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https://github.com/catlog22/Claude-Code-Workflow.git
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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.
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catlog22
75
.claude/skills/team-review/role-specs/fixer.md
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75
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---
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prefix: FIX
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inner_loop: true
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message_types:
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success: fix_complete
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error: fix_failed
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---
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# Code Fixer
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Fix code based on reviewed findings. Load manifest, plan fix groups, apply with rollback-on-failure, verify. Code-generation role -- modifies source files.
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## Phase 2: Context & Scope Resolution
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| Input | Source | Required |
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|-------|--------|----------|
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| Task description | From task subject/description | Yes |
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| Session path | Extracted from task description | Yes |
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| Fix manifest | <session>/fix/fix-manifest.json | Yes |
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| Review report | <session>/review/review-report.json | Yes |
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| .msg/meta.json | <session>/.msg/meta.json | No |
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1. Extract session path, input path from task description
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2. Load manifest (scope, source report path) and review report (findings with enrichment)
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3. Filter fixable findings: severity in scope AND fix_strategy !== 'skip'
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4. If 0 fixable -> report complete immediately
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5. Detect quick path: findings <= 5 AND no cross-file dependencies
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6. Detect verification tools: tsc (tsconfig.json), eslint (package.json), jest (package.json), pytest (pyproject.toml), semgrep (semgrep available)
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7. Load wisdom files from `<session>/wisdom/`
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## Phase 3: Plan + Execute
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### 3A: Plan Fixes (deterministic, no CLI)
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1. Group findings by primary file
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2. Merge groups with cross-file dependencies (union-find)
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3. Topological sort within each group (respect fix_dependencies, append cycles at end)
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4. Sort groups by max severity (critical first)
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5. Determine execution path: quick_path (<=5 findings, <=1 group) or standard
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6. Write `<session>/fix/fix-plan.json`: `{plan_id, quick_path, groups[{id, files[], findings[], max_severity}], execution_order[], total_findings, total_groups}`
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### 3B: Execute Fixes
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**Quick path**: Single code-developer agent for all findings.
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**Standard path**: One code-developer agent per group, in execution_order.
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Agent prompt includes: finding list (dependency-sorted), file contents (truncated 8K), critical rules:
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1. Apply each fix using Edit tool in order
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2. After each fix, run related tests
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3. Tests PASS -> finding is "fixed"
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4. Tests FAIL -> `git checkout -- {file}` -> mark "failed" -> continue
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5. No retry on failure. Rollback and move on
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6. If finding depends on previously failed finding -> mark "skipped"
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Agent returns JSON: `{results:[{id, status: fixed|failed|skipped, file, error?}]}`
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Fallback: check git diff per file if no structured output.
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Write `<session>/fix/execution-results.json`: `{fixed[], failed[], skipped[]}`
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## Phase 4: Post-Fix Verification
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1. Run available verification tools on modified files:
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| Tool | Command | Pass Criteria |
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|------|---------|---------------|
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| tsc | `npx tsc --noEmit` | 0 errors |
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| eslint | `npx eslint <files>` | 0 errors |
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| jest | `npx jest --passWithNoTests` | Tests pass |
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| pytest | `pytest --tb=short` | Tests pass |
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| semgrep | `semgrep --config auto <files> --json` | 0 results |
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2. If verification fails critically -> rollback last batch
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3. Write `<session>/fix/verify-results.json`
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4. Generate `<session>/fix/fix-summary.json`: `{fix_id, fix_date, scope, total, fixed, failed, skipped, fix_rate, verification}`
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5. Generate `<session>/fix/fix-summary.md` (human-readable)
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6. Update `<session>/.msg/meta.json` with fix results
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7. Contribute discoveries to `<session>/wisdom/` files
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66
.claude/skills/team-review/role-specs/reviewer.md
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66
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---
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prefix: REV
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inner_loop: false
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message_types:
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success: review_complete
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error: error
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---
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# Finding Reviewer
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Deep analysis on scan findings: triage, root cause / impact / optimization enrichment via CLI fan-out, cross-correlation, and structured review report generation. Read-only -- never modifies source code.
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## Phase 2: Context & Triage
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| Input | Source | Required |
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|-------|--------|----------|
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| Task description | From task subject/description | Yes |
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| Session path | Extracted from task description | Yes |
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| Scan results | <session>/scan/scan-results.json | Yes |
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| .msg/meta.json | <session>/.msg/meta.json | No |
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1. Extract session path, input path, dimensions from task description
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2. Load scan results. If missing or empty -> report clean, complete immediately
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3. Load wisdom files from `<session>/wisdom/`
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4. Triage findings into two buckets:
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| Bucket | Criteria | Action |
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|--------|----------|--------|
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| deep_analysis | severity in [critical, high, medium], max 15, sorted critical-first | Enrich with root cause, impact, optimization |
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| pass_through | remaining (low, info, or overflow) | Include in report without enrichment |
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If deep_analysis empty -> skip Phase 3, go to Phase 4.
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## Phase 3: Deep Analysis (CLI Fan-out)
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Split deep_analysis into two domain groups, run parallel CLI agents:
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| Group | Dimensions | Focus |
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|-------|-----------|-------|
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| A | Security + Correctness | Root cause tracing, fix dependencies, blast radius |
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| B | Performance + Maintainability | Optimization approaches, refactor tradeoffs |
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If either group empty -> skip that agent.
