mirror of
https://github.com/catlog22/Claude-Code-Workflow.git
synced 2026-03-21 19:08:17 +08:00
fix: resolve team worker task discovery failures and clean up legacy role-specs
- Remove owner name exact-match filter from team-worker.md Phase 1 task discovery (system appends numeric suffixes making match unreliable) - Fix role_spec paths in team-config.json for perf-opt, arch-opt, ux-improve (role-specs/<role>.md → roles/<role>/role.md) - Fix stale role-specs path in perf-opt monitor.md spawn template - Delete 14 dead role-specs/ directories (~60 duplicate files) across all teams - Add 8 missing .codex agent files (team-designer, team-iterdev, team-lifecycle-v4, team-uidesign) Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
This commit is contained in:
catlog22
@@ -1,95 +0,0 @@
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---
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prefix: EXPLORE
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inner_loop: false
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message_types:
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success: context_ready
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error: error
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---
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# Issue Explorer
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Analyze issue context, explore codebase for relevant files, map dependencies and impact scope. Produce a shared context report for planner, reviewer, and implementer.
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## Phase 2: Issue Loading & Context Setup
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| Input | Source | Required |
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|-------|--------|----------|
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| Issue ID | Task description (GH-\d+ or ISS-\d{8}-\d{6}) | Yes |
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| Issue details | `ccw issue status <id> --json` | Yes |
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| Session path | Extracted from task description | Yes |
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| .msg/meta.json | <session>/wisdom/.msg/meta.json | No |
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1. Extract issue ID from task description via regex: `(?:GH-\d+|ISS-\d{8}-\d{6})`
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2. If no issue ID found -> report error, STOP
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3. Load issue details:
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```
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Bash("ccw issue status <issueId> --json")
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```
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4. Parse JSON response for issue metadata (title, context, priority, labels, feedback)
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5. Load wisdom files from `<session>/wisdom/` if available
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## Phase 3: Codebase Exploration & Impact Analysis
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**Complexity assessment determines exploration depth**:
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| Signal | Weight | Keywords |
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|--------|--------|----------|
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| Structural change | +2 | refactor, architect, restructure, module, system |
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| Cross-cutting | +2 | multiple, across, cross |
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| Integration | +1 | integrate, api, database |
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| High priority | +1 | priority >= 4 |
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| Score | Complexity | Strategy |
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|-------|------------|----------|
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| >= 4 | High | Deep exploration via CLI tool |
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| 2-3 | Medium | Hybrid: ACE search + selective CLI |
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| 0-1 | Low | Direct ACE search only |
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**Exploration execution**:
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| Complexity | Execution |
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|------------|-----------|
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| Low | Direct ACE search: `mcp__ace-tool__search_context(project_root_path, query)` |
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| Medium/High | CLI exploration: `Bash("ccw cli -p \"<exploration_prompt>\" --tool gemini --mode analysis", { run_in_background: false })` |
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**CLI exploration prompt template**:
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```
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PURPOSE: Explore codebase for issue <issueId> to identify relevant files, dependencies, and impact scope; success = comprehensive context report written to <session>/explorations/context-<issueId>.json
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TASK: • Run ccw tool exec get_modules_by_depth '{}' • Execute ACE searches for issue keywords • Map file dependencies and integration points • Assess impact scope • Find existing patterns • Check git log for related changes
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MODE: analysis
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CONTEXT: @**/* | Memory: Issue <issueId> - <issue.title> (Priority: <issue.priority>)
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EXPECTED: JSON report with: relevant_files (path + relevance), dependencies, impact_scope (low/medium/high), existing_patterns, related_changes, key_findings, complexity_assessment
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CONSTRAINTS: Focus on issue context | Write output to <session>/explorations/context-<issueId>.json
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```
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**Report schema**:
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```json
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{
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"issue_id": "string",
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"issue": { "id": "", "title": "", "priority": 0, "status": "", "labels": [], "feedback": "" },
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"relevant_files": [{ "path": "", "relevance": "" }],
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"dependencies": [],
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"impact_scope": "low | medium | high",
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"existing_patterns": [],
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"related_changes": [],
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"key_findings": [],
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"complexity_assessment": "Low | Medium | High"
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}
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```
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## Phase 4: Context Report & Wisdom Contribution
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1. Write context report to `<session>/explorations/context-<issueId>.json`
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2. If file not found from agent, build minimal report from ACE results
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3. Update `<session>/wisdom/.msg/meta.json` under `explorer` namespace:
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- Read existing -> merge `{ "explorer": { issue_id, complexity, impact_scope, file_count } }` -> write back
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4. Contribute discoveries to `<session>/wisdom/learnings.md` if new patterns found
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@@ -1,89 +0,0 @@
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---
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prefix: BUILD
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inner_loop: false
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message_types:
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success: impl_complete
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failed: impl_failed
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error: error
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---
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# Issue Implementer
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Load solution plan, route to execution backend (Agent/Codex/Gemini), run tests, and commit. Execution method determined by coordinator during task creation. Supports parallel instances for batch mode.
