mirror of
https://github.com/catlog22/Claude-Code-Workflow.git
synced 2026-03-06 16:31:12 +08:00
feat: Add coordinator commands and role specifications for UI design team
- Implemented the 'monitor' command for coordinator role to handle monitoring events, task completion, and pipeline management. - Created role specifications for the coordinator, detailing responsibilities, command execution protocols, and session management. - Added role specifications for the analyst, discussant, explorer, and synthesizer in the ultra-analyze skill, defining their context loading, analysis, and synthesis processes.
This commit is contained in:
catlog22
70
.claude/skills/team-tech-debt/role-specs/assessor.md
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70
.claude/skills/team-tech-debt/role-specs/assessor.md
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---
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prefix: TDEVAL
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inner_loop: false
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message_types:
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success: assessment_complete
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error: error
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---
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# Tech Debt Assessor
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Quantitative evaluator for tech debt items. Score each debt item on business impact (1-5) and fix cost (1-5), classify into priority quadrants, produce priority-matrix.json.
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## Phase 2: Load Debt Inventory
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| Input | Source | Required |
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|-------|--------|----------|
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| Session path | task description (regex: `session:\s*(.+)`) | Yes |
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| .msg/meta.json | <session>/.msg/meta.json | Yes |
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| Debt inventory | meta.json:debt_inventory OR <session>/scan/debt-inventory.json | Yes |
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1. Extract session path from task description
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2. Read .msg/meta.json for team context
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3. Load debt_inventory from shared memory or fallback to debt-inventory.json file
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4. If debt_inventory is empty -> report empty assessment and exit
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## Phase 3: Evaluate Each Item
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**Strategy selection**:
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| Item Count | Strategy |
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|------------|----------|
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| <= 10 | Heuristic: severity-based impact + effort-based cost |
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| 11-50 | CLI batch: single gemini analysis call |
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| > 50 | CLI chunked: batches of 25 items |
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**Impact Score Mapping** (heuristic):
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| Severity | Impact Score |
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|----------|-------------|
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| critical | 5 |
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| high | 4 |
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| medium | 3 |
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| low | 1 |
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**Cost Score Mapping** (heuristic):
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| Estimated Effort | Cost Score |
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|------------------|------------|
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| small | 1 |
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| medium | 3 |
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| large | 5 |
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| unknown | 3 |
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**Priority Quadrant Classification**:
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| Impact | Cost | Quadrant |
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|--------|------|----------|
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| >= 4 | <= 2 | quick-win |
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| >= 4 | >= 3 | strategic |
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| <= 3 | <= 2 | backlog |
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| <= 3 | >= 3 | defer |
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For CLI mode, prompt gemini with full debt summary requesting JSON array of `{id, impact_score, cost_score, risk_if_unfixed, priority_quadrant}`. Unevaluated items fall back to heuristic scoring.
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## Phase 4: Generate Priority Matrix
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1. Build matrix structure: evaluation_date, total_items, by_quadrant (grouped), summary (counts per quadrant)
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2. Sort within each quadrant by impact_score descending
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3. Write `<session>/assessment/priority-matrix.json`
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4. Update .msg/meta.json with `priority_matrix` summary and evaluated `debt_inventory`
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68
.claude/skills/team-tech-debt/role-specs/executor.md
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68
.claude/skills/team-tech-debt/role-specs/executor.md
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---
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prefix: TDFIX
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inner_loop: true
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message_types:
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success: fix_complete
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progress: fix_progress
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error: error
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---
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# Tech Debt Executor
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Debt cleanup executor. Apply remediation plan actions in worktree: refactor code, update dependencies, add tests, add documentation. Batch-delegate to code-developer subagent, self-validate after each batch.
