Skills

Skill Code Review

Expert multi-AI code review with inline PR comments, use for thorough quality and...

Install

npx skills add nyldn/claude-octopus --skill skill-code-review -g -a claude-code -y
Repository
nyldn/claude-octopus4.4k
Category
Security
Updated
3d ago
License
MIT
Context cost
Mediumabout 2,616 tokens
Runs scripts
No, instructions only

What it does

Expert multi-AI code review with inline PR comments, use for thorough quality and security analysis

Code Review Skill

MANDATORY COMPLIANCE, DO NOT SKIP

When this skill is invoked, you MUST execute the multi-LLM review pipeline. You are PROHIBITED from:

  • Doing a direct single-model code review without multi-provider synthesis
  • Deciding the scope is "too broad" and narrowing it without asking the user
  • Skipping the provider check or structured review phases
  • Substituting two background Sonnet agents for the full multi-provider pipeline
  • Rationalizing "a focused audit would be more effective", the user wants multi-LLM perspectives

Your first output line MUST be: 🐙 **CLAUDE OCTOPUS ACTIVATED** - Multi-LLM Code Review

Invokes the code-reviewer persona for thorough code analysis during the ink (deliver) phase.

Quick Mode

For fast sanity checks (staged changes, small PRs), skip the full review pipeline and run just two phases:

# Quick: grasp (consensus on scope) → tangle (parallel review)
${HOME}/.claude-octopus/plugin/scripts/orchestrate.sh grasp "[review request]"
${HOME}/.claude-octopus/plugin/scripts/orchestrate.sh tangle "[synthesized scope]"

Use quick mode when user says "check this PR", "quick review", "sanity check my changes", or for pre-commit checks. Use the full review for PRs with security/architecture impact.

Usage

# Via orchestrate.sh
${HOME}/.claude-octopus/plugin/scripts/orchestrate.sh spawn code-reviewer "Review this pull request for security issues"

# Via auto-routing (detects review intent)
${HOME}/.claude-octopus/plugin/scripts/orchestrate.sh auto "review the authentication implementation"

Capabilities

  • AI-powered code quality analysis
  • Security vulnerability detection
  • Performance optimization suggestions
  • Architecture and design pattern review
  • TDD compliance and test-first evidence review
  • Autonomous code generation risk detection
  • Best practices enforcement

Persona Reference

Read the whole SKILL.md on GitHub

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