mirror of
https://github.com/catlog22/Claude-Code-Workflow.git
synced 2026-02-11 02:33:51 +08:00
Refactor issue management and history tracking
- Removed the interactive issue management command and its associated documentation. - Enhanced the issue planning command to streamline project context reading and solution creation. - Improved queue management with conflict clarification and status syncing from queues. - Added functionality to track completed issues, moving them to a history file upon completion. - Updated CLI options to support syncing issue statuses from queues. - Introduced new API endpoint for retrieving completed issues from history. - Enhanced error handling and validation for issue updates and queue management.
This commit is contained in:
@@ -17,8 +17,7 @@ Queue formation command using **issue-queue-agent** that analyzes all bound solu
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- **Agent-driven**: issue-queue-agent handles all ordering logic
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- **Solution-level granularity**: Queue items are solutions, not tasks
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- Inter-solution dependency DAG (based on file conflicts)
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- File conflict detection between solutions
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- **Conflict clarification**: High-severity conflicts prompt user decision
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- Semantic priority calculation per solution (0.0-1.0)
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- Parallel/Sequential group assignment for solutions
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@@ -52,28 +51,29 @@ ccw issue queue delete <queue-id> Delete queue from history
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```
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Phase 1: Solution Loading
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├─ Load issues.jsonl
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├─ Filter issues with bound_solution_id
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├─ Read solutions/{issue-id}.jsonl for each issue
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├─ Find bound solution by ID
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├─ Collect files_touched from all tasks in solution
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└─ Build solution objects (NOT individual tasks)
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├─ Load issues.jsonl, filter by status='planned' + bound_solution_id
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├─ Read solutions/{issue-id}.jsonl, find bound solution
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├─ Extract files_touched from task modification_points
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└─ Build solution objects array
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Phase 2-4: Agent-Driven Queue Formation (issue-queue-agent)
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├─ Launch issue-queue-agent with all solutions
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├─ Launch issue-queue-agent with solutions array
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├─ Agent performs:
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│ ├─ Detect file overlaps between solutions
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│ ├─ Build dependency DAG from file conflicts
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│ ├─ Detect circular dependencies
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│ ├─ Resolve conflicts using priority rules
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│ ├─ Conflict analysis (5 types via Gemini CLI)
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│ ├─ Build dependency DAG from conflicts
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│ ├─ Calculate semantic priority per solution
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│ └─ Assign execution groups (parallel/sequential)
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└─ Output: queue JSON with ordered solutions (S-1, S-2, ...)
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└─ Agent writes: queue JSON + index update
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Phase 5: Queue Output
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├─ Write queue.json with solutions array
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├─ Update issue statuses in issues.jsonl
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└─ Display queue summary
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Phase 5: Conflict Clarification (if needed)
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├─ Check agent return for `clarifications` array
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├─ If clarifications exist → AskUserQuestion
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├─ Pass user decisions back to agent (resume)
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└─ Agent updates queue with resolved conflicts
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Phase 6: Status Update & Summary
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├─ Update issue statuses to 'queued'
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└─ Display queue summary, next step: /issue:execute
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```
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## Implementation
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@@ -105,87 +105,133 @@ Phase 5: Queue Output
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### Phase 2-4: Agent-Driven Queue Formation
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**Generate Queue ID** (command layer, pass to agent):
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```javascript
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// Generate queue-id ONCE here, pass to agent
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const now = new Date();
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const queueId = `QUE-${now.toISOString().replace(/[-:T]/g, '').slice(0, 14)}`;
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// Build minimal prompt - agent orders SOLUTIONS, not tasks
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const agentPrompt = `
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## Order Solutions
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**Queue ID**: ${queueId}
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**Solutions**: ${allSolutions.length} from ${plannedIssues.length} issues
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**Project Root**: ${process.cwd()}
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### Input (Solution-Level)
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\`\`\`json
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${JSON.stringify(allSolutions, null, 2)}
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\`\`\`
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### Steps
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1. Parse solutions: Extract solution IDs, files_touched, task_count, priority
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2. Detect conflicts: Find file overlaps between solutions (files_touched intersection)
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3. Build DAG: Create dependency edges where solutions share files
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4. Detect cycles: Verify no circular dependencies (abort if found)
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5. Resolve conflicts: Apply ordering rules based on action types
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6. Calculate priority: Compute semantic priority (0.0-1.0) per solution
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7. Assign groups: Parallel (P*) for no-conflict, Sequential (S*) for conflicts
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8. Generate queue: Write queue JSON with ordered solutions
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9. Update index: Update queues/index.json with new queue entry
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### Rules
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- **Solution Granularity**: Queue items are solutions, NOT individual tasks
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- **DAG Validity**: Output must be valid DAG with no circular dependencies
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- **Conflict Detection**: Two solutions conflict if files_touched intersect
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- **Ordering Priority**:
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1. Higher issue priority first (critical > high > medium > low)
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2. Fewer dependencies first (foundation solutions)
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3. More tasks = higher priority (larger impact)
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- **Parallel Safety**: Solutions in same parallel group must have NO file overlaps
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- **Queue Item ID Format**: \`S-N\` (S-1, S-2, S-3, ...)
