Review Code
## Setup
On first use, read `setup.md` for integration guidance and local memory initialization.
## When to Use
User asks for a code review, PR review, merge-readiness check, or bug-risk audit before shipping.
Agent delivers a risk-ranked review with explicit evidence, impact, confidence, and concrete fix direction.
## Architecture
Memory lives in `~/review-code/`. See `memory-template.md` for structure and starter templates.
```text
~/review-code/
├── memory.md # Review preferences, stack context, and recent constraints
├── findings/ # Optional per-review finding logs
├── baselines/ # Team conventions and accepted risk baselines
└── sessions/ # Session summaries for ongoing audits
```
## Quick Reference
| Topic | File |
|-------|------|
| Setup and integration behavior | `setup.md` |
| Memory schema and templates | `memory-template.md` |
| End-to-end review execution flow | `review-workflow.md` |
| Severity and confidence calibration | `severity-and-confidence.md` |
| Language and architecture risk checks | `language-risk-checklists.md` |
| Test impact requirements by change type | `test-impact-playbook.md` |
| Comment and report templates | `comment-templates.md` |
| Patch strategy for actionable fixes | `patch-strategy.md` |
## Data Storage
Local notes stay in `~/review-code/`.
Before creating or changing local files, present the planned write and ask for user confirmation.
## Core Rules
### 1. Define the Review Contract First
Confirm target scope before reviewing: branch, files, risk tolerance, and release context.
If scope is unclear, state assumptions explicitly and keep findings tied to those assumptions.
### 2. Start With Risk Mapping, Then Deep Dive
Run a fast pass to locate high-risk zones first: auth, money, data integrity, concurrency, and migration paths.
Only then perform line-level analysis with `review-workflow.md` so major failures are surfaced early.
### 3. Every Finding Must Be Evidence-Backed
Do not report vague concerns.
Each finding must include: trigger location, concrete failure mode, user or business impact, and minimal reproduction clue.
If evidence is weak, mark low confidence or downgrade to a question.
### 4. Separate Blocking vs Advisory With Severity + Confidence
Use `severity-and-confidence.md` for consistent triage.
Blocking findings must be reproducible or highly probable with strong impact.
Advisory feedback must remain concise and never hide blockers.
### 5. Always Pair Findings With a Fix Path
For each blocking issue, provide a minimally disruptive fix strategy.
Use `patch-strategy.md` to propose rollback-safe edits, guard tests, and verification steps.
### 6. Tie Review Quality to Test Impact
Map each change to required tests using `test-impact-playbook.md`.
If tests are missing, list the exact scenarios that must be added and why they prevent regressions.
### 7. Optimize for Signal, Not Volume
Prioritize high-impact defects over style noise.
If no blockers are found, state that explicitly and list residual risks, test gaps, and monitoring advice.
## Common Traps
- Reporting opinions as facts -> review credibility drops and teams ignore real blockers.
- Mixing blocker and nit feedback without labels -> delayed merges and mis-prioritized fixes.
- Calling something “probably fine” without tests -> silent regressions in production.
- Suggesting large rewrites for local defects -> good fixes are postponed indefinitely.
- Ignoring release context (hotfix vs refactor) -> wrong trade-offs for urgency.
- Missing migration and backward-compatibility checks -> runtime failures after deploy.
## External Endpoints
This skill makes NO external network requests.
| Endpoint | Data Sent | Purpose |
|----------|-----------|---------|
| None | None | N/A |
No other data is sent externally.
## Security & Privacy
**Data that leaves your machine:**
- Nothing by default. This is an instruction-only review skill unless the user explicitly exports artifacts.
**Data stored locally:**
- Review preferences, project constraints, and optional findings approved by the user.
- Stored in `~/review-code/`.
**This skill does NOT:**
- auto-approve code or merge pull requests.
- make undeclared network calls.
- store credentials, tokens, or sensitive payloads.
- modify its own core instructions or auxiliary files.
## Trust
This is an instruction-only code review skill.
No credentials are required and no third-party services are contacted by default.
## Related Skills
Install with `clawhub install <slug>` if user confirms:
- `code` - implementation workflow that complements review findings.
- `git` - safer branch, diff, and commit handling during remediation.
- `typescript` - stricter typing and runtime safety review for TS-heavy codebases.
- `ci-cd` - release-gate checks and deployment safeguards after fixes.
- `devops` - production risk assessment and rollback planning.
## Feedback
- If useful: `clawhub star review-code`
- Stay updated: `clawhub sync`
标签
skill
ai