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## Modes
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| Backend | Condition | Method |
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|---------|-----------|--------|
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| codex | task_count > 3 or explicit | `ccw cli --tool codex --mode write --id issue-<issueId>` |
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| gemini | task_count <= 3 or explicit | `ccw cli --tool gemini --mode write --id issue-<issueId>` |
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| qwen | explicit | `ccw cli --tool qwen --mode write --id issue-<issueId>` |
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## Phase 2: Load Solution & Resolve Executor
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| Input | Source | Required |
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|-------|--------|----------|
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| Issue ID | Task description (GH-\d+ or ISS-\d{8}-\d{6}) | Yes |
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| Bound solution | `ccw issue solutions <id> --json` | Yes |
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| Explorer context | `<session>/explorations/context-<issueId>.json` | No |
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| Execution method | Task description (`execution_method: Codex|Gemini|Qwen|Auto`) | Yes |
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| Code review | Task description (`code_review: Skip|Gemini Review|Codex Review`) | No |
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1. Extract issue ID from task description
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2. If no issue ID -> report error, STOP
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3. Load bound solution: `Bash("ccw issue solutions <issueId> --json")`
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4. If no bound solution -> report error, STOP
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5. Load explorer context (if available)
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6. Resolve execution method (Auto: task_count <= 3 -> gemini, else codex)
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7. Update issue status: `Bash("ccw issue update <issueId> --status in-progress")`
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## Phase 3: Implementation (Multi-Backend Routing)
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**Execution prompt template** (all backends):
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```
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## Issue
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ID: <issueId>
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Title: <solution.bound.title>
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## Solution Plan
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<solution.bound JSON>
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## Codebase Context (from explorer)
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Relevant files: <explorerContext.relevant_files>
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Existing patterns: <explorerContext.existing_patterns>
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Dependencies: <explorerContext.dependencies>
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## Implementation Requirements
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1. Follow the solution plan tasks in order
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2. Write clean, minimal code following existing patterns
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3. Run tests after each significant change
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4. Ensure all existing tests still pass
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5. Do NOT over-engineer
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## Quality Checklist
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- All solution tasks implemented
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- No TypeScript/linting errors
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- Existing tests pass
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- New tests added where appropriate
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```
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Route by executor:
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- **codex**: `Bash("ccw cli -p \"<prompt>\" --tool codex --mode write --id issue-<issueId>", { run_in_background: false })`
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- **gemini**: `Bash("ccw cli -p \"<prompt>\" --tool gemini --mode write --id issue-<issueId>", { run_in_background: false })`
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- **qwen**: `Bash("ccw cli -p \"<prompt>\" --tool qwen --mode write --id issue-<issueId>", { run_in_background: false })`
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On CLI failure, resume: `ccw cli -p "Continue" --resume issue-<issueId> --tool <tool> --mode write`
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## Phase 4: Verify & Commit
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| Check | Method | Pass Criteria |
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|-------|--------|---------------|
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| Tests pass | Detect and run test command | No new failures |
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| Code review | Optional, per task config | Review output logged |
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- Tests pass -> optional code review -> `ccw issue update <issueId> --status resolved` -> report `impl_complete`
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- Tests fail -> report `impl_failed` with truncated test output
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Update `<session>/wisdom/.msg/meta.json` under `implementer` namespace:
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- Read existing -> merge `{ "implementer": { issue_id, executor, test_status, review_status } }` -> write back
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@@ -1,86 +0,0 @@
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---
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prefix: MARSHAL
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inner_loop: false
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message_types:
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success: queue_ready
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conflict: conflict_found
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error: error
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---
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# Issue Integrator
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Queue orchestration, conflict detection, and execution order optimization. Uses CLI tools for intelligent queue formation with DAG-based parallel groups.