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- **Queue ID**: Use the provided Queue ID (passed above), do NOT generate new one
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### Generate Files (STRICT - only these 2)
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1. \`.workflow/issues/queues/{Queue ID}.json\` - Use Queue ID from above
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2. \`.workflow/issues/queues/index.json\` - Update existing index
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Write ONLY these 2 files, using the provided Queue ID.
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### Return Summary
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\`\`\`json
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{
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"queue_id": "QUE-YYYYMMDD-HHMMSS",
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"total_solutions": N,
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"total_tasks": N,
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"execution_groups": [{ "id": "P1", "type": "parallel", "count": N }],
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"conflicts_resolved": N,
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"issues_queued": ["ISS-xxx"]
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}
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\`\`\`
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`;
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const result = Task(
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subagent_type="issue-queue-agent",
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run_in_background=false,
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description=`Order ${allSolutions.length} solutions`,
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prompt=agentPrompt
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);
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const summary = JSON.parse(result);
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const queueId = `QUE-${new Date().toISOString().replace(/[-:T]/g, '').slice(0, 14)}`;
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```
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### Phase 5: Validation & Status Update
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**Agent Prompt**:
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```
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## Order Solutions into Execution Queue
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**Validation:**
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- Verify queue file exists at `queues/{queue-id}.json`
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- Check `solutions` array is non-empty → abort if empty
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**Queue ID**: ${queueId}
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**Solutions**: ${solutions.length} from ${issues.length} issues
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**Project Root**: ${cwd}
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**Status Update:**
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- Update each queued issue status to `queued` via `ccw issue update <id> --status queued`
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### Input
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${JSON.stringify(solutions)}
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### Workflow
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Step 1: Build dependency graph from solutions (nodes=solutions, edges=file conflicts)
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Step 2: Use Gemini CLI for conflict analysis (5 types: file, API, data, dependency, architecture)
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Step 3: For high-severity conflicts without clear resolution → add to `clarifications`
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Step 4: Calculate semantic priority (base from issue priority + task_count boost)
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Step 5: Assign execution groups: P* (parallel, no overlaps) / S* (sequential, shared files)
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Step 6: Write queue JSON + update index
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### Output Requirements
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**Write files** (exactly 2):
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- `.workflow/issues/queues/${queueId}.json` - Full queue with solutions, conflicts, groups
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- `.workflow/issues/queues/index.json` - Update with new queue entry
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**Return JSON**:
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\`\`\`json
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{
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"queue_id": "${queueId}",
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"total_solutions": N,
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"total_tasks": N,
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"execution_groups": [{"id": "P1", "type": "parallel", "count": N}],
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"issues_queued": ["ISS-xxx"],
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"clarifications": [{"conflict_id": "CFT-1", "question": "...", "options": [...]}]
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}
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\`\`\`
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### Rules
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- Solution granularity (NOT individual tasks)
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- Queue Item ID format: S-1, S-2, S-3, ...
