dev
307d2fd471
Adds the project-review workflow for code review independent of the git diff. The scope is parsed from the user instruction: 全面/整个项目 -> whole-project (score every source file), otherwise feature + target keyword (locate the code with semantic search + graph queries). - scoring_tools.py: score_review_func gains all_files=True to score every source file in the graph via store.get_all_files() - main.py: score_review_tool gains all_files param; registers the project_review MCP prompt (prompts 6->7) - prompts.py: project_review_prompt(scope, target) with whole-project and feature branches (fixed a precedence bug that truncated the feature text) - skills.py + skills/project-review/: new read-only project-review skill with shared checklists - .opencode/command/code-review-graph-project-review.md: slash command - tests: test_project_review.py (prompt rendering), TestProjectReviewPrompt, skill count assertions 5->6, all_files wiring checks - docs: prompts (6->7) + project-review entries across COMMANDS, CLAUDE, README (+localized), INDEX, architecture, LLM-OPTIMIZED-REFERENCE, CHANGELOG
83 lines
3.4 KiB
Markdown
83 lines
3.4 KiB
Markdown
# Unified Review — Generic Checklist
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Reference for the Layer-1 chain decomposition and gstack CRITICAL sub-pass.
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Load the language-specific checklist when available (`java-spring.md`,
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`python-django.md`, `python-fastapi.md`, `node-express.md`, `go-gin.md`,
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`csharp-dotnet.md`, `rust.md`, `php-laravel.md`, `ruby-rails.md`); otherwise
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use this generic list.
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## Layer 1 — eight categories
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For each changed area mark ✅ Clean / ⚠️ Issues Found / — N/A.
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1. **Interface** — parameter validation, response conventions, HTTP status
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codes, rate limiting, API versioning, protocol correctness
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2. **Business** — logic aligns with requirements, state machine correctness,
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idempotency design, distributed locks
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3. **Data** — SQL injection, query performance, index usage, transaction
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boundaries, cache invalidation
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4. **Utility** — input validity, no side effects, error return values,
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date/time timezone handling
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5. **Error handling** — exception classification, fallback logic, error
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message sanitization, retry with backoff
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6. **Security** — AuthN/AuthZ, sensitive data masking, permission control,
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CSRF/XSS prevention
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7. **Performance** — N+1 queries, caching strategy, connection pooling,
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batch operations, blocking in async paths
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8. **Observability** — structured logging with correlation IDs, metrics,
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health checks
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## gstack CRITICAL sub-pass (highest severity)
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### SQL & Data Safety
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- String interpolation in SQL — use parameterized queries
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- TOCTOU check-then-set — use atomic `WHERE` + update
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- Bypassing model validations for direct DB writes
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- N+1 queries — missing eager loading
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### Race Conditions & Concurrency
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- Read-check-write without uniqueness constraint / duplicate-key retry
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- find-or-create without a unique DB index
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- Status transitions not atomic (`WHERE old_status = ? UPDATE ...`)
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- Unsafe HTML rendering on user-controlled data
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### LLM Output Trust Boundary
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- LLM-generated values (emails, URLs, names) written to DB without format
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validation
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- Structured tool output accepted without type/shape checks
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- LLM-generated URLs fetched without an allowlist (SSRF)
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- LLM output stored in knowledge bases without sanitization (stored prompt
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injection)
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### Shell Injection
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- `subprocess` with `shell=True` AND interpolated command strings
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- `os.system()` with variable interpolation
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- `eval()`/`exec()` on LLM-generated code without sandboxing
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### Enum & Value Completeness
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- New enum/status/tier values: read (not just grep) every consumer that
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switches/filters/displays the value
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- Check allowlists and `case`/`if-elsif` chains for fall-through
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## Suppressions — do NOT flag
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- Harmless redundancy that aids readability
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- "Add a comment explaining a threshold" — thresholds drift
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- Consistency-only changes
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- Anything already addressed in the diff
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## Severity
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- 🔴 **blocker** — must fix before merge (injection, secrets, missing
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transaction, auth bypass) → verdict FAIL
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- 🟡 **major** — should fix before merge (missing validation, missing
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fallback, N+1, unmasked data)
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- 🔵 **minor** — can optimize later (naming, duplicate code, comments)
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## Confidence calibration
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- 9-10 verified by reading specific code
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- 7-8 high-confidence pattern match
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- 5-6 medium — show with caveat
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- 3-4 low — move to appendix
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- 1-2 speculation — suppress unless severity would be P0
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Every finding: `[SEVERITY] (confidence: N/10) file:line — problem → fix`.
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