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## Phase 2: Load Remediation Plan
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| Input | Source | Required |
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|-------|--------|----------|
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| Session path | task description (regex: `session:\s*(.+)`) | Yes |
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| .msg/meta.json | <session>/.msg/meta.json | Yes |
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| Remediation plan | <session>/plan/remediation-plan.json | Yes |
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| Worktree info | meta.json:worktree.path, worktree.branch | Yes |
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| Context accumulator | From prior TDFIX tasks (inner loop) | Yes (inner loop) |
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1. Extract session path from task description
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2. Read .msg/meta.json for worktree path and branch
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3. Read remediation-plan.json, extract all actions from plan phases
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4. Group actions by type: refactor, restructure, add-tests, update-deps, add-docs
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5. Split large groups (> 10 items) into sub-batches of 10
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6. For inner loop (fix-verify cycle): load context_accumulator from prior TDFIX tasks, parse review/validation feedback for specific issues
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**Batch order**: refactor -> update-deps -> add-tests -> add-docs -> restructure
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## Phase 3: Execute Fixes
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For each batch, delegate to `code-developer` subagent (synchronous, `run_in_background: false`):
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**Worktree constraint**: ALL file operations and commands must execute within worktree path. Use `cd "<worktree-path>" && ...` prefix for all Bash commands.
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**Per-batch delegation**:
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- Provide batch type prompt (refactor/update-deps/add-tests/add-docs/restructure)
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- List all items with file paths, descriptions, and fix steps
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- Enforce: read files before modifying, minimal changes, backward compatibility, no new features, no suppressions
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**Fix Results Tracking**:
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| Field | Description |
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|-------|-------------|
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| items_fixed | Count of successfully fixed items |
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| items_failed | Count of failed items |
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| items_remaining | Remaining items count |
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| batches_completed | Completed batch count |
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| files_modified | Array of modified file paths |
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| errors | Array of error messages |
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After each batch, verify file modifications via `git diff --name-only` in worktree.
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## Phase 4: Self-Validation
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All commands in worktree:
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| Check | Command | Pass Criteria |
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|-------|---------|---------------|
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| Syntax | `tsc --noEmit` or `python -m py_compile` | No new errors |
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| Lint | `eslint --no-error-on-unmatched-pattern` | No new errors |
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Write `<session>/fixes/fix-log.json` with fix results. Update .msg/meta.json with `fix_results`.
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Append to context_accumulator for next TDFIX task (inner loop): files modified, fixes applied, validation results, discovered caveats.
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71
.claude/skills/team-tech-debt/role-specs/planner.md
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71
.claude/skills/team-tech-debt/role-specs/planner.md
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---
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prefix: TDPLAN
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inner_loop: false
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message_types:
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success: plan_ready
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revision: plan_revision
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error: error
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---
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# Tech Debt Planner
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Remediation plan designer. Create phased remediation plan from priority matrix: Phase 1 quick-wins (immediate), Phase 2 systematic (medium-term), Phase 3 prevention (long-term). Produce remediation-plan.md.
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## Phase 2: Load Assessment Data
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| Input | Source | Required |
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|-------|--------|----------|
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| Session path | task description (regex: `session:\s*(.+)`) | Yes |
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| .msg/meta.json | <session>/.msg/meta.json | Yes |
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| Priority matrix | <session>/assessment/priority-matrix.json | Yes |
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1. Extract session path from task description
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2. Read .msg/meta.json for debt_inventory
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3. Read priority-matrix.json for quadrant groupings
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4. Group items: quickWins (quick-win), strategic (strategic), backlog (backlog), deferred (defer)
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## Phase 3: Create Remediation Plan
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**Strategy selection**:
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| Item Count (quick-win + strategic) | Strategy |
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|------------------------------------|----------|
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| <= 5 | Inline: generate steps from item data |
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| > 5 | CLI-assisted: gemini generates detailed remediation steps |
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**3-Phase Plan Structure**:
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| Phase | Name | Source Items | Focus |
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|-------|------|-------------|-------|
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| 1 | Quick Wins | quick-win quadrant | High impact, low cost -- immediate execution |
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| 2 | Systematic | strategic quadrant | High impact, high cost -- structured refactoring |
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| 3 | Prevention | Generated from dimension patterns | Long-term prevention mechanisms |
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**Action Type Mapping**:
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| Dimension | Action Type |
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|-----------|-------------|
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| code | refactor |
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| architecture | restructure |
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| testing | add-tests |
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| dependency | update-deps |
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| documentation | add-docs |
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**Prevention Actions** (generated when dimension has >= 3 items):
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| Dimension | Prevention Action |
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|-----------|-------------------|
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| code | Add linting rules for complexity thresholds and code smell detection |
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| architecture | Introduce module boundary checks in CI pipeline |
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| testing | Set minimum coverage thresholds in CI and add pre-commit test hooks |
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| dependency | Configure automated dependency update bot (Renovate/Dependabot) |
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| documentation | Add JSDoc/docstring enforcement in linting rules |
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For CLI-assisted mode, prompt gemini with debt summary requesting specific fix steps per item, grouped into phases, with dependencies and estimated time.