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- Use provided Queue ID (do NOT generate new)
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- `clarifications` only present if high-severity unresolved conflicts exist
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### Done Criteria
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- [ ] Queue JSON written with all solutions ordered
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- [ ] Index updated with active_queue_id
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- [ ] No circular dependencies
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- [ ] Parallel groups have no file overlaps
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- [ ] Return JSON matches required shape
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```
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**Launch Agent**:
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```javascript
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const result = Task(
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subagent_type="issue-queue-agent",
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prompt=agentPrompt,
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description=`Order ${solutions.length} solutions`
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);
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```
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### Phase 5: Conflict Clarification
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**Check Agent Return:**
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- Parse agent result JSON
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- If `clarifications` array exists and non-empty → user decision required
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**Clarification Flow:**
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```javascript
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if (result.clarifications?.length > 0) {
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for (const clarification of result.clarifications) {
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// Present to user via AskUserQuestion
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const answer = AskUserQuestion({
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questions: [{
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question: clarification.question,
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header: clarification.conflict_id,
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options: clarification.options,
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multiSelect: false
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}]
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});
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// Resume agent with user decision
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Task(
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subagent_type="issue-queue-agent",
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resume=agentId,
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prompt=`Conflict ${clarification.conflict_id} resolved: ${answer.selected}`
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);
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}
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}
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```
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### Phase 6: Status Update & Summary
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**Status Update** (single command):
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```bash
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ccw issue update --from-queue [queue-id] --json
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# Examples
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ccw issue update --from-queue --json # Use active queue
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ccw issue update --from-queue QUE-xxx --json # Use specific queue
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```
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**Output** (JSON):
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```json
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{
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"success": true,
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"queue_id": "QUE-xxx",
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"queued": ["ISS-001", "ISS-002"],
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"queued_count": 2,
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"unplanned": ["ISS-003"],
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"unplanned_count": 1
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}
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```
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**Behavior:**
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- Updates issues in queue to `status: 'queued'` (skips already queued/executing/completed)
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- Identifies planned issues with `bound_solution_id` NOT in queue → `unplanned` array
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- Optional `queue-id`: defaults to active queue if omitted
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**Summary Output:**
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- Display queue ID, solution count, task count, issue IDs
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- Display queue ID, solution count, task count
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- Show unplanned issues (planned but NOT in queue)
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- Show next step: `/issue:execute`
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@@ -221,77 +267,16 @@ const summary = JSON.parse(result);
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}
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```
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### Queue File Schema (Solution-Level)
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```json
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{
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"id": "QUE-20251227-143000",
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"status": "active",
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"solutions": [
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{
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"item_id": "S-1",
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"issue_id": "ISS-20251227-003",
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"solution_id": "SOL-ISS-20251227-003-1",
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"status": "pending",
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"execution_order": 1,
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"execution_group": "P1",
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"depends_on": [],
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"semantic_priority": 0.8,
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"files_touched": ["src/auth.ts", "src/utils.ts"],
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"task_count": 3
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},
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{
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"item_id": "S-2",
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"issue_id": "ISS-20251227-001",
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"solution_id": "SOL-ISS-20251227-001-1",
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"status": "pending",
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"execution_order": 2,
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"execution_group": "P1",
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"depends_on": [],
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"semantic_priority": 0.7,
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"files_touched": ["src/api.ts"],
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"task_count": 2
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},
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{
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"item_id": "S-3",
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"issue_id": "ISS-20251227-002",
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"solution_id": "SOL-ISS-20251227-002-1",
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"status": "pending",
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"execution_order": 3,
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"execution_group": "S2",
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"depends_on": ["S-1"],
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"semantic_priority": 0.5,
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"files_touched": ["src/auth.ts"],
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"task_count": 4
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}
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],
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"conflicts": [
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{
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"type": "file_conflict",
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"file": "src/auth.ts",
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"solutions": ["S-1", "S-3"],
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"resolution": "sequential",
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"resolution_order": ["S-1", "S-3"],
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"rationale": "S-1 creates auth module, S-3 extends it"
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}
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],
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"execution_groups": [
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{ "id": "P1", "type": "parallel", "solutions": ["S-1", "S-2"] },
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{ "id": "S2", "type": "sequential", "solutions": ["S-3"] }
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]
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}
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```
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**Note**: Queue file schema is produced by `issue-queue-agent`. See agent documentation for details.
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## Error Handling
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| Error | Resolution |
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|-------|------------|
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| No bound solutions | Display message, suggest /issue:plan |
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| Circular dependency | List cycles, abort queue formation |
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| Unresolved conflicts | Agent resolves using ordering rules |
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| Invalid task reference | Skip and warn |
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| High-severity conflict | Return `clarifications`, prompt user decision |
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| User cancels clarification | Abort queue formation |
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| **index.json not updated** | Auto-fix: Set active_queue_id to new queue |
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| **Wrong status value** | Auto-fix: Convert non-pending status to "pending" |
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| **No entry points (all have deps)** | Auto-fix: Clear depends_on for first item |
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| **Queue file missing solutions** | Abort with error, agent must regenerate |
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## Quality Checklist
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@@ -302,7 +287,7 @@ Before completing, verify:
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- [ ] Queue JSON written to `queues/{queue-id}.json`
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- [ ] Index updated in `queues/index.json` with `active_queue_id`
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- [ ] No circular dependencies in solution DAG
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- [ ] File conflicts resolved with rationale
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- [ ] All conflicts resolved (auto or via user clarification)
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- [ ] Parallel groups have no file overlaps
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- [ ] Issue statuses updated to `queued`
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@@ -311,3 +296,4 @@ Before completing, verify:
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- `/issue:plan` - Plan issues and bind solutions
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- `/issue:execute` - Execute queue with codex
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- `ccw issue queue list` - View current queue
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- `ccw issue update --from-queue [queue-id]` - Sync issue statuses from queue
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Reference in New Issue
Block a user