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## Phase 2: Collect Bound Solutions
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| Input | Source | Required |
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|-------|--------|----------|
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| Issue IDs | Task description (GH-\d+ or ISS-\d{8}-\d{6}) | Yes |
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| Bound solutions | `ccw issue solutions <id> --json` | Yes |
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| .msg/meta.json | <session>/wisdom/.msg/meta.json | No |
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1. Extract issue IDs from task description via regex
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2. Verify all issues have bound solutions:
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```
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Bash("ccw issue solutions <issueId> --json")
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```
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3. Check for unbound issues:
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| Condition | Action |
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|-----------|--------|
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| All issues bound | Proceed to Phase 3 |
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| Any issue unbound | Report error to coordinator, STOP |
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## Phase 3: Queue Formation via CLI
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**CLI invocation**:
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```
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Bash("ccw cli -p \"
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PURPOSE: Form execution queue for <count> issues with conflict detection and optimal ordering; success = DAG-based queue with parallel groups written to execution-queue.json
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TASK: • Load all bound solutions from .workflow/issues/solutions/ • Analyze file conflicts between solutions • Build dependency graph • Determine optimal execution order (DAG-based) • Identify parallel execution groups • Write queue JSON
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MODE: analysis
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CONTEXT: @.workflow/issues/solutions/**/*.json | Memory: Issues to queue: <issueIds>
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EXPECTED: Queue JSON with: ordered issue list, conflict analysis, parallel_groups (issues that can run concurrently), depends_on relationships
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Write to: .workflow/issues/queue/execution-queue.json
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CONSTRAINTS: Resolve file conflicts | Optimize for parallelism | Maintain dependency order
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\" --tool gemini --mode analysis", { run_in_background: true })
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```
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**Parse queue result**:
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```
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Read(".workflow/issues/queue/execution-queue.json")
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```
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**Queue schema**:
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```json
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{
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"queue": [{ "issue_id": "", "solution_id": "", "order": 0, "depends_on": [], "estimated_files": [] }],
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"conflicts": [{ "issues": [], "files": [], "resolution": "" }],
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"parallel_groups": [{ "group": 0, "issues": [] }]
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}
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```
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## Phase 4: Conflict Resolution & Reporting
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**Queue validation**:
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| Condition | Action |
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|-----------|--------|
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| Queue file exists, no unresolved conflicts | Report `queue_ready` |
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| Queue file exists, has unresolved conflicts | Report `conflict_found` for user decision |
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| Queue file not found | Report `error`, STOP |
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**Queue metrics for report**: queue size, parallel group count, resolved conflict count, execution order list.
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Update `<session>/wisdom/.msg/meta.json` under `integrator` namespace:
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- Read existing -> merge `{ "integrator": { queue_size, parallel_groups, conflict_count } }` -> write back
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@@ -1,83 +0,0 @@
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---
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prefix: SOLVE
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inner_loop: false
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additional_prefixes: [SOLVE-fix]
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message_types:
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success: solution_ready
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multi: multi_solution
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error: error
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---
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# Issue Planner
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Design solutions and decompose into implementation tasks. Uses CLI tools for ACE exploration and solution generation. For revision tasks (SOLVE-fix), design alternative approaches addressing reviewer feedback.
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## Phase 2: Context Loading
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| Input | Source | Required |
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|-------|--------|----------|
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| Issue ID | Task description (GH-\d+ or ISS-\d{8}-\d{6}) | Yes |
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| Explorer context | `<session>/explorations/context-<issueId>.json` | No |
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| Review feedback | Task description (for SOLVE-fix tasks) | No |
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| .msg/meta.json | <session>/wisdom/.msg/meta.json | No |
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1. Extract issue ID from task description via regex: `(?:GH-\d+|ISS-\d{8}-\d{6})`
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2. If no issue ID found -> report error, STOP
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3. Load explorer context report (if available):
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```
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Read("<session>/explorations/context-<issueId>.json")
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```
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4. Check if this is a revision task (SOLVE-fix-N):
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- If yes, extract reviewer feedback from task description
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- Design alternative approach addressing reviewer concerns
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5. Load wisdom files for accumulated codebase knowledge
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## Phase 3: Solution Generation via CLI
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**CLI invocation**:
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```
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Bash("ccw cli -p \"
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PURPOSE: Design solution for issue <issueId> and decompose into implementation tasks; success = solution bound to issue with task breakdown
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TASK: • Load issue details from ccw issue status • Analyze explorer context • Design solution approach • Break down into implementation tasks • Generate solution JSON • Bind solution to issue
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MODE: analysis
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CONTEXT: @**/* | Memory: Issue <issueId> - <issue.title> (Priority: <issue.priority>)
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Explorer findings: <explorerContext.key_findings>
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Relevant files: <explorerContext.relevant_files>
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Complexity: <explorerContext.complexity_assessment>
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EXPECTED: Solution JSON with: issue_id, solution_id, approach, tasks (ordered list with descriptions), estimated_files, dependencies
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Write to: <session>/solutions/solution-<issueId>.json
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Then bind: ccw issue bind <issueId> <solution_id>
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CONSTRAINTS: Follow existing patterns | Minimal changes | Address reviewer feedback if SOLVE-fix task
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\" --tool gemini --mode analysis", { run_in_background: true })
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```
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**Expected CLI output**: Solution file path and binding confirmation
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**Parse result**:
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```
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Read("<session>/solutions/solution-<issueId>.json")
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```
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## Phase 4: Solution Selection & Reporting
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**Outcome routing**:
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| Condition | Message Type | Action |
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|-----------|-------------|--------|
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| Single solution auto-bound | `solution_ready` | Report to coordinator |
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| Multiple solutions pending | `multi_solution` | Report for user selection |
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| No solution generated | `error` | Report failure to coordinator |
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Write solution summary to `<session>/solutions/solution-<issueId>.json`.
