mirror of
https://github.com/catlog22/Claude-Code-Workflow.git
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bbdd1840de
- Introduced `document-standards.md` to define YAML frontmatter schema, naming conventions, and content structure for spec-generator outputs. - Created `quality-gates.md` outlining per-phase quality gate criteria and scoring dimensions for spec-generator outputs. - Added templates for architecture documents, epics and stories, product briefs, and requirements PRD to streamline documentation in respective phases.
84 lines
3.2 KiB
Markdown
84 lines
3.2 KiB
Markdown
---
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prefix: TDSCAN
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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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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: CLI explore + CLI 5 dimensions + multi-perspective Gemini |
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| 2-3 | Medium | Dual Fan-out: CLI 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: CLI exploration (structure, patterns, dependencies angles) via `ccw cli --tool gemini --mode analysis`
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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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