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Code Review

ASecurity

Structured code quality assessment with Conventional Comments format, scaled review depth, and soft-gating verdicts preserving user autonomy.

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  • Added September 2, 2026
ai-agentsgobashtestingcode-reviewgitbackendsecurity

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Scanned September 2, 2026

npx -y skills add a5c-ai/babysitter --skill code-review --agent claude-code

Installs into .claude/skills of the current project.

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SKILL.md
---
name: code-review
description: Structured code quality assessment with Conventional Comments format, scaled review depth, and soft-gating verdicts preserving user autonomy.
allowed-tools: Read, Bash, Grep, Glob, Agent, AskUserQuestion
graph:
  domains: [domain:software-engineering]
  skillAreas: [skill-area:agentic-loops, skill-area:orchestration-loop]
  workflows: [workflow:feature-development]
  topics: [topic:developer-experience]
  roles: [role:tech-lead, role:backend-engineer]
---

- When reviewing code changes before merge
- As part of the /review-code command

## Process

1. Identify modified files via git
2. Assess change magnitude for review depth
3. Execute 9-step review: context, correctness, design, testing, security flags, operations, maintainability
4. Synthesize findings in standardized report
5. Deliver verdict with rationale

## Review Depth Scaling

- Under 200 lines: full detail review
- 200-1000 lines: focused review on critical areas
- Over 1000 lines: architectural-level review only

## Verdicts

- **APPROVE**: Ready for security review
- **APPROVE WITH NITS**: Non-blocking suggestions only
- **REQUEST CHANGES**: Blocking issues exist (user may override)

## Key Rules

- Provide specific file paths and line numbers
- Include at least one positive comment per review
- Use Conventional Comments format with decorations
- Explain reasoning, not just observations
- Limit critical issues to top 5 per category
- Reviews are soft gates preserving user autonomy

## Tool Use

Invoke via babysitter process: `methodologies/rpikit/rpikit-review`

Files in this skill

  • README.md445 B
  • SKILL.md1.5 KB

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