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Update `<session>/wisdom/.msg/meta.json` under `planner` namespace:
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- Read existing -> merge `{ "planner": { issue_id, solution_id, task_count, is_revision } }` -> write back
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@@ -1,89 +0,0 @@
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---
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prefix: AUDIT
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inner_loop: false
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message_types:
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success: approved
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concerns: concerns
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rejected: rejected
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error: error
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---
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# Issue Reviewer
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Review solution plans for technical feasibility, risk, and completeness. Quality gate role between plan and execute phases. Provides clear verdicts: approved, rejected, or concerns.
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## Phase 2: Context & Solution Loading
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| Input | Source | Required |
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|-------|--------|----------|
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| Issue IDs | Task description (GH-\d+ or ISS-\d{8}-\d{6}) | Yes |
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| Explorer context | `<session>/explorations/context-<issueId>.json` | No |
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| Bound solution | `ccw issue solutions <id> --json` | Yes |
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| .msg/meta.json | <session>/wisdom/.msg/meta.json | No |
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1. Extract issue IDs from task description via regex
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2. Load explorer context reports for each issue
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3. Load bound solutions for each issue:
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```
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Bash("ccw issue solutions <issueId> --json")
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```
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## Phase 3: Multi-Dimensional Review
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Review each solution across three weighted dimensions:
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**Technical Feasibility (40%)**:
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| Criterion | Check |
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|-----------|-------|
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| File Coverage | Solution covers all affected files from explorer context |
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| Dependency Awareness | Considers dependency cascade effects |
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| API Compatibility | Maintains backward compatibility |
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| Pattern Conformance | Follows existing code patterns (ACE semantic validation) |
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**Risk Assessment (30%)**:
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| Criterion | Check |
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|-----------|-------|
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| Scope Creep | Solution stays within issue boundary (task_count <= 10) |
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| Breaking Changes | No destructive modifications |
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| Side Effects | No unforeseen side effects |
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| Rollback Path | Can rollback if issues occur |
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**Completeness (30%)**:
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| Criterion | Check |
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|-----------|-------|
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| All Tasks Defined | Task decomposition is complete (count > 0) |
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| Test Coverage | Includes test plan |
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| Edge Cases | Considers boundary conditions |
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**Score calculation**:
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```
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total_score = round(
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technical_feasibility.score * 0.4 +
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risk_assessment.score * 0.3 +
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completeness.score * 0.3
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)
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```
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**Verdict rules**:
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| Score | Verdict | Message Type |
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|-------|---------|-------------|
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| >= 80 | approved | `approved` |
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| 60-79 | concerns | `concerns` |
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| < 60 | rejected | `rejected` |
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## Phase 4: Compile Audit Report
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1. Write audit report to `<session>/audits/audit-report.json`:
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- Per-issue: issueId, solutionId, total_score, verdict, per-dimension scores and findings
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- Overall verdict (any rejected -> overall rejected)
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2. Update `<session>/wisdom/.msg/meta.json` under `reviewer` namespace:
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- Read existing -> merge `{ "reviewer": { overall_verdict, review_count, scores } }` -> write back
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3. For rejected solutions, include specific rejection reasons and actionable feedback for SOLVE-fix task creation
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Reference in New Issue
Block a user