下一 wave → back to Phase 3 loop
```
### 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 |
| 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 |