Agent skill

code-review

Review and score code quality across 12 dimensions. Read-only analysis with numeric scoring. Use to diagnose issues before fixing.

View SKILL.md on GitHub Repository
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Forks 31

Install this agent skill to your Project

npx add-skill https://github.com/majiayu000/claude-skill-registry/tree/main/skills/other/other/code-review-corbat-tech-coco

SKILL.md

Code Review

Comprehensive code quality review with numeric scoring. Read-only — this skill does not modify any files.

How it works

This skill is agent-implemented — the agent reads the steps below and executes them autonomously. There is no standalone bash script.

/code-review
/code-review security
/code-review src/api/

Input

  • $ARGUMENTS = optional focus area (e.g., "security", "tests", "src/api/")
  • If empty, reviews the entire project

Phase 1: Context Gathering

Understand the project before reviewing:

bash
# Project type and structure
ls -la
cat package.json 2>/dev/null || cat Cargo.toml 2>/dev/null || cat pyproject.toml 2>/dev/null || echo "unknown project type"

# Recent changes (what to focus on)
git diff --stat HEAD~5..HEAD 2>/dev/null || git diff --stat
git log --oneline -10

# Test infrastructure
ls -la test/ tests/ __tests__/ spec/ 2>/dev/null

Phase 2: Run Automated Checks

Run every available automated check and capture results:

bash
# Auto-detect and run checks
if [ -f "pnpm-lock.yaml" ]; then
  pnpm typecheck 2>&1 || true
  pnpm lint 2>&1 || true
  pnpm test 2>&1 || true
elif [ -f "yarn.lock" ]; then
  yarn typecheck 2>&1 || true
  yarn lint 2>&1 || true
  yarn test 2>&1 || true
elif [ -f "package-lock.json" ]; then
  npm run typecheck 2>&1 || true
  npm run lint 2>&1 || true
  npm test 2>&1 || true
elif [ -f "Cargo.toml" ]; then
  cargo clippy 2>&1 || true
  cargo test 2>&1 || true
elif [ -f "pyproject.toml" ]; then
  ruff check . 2>&1 || true
  pytest 2>&1 || true
fi

Capture pass/fail and any error output for each check.

Phase 3: Manual Code Analysis

Review code across 12 quality dimensions. For each dimension, read relevant files and assess:

Dimensions and Weights

# Dimension Weight What to check
1 Correctness 15% Do tests pass? Does the build succeed? Logic errors?
2 Completeness 10% Are requirements met? Missing edge cases? TODO/FIXME items?
3 Robustness 10% Error handling, null checks, boundary conditions, input validation
4 Readability 10% Naming clarity, function size, code organization
5 Maintainability 10% Coupling, cohesion, single responsibility, DRY
6 Complexity 8% Cyclomatic complexity, nesting depth, function length
7 Duplication 7% Copy-paste code, repeated patterns that should be abstracted
8 Test Coverage 10% Line/branch coverage, critical paths tested
9 Test Quality 5% Meaningful assertions, edge cases, test isolation
10 Security 8% OWASP top 10, injection, XSS, hardcoded secrets, auth gaps
11 Documentation 4% Public API docs, complex logic explained, README accuracy
12 Style 3% Linting compliance, consistent formatting

Severity Classification

For each issue found, classify as:

  • P0 Critical — Blocks deployment. Security vulnerabilities, data loss, crashes.
  • P1 High — Must fix before merge. Bugs, missing error handling, failing tests.
  • P2 Medium — Should fix soon. Code smells, moderate complexity, weak tests.
  • P3 Low — Nice to have. Style issues, minor refactors, documentation gaps.

Phase 4: Scoring

Calculate the weighted score (0-100):

For each dimension:

  1. Assign a score from 0-100 based on the analysis
  2. Multiply by the weight
  3. Sum all weighted scores
TOTAL = sum(dimension_score * weight) for all 12 dimensions

Score interpretation

Score Grade Meaning
95-100 A+ Excellent — production ready, exemplary code
85-94 A Senior-level — solid, maintainable, well-tested
70-84 B Good — some issues but functional and reasonable
50-69 C Needs work — significant issues to address
0-49 D Poor — critical problems, not ready for review

Output Format

Present the results in this exact format:

## Code Review Report

### Summary
- **Score: XX/100 (Grade X)**
- Files analyzed: N
- Issues found: N (P0: N, P1: N, P2: N, P3: N)

### Dimension Scores

| Dimension        | Score | Weight | Weighted | Notes |
|------------------|-------|--------|----------|-------|
| Correctness      | XX    | 15%    | XX.X     | ...   |
| Completeness     | XX    | 10%    | XX.X     | ...   |
| Robustness       | XX    | 10%    | XX.X     | ...   |
| Readability      | XX    | 10%    | XX.X     | ...   |
| Maintainability  | XX    | 10%    | XX.X     | ...   |
| Complexity       | XX    | 8%     | XX.X     | ...   |
| Duplication      | XX    | 7%     | XX.X     | ...   |
| Test Coverage    | XX    | 10%    | XX.X     | ...   |
| Test Quality     | XX    | 5%     | XX.X     | ...   |
| Security         | XX    | 8%     | XX.X     | ...   |
| Documentation    | XX    | 4%     | XX.X     | ...   |
| Style            | XX    | 3%     | XX.X     | ...   |
| **TOTAL**        |       | 100%   | **XX.X** |       |

### Issues (sorted by severity)

#### P0 Critical
- [file:line] Description of the issue

#### P1 High
- [file:line] Description of the issue

#### P2 Medium
- [file:line] Description of the issue

#### P3 Low
- [file:line] Description of the issue

### Recommendations
1. Top priority fix: ...
2. Second priority: ...
3. ...

Important

  • This skill is read-only — it NEVER modifies files
  • Run /code-fix after this to apply fixes based on the findings
  • Run /coco-fix-iterate to automatically review, fix, and iterate until the score target is met
  • Be honest with scores — inflated scores defeat the purpose
  • Focus analysis on recently changed files when a focus area is not specified

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