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## Phase 4: Validate & Save
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1. Calculate validation metrics: total_actions, total_effort, files_affected, has_quick_wins, has_prevention
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2. Write `<session>/plan/remediation-plan.md` (markdown with per-item checklists)
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3. Write `<session>/plan/remediation-plan.json` (machine-readable)
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4. Update .msg/meta.json with `remediation_plan` summary
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84
.claude/skills/team-tech-debt/role-specs/scanner.md
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84
.claude/skills/team-tech-debt/role-specs/scanner.md
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---
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prefix: TDSCAN
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inner_loop: false
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subagents: []
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message_types:
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success: scan_complete
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error: error
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info: debt_items_found
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---
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# Tech Debt Scanner
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Multi-dimension tech debt scanner. Scan codebase across 5 dimensions (code, architecture, testing, dependency, documentation), produce structured debt inventory with severity rankings.
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## Phase 2: Context & Environment Detection
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| Input | Source | Required |
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|-------|--------|----------|
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| Scan scope | task description (regex: `scope:\s*(.+)`) | No (default: `**/*`) |
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| Session path | task description (regex: `session:\s*(.+)`) | Yes |
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| .msg/meta.json | <session>/.msg/meta.json | Yes |
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1. Extract session path and scan scope from task description
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2. Read .msg/meta.json for team context
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3. Detect project type and framework:
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| Signal File | Project Type |
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|-------------|-------------|
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| package.json + React/Vue/Angular | Frontend Node |
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| package.json + Express/Fastify/NestJS | Backend Node |
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| pyproject.toml / requirements.txt | Python |
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| go.mod | Go |
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| No detection | Generic |
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4. Determine scan dimensions (default: code, architecture, testing, dependency, documentation)
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5. Detect perspectives from task description:
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| Condition | Perspective |
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|-----------|-------------|
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| `security\|auth\|inject\|xss` | security |
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| `performance\|speed\|optimize` | performance |
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| `quality\|clean\|maintain\|debt` | code-quality |
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| `architect\|pattern\|structure` | architecture |
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| Default | code-quality + architecture |
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6. Assess complexity:
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| Score | Complexity | Strategy |
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|-------|------------|----------|
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| >= 4 | High | Triple Fan-out: subagent explore + CLI 5 dimensions + multi-perspective Gemini |
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| 2-3 | Medium | Dual Fan-out: subagent explore + CLI 3 dimensions |
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| 0-1 | Low | Inline: ACE search + Grep |
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## Phase 3: Multi-Dimension Scan
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**Low Complexity** (inline):
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- Use `mcp__ace-tool__search_context` for code smells, TODO/FIXME, deprecated APIs, complex functions, dead code, missing tests
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- Classify findings into dimensions
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**Medium/High Complexity** (Fan-out):
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- Fan-out A: Subagent exploration (structure, patterns, dependencies angles) via `cli-explore-agent`
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- Fan-out B: CLI dimension analysis (parallel gemini per dimension -- code, architecture, testing, dependency, documentation)
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- Fan-out C (High only): Multi-perspective Gemini analysis (security, performance, code-quality, architecture)
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- Fan-in: Merge results, cross-deduplicate by file:line, boost severity for multi-source findings
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**Standardize each finding**:
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| Field | Description |
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|-------|-------------|
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| `id` | `TD-NNN` (sequential) |
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| `dimension` | code, architecture, testing, dependency, documentation |
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| `severity` | critical, high, medium, low |
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| `file` | File path |
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| `line` | Line number |
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| `description` | Issue description |
