code-review
The code-review skill conducts structured multi-pass code analysis for pull requests, staged changes, or individual files. It systematically orients to the change's intent and type, flags only genuine defects like logic errors and security issues during a critical pass, applies specialist lenses for tests and data access, then assigns confidence levels to findings. Use this when reviewing code changes to distinguish between substantive problems and stylistic preferences.
git clone --depth 1 https://github.com/blueberrycongee/termcanvas /tmp/code-review && cp -r /tmp/code-review/skills/skills/code-review ~/.claude/skills/code-reviewSKILL.md
# Code Review Structured multi-pass review. Read the full diff before commenting on anything. ## Phase 1: Orient 1. Determine the review scope: - If reviewing a PR: `git diff <base>..HEAD` - If reviewing staged changes: `git diff --cached` - If reviewing a file: read the file 2. Understand the intent: read the commit messages, PR description, or task description to understand what the change is supposed to do 3. Identify the change type: feature, bugfix, refactor, config, dependency update ## Phase 2: Critical Pass Read the diff line by line. Flag only real issues: **Always check:** - Logic errors (wrong conditions, off-by-one, missing null checks on external data) - SQL injection, XSS, command injection, path traversal - Race conditions in concurrent code - Resource leaks (unclosed handles, missing cleanup) - Missing error handling at system boundaries (network, file I/O, user input) - Breaking API contract changes without version bump **Never flag:** - Style preferences (naming, formatting) unless they cause confusion - Missing comments on self-explanatory code - Hypothetical edge cases that cannot happen given the invariants - "I would have done it differently" without a concrete defect ## Phase 3: Specialist Focus Based on the change type, apply the relevant specialist lens: **If the diff touches tests:** - Do tests actually test behavior, or just assert mock return values? - Are there tautological assertions (`expect(true).toBe(true)`)? - Is the test coupled to implementation details rather than outcomes? **If the diff touches data access:** - N+1 query patterns in loops - Unbounded result sets without pagination - Transactions where atomic operations are needed **If the diff touches auth/security:** - Apply Phase 2-4 of the `security-audit` skill to the changed code **If the diff touches UI:** - State management: are loading/error/empty states handled? - Accessibility: keyboard navigation, semantic HTML, ARIA labels - Responsive: does it work at mobile/tablet/desktop breakpoints? ## Phase 4: Verdict For each finding, assign a confidence level: - **High (8-10)**: Confirmed defect with clear evidence — fix before merge - **Medium (5-7)**: Likely issue, but may depend on context — discuss - **Low (1-4)**: Possible concern, worth noting — optional Report format per finding: ``` [severity] file:line — description Confidence: N/10 Suggestion: specific fix ``` ## Final verdict - **Approve**: no High findings, no more than 2 Medium findings - **Request changes**: any High finding, or 3+ Medium findings - **If nothing is wrong**: say "no issues found" — do not invent problems ## Rules - Read the code before commenting — never review from the description alone - Every finding must reference a specific file and line - Do not suggest refactoring that is unrelated to the change being reviewed - A review that flags nothing wrong is a valid review — do not pad
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Use when a task should run through Hydra's Lead-driven workflow for multi-agent orchestration, or when an existing workflow must be inspected or cleaned up.
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Use when starting work in a TermCanvas-managed repo to route between direct work, Hydra, or a narrow TermCanvas skill.