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Build prompt per group requesting 6 enrichment fields per finding:
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- `root_cause`: `{description, related_findings[], is_symptom}`
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- `impact`: `{scope: low/medium/high, affected_files[], blast_radius}`
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- `optimization`: `{approach, alternative, tradeoff}`
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- `fix_strategy`: minimal / refactor / skip
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- `fix_complexity`: low / medium / high
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- `fix_dependencies`: finding IDs that must be fixed first
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Execute via `ccw cli --tool gemini --mode analysis --rule analysis-diagnose-bug-root-cause` (fallback: qwen -> codex). Parse JSON array responses, merge with originals (CLI-enriched replace originals, unenriched get defaults). Write `<session>/review/enriched-findings.json`.
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## Phase 4: Report Generation
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1. Combine enriched + pass_through findings
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2. Cross-correlate:
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- **Critical files**: file appears in >=2 dimensions -> list with finding_count, severities
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- **Root cause groups**: cluster findings sharing related_findings -> identify primary
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- **Optimization suggestions**: from root cause groups + standalone enriched findings
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3. Compute metrics: by_dimension, by_severity, dimension_severity_matrix, fixable_count, auto_fixable_count
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4. Write `<session>/review/review-report.json`: `{review_id, review_date, findings[], critical_files[], optimization_suggestions[], root_cause_groups[], summary}`
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5. Write `<session>/review/review-report.md`: Executive summary, metrics matrix (dimension x severity), critical/high findings table, critical files list, optimization suggestions, recommended fix scope
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6. Update `<session>/.msg/meta.json` with review summary
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7. Contribute discoveries to `<session>/wisdom/` files
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70
.claude/skills/team-review/role-specs/scanner.md
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70
.claude/skills/team-review/role-specs/scanner.md
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---
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prefix: SCAN
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inner_loop: false
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message_types:
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success: scan_complete
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error: error
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---
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# Code Scanner
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Toolchain + LLM semantic scan producing structured findings. Static analysis tools in parallel, then LLM for issues tools miss. Read-only -- never modifies source code. 4-dimension system: security (SEC), correctness (COR), performance (PRF), maintainability (MNT).
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## Phase 2: Context & Toolchain Detection
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| Input | Source | Required |
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|-------|--------|----------|
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| Task description | From task subject/description | Yes |
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| Session path | Extracted from task description | Yes |
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| .msg/meta.json | <session>/.msg/meta.json | No |
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1. Extract session path, target, dimensions, quick flag from task description
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2. Resolve target files (glob pattern or directory -> `**/*.{ts,tsx,js,jsx,py,go,java,rs}`)
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3. If no source files found -> report empty, complete task cleanly
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4. Detect toolchain availability:
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| Tool | Detection | Dimension |
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|------|-----------|-----------|
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| tsc | `tsconfig.json` exists | COR |
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| eslint | `.eslintrc*` or `eslint` in package.json | COR/MNT |
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| semgrep | `.semgrep.yml` exists | SEC |
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| ruff | `pyproject.toml` + ruff available | SEC/COR/MNT |
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| mypy | mypy available + `pyproject.toml` | COR |
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| npmAudit | `package-lock.json` exists | SEC |
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5. Load wisdom files from `<session>/wisdom/` if they exist
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## Phase 3: Scan Execution
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**Quick mode**: Single CLI call with analysis mode, max 20 findings, skip toolchain.
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**Standard mode** (sequential):
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### 3A: Toolchain Scan
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Run detected tools in parallel via Bash backgrounding. Each tool writes to `<session>/scan/tmp/<tool>.{json|txt}`. After `wait`, parse each output into normalized findings:
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- tsc: `file(line,col): error TSxxxx: msg` -> dimension=correctness, source=tool:tsc
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- eslint: JSON array -> severity 2=correctness/high, else=maintainability/medium
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- semgrep: `{results[]}` -> dimension=security, severity from extra.severity
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- ruff: `[{code,message,filename}]` -> S*=security, F*/B*=correctness, else=maintainability
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- mypy: `file:line: error: msg [code]` -> dimension=correctness
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- npm audit: `{vulnerabilities:{}}` -> dimension=security, category=dependency
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Write `<session>/scan/toolchain-findings.json`.
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### 3B: Semantic Scan (LLM via CLI)
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Build prompt with target file patterns, toolchain dedup summary, and per-dimension focus areas:
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- SEC: Business logic vulnerabilities, privilege escalation, sensitive data flow, auth bypass
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- COR: Logic errors, unhandled exception paths, state management bugs, race conditions
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- PRF: Algorithm complexity, N+1 queries, unnecessary sync, memory leaks, missing caching
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- MNT: Architectural coupling, abstraction leaks, convention violations, dead code
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Execute via `ccw cli --tool gemini --mode analysis --rule analysis-review-code-quality` (fallback: qwen -> codex). Parse JSON array response, validate required fields (dimension, title, location.file), enforce per-dimension limit (max 5 each), filter minimum severity (medium+). Write `<session>/scan/semantic-findings.json`.
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## Phase 4: Aggregate & Output
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1. Merge toolchain + semantic findings, deduplicate (same file + line + dimension = duplicate)
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2. Assign dimension-prefixed IDs: SEC-001, COR-001, PRF-001, MNT-001
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3. Write `<session>/scan/scan-results.json` with schema: `{scan_date, target, dimensions, quick_mode, total_findings, by_severity, by_dimension, findings[]}`
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4. Each finding: `{id, dimension, category, severity, title, description, location:{file,line}, source, suggested_fix, effort, confidence}`
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5. Update `<session>/.msg/meta.json` with scan summary (findings_count, by_severity, by_dimension)
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6. Contribute discoveries to `<session>/wisdom/` files
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