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| `suggestion` | Fix suggestion |
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| `estimated_effort` | small, medium, large, unknown |
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## Phase 4: Aggregate & Save
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1. Deduplicate findings across Fan-out layers (file:line key), merge cross-references
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2. Sort by severity (cross-referenced items boosted)
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3. Write `<session>/scan/debt-inventory.json` with scan_date, dimensions, total_items, by_dimension, by_severity, items
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4. Update .msg/meta.json with `debt_inventory` array and `debt_score_before` count
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70
.claude/skills/team-tech-debt/role-specs/validator.md
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70
.claude/skills/team-tech-debt/role-specs/validator.md
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@@ -0,0 +1,70 @@
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---
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prefix: TDVAL
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inner_loop: false
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message_types:
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success: validation_complete
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error: error
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fix: regression_found
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---
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# Tech Debt Validator
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Cleanup result validator. Run test suite, type checks, lint checks, and quality analysis to verify debt cleanup introduced no regressions. Compare before/after debt scores, produce validation-report.json.
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## Phase 2: Load Context
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| Input | Source | Required |
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|-------|--------|----------|
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| Session path | task description (regex: `session:\s*(.+)`) | Yes |
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| .msg/meta.json | <session>/.msg/meta.json | Yes |
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| Fix log | <session>/fixes/fix-log.json | No |
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1. Extract session path from task description
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2. Read .msg/meta.json for: worktree.path, debt_inventory, fix_results, debt_score_before
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3. Determine command prefix: `cd "<worktree-path>" && ` if worktree exists
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4. Read fix-log.json for modified files list
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5. Detect available validation tools in worktree:
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| Signal | Tool | Method |
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|--------|------|--------|
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| package.json + npm | npm test | Test suite |
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| pytest available | python -m pytest | Test suite |
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| npx tsc available | npx tsc --noEmit | Type check |
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| npx eslint available | npx eslint | Lint check |
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## Phase 3: Run Validation Checks
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Execute 4-layer validation (all commands in worktree):
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**1. Test Suite**:
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- Run `npm test` or `python -m pytest` in worktree
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- PASS if no FAIL/error/failed keywords; FAIL with regression count otherwise
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- Skip with "no-tests" if no test runner available
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**2. Type Check**:
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- Run `npx tsc --noEmit` in worktree
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- Count `error TS` occurrences for error count
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**3. Lint Check**:
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- Run `npx eslint --no-error-on-unmatched-pattern <modified-files>` in worktree
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- Count error occurrences
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**4. Quality Analysis** (optional, when > 5 modified files):
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- Use gemini CLI to compare code quality before/after
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- Assess complexity, duplication, naming quality improvements
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**Debt Score Calculation**:
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- debt_score_after = debt items NOT in modified files (remaining unfixed items)
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- improvement_percentage = ((before - after) / before) * 100
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**Auto-fix attempt** (when total_regressions <= 3):
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- Spawn code-developer subagent to fix regressions in worktree
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- Constraints: fix only regressions, preserve debt cleanup changes, no suppressions
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- Re-run checks after fix attempt
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## Phase 4: Compare & Report
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1. Calculate: total_regressions = test_regressions + type_errors + lint_errors; passed = (total_regressions === 0)
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2. Write `<session>/validation/validation-report.json` with: validation_date, passed, regressions, checks (per-check status), debt_score_before, debt_score_after, improvement_percentage
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3. Update .msg/meta.json with `validation_results` and `debt_score_after`
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4. Select message type: `validation_complete` if passed, `regression_found` if not
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