github-code-review

A code-review helper for GitHub pull requests, which are proposed changes submitted for review before merging. It coordinates separate reviewers for security, performance, architecture, style, and accessibility.

In plain words
What is it for?
Use it to review pull-request files and diffs, start multi-reviewer checks, post review status, and examine changes across pull requests.
Why use it?
It gives a code change several focused reviews instead of relying on one general pass or only automated checks.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/aegntic/cldcde/github-code-review
Any agent
npx skills add aegntic/cldcde --skill github-code-review
Clone the repo
git clone --depth 1 https://github.com/aegntic/cldcde

Made for: Claude Code, Codex.

Per session 15 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 6,644 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00015 $0.06644
Opus 5 $0.00008 $0.03322
Sonnet 5 $0.00003 $0.01329
Haiku 4.5 $0.00002 $0.00664

Measured yesterday against content hash 6ed59c79ed71, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

github-code-review scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Runs shell commandslowCapability

Expected in a hook, worth knowing in a rule or an instructions file.

const { execSync } = require('child_process');
.claude/skills/github-code-review/SKILL.md · 1,141 lines

How it starts

The opening of the file, as written. The whole thing — 1,141 lines — stays where its author put it; the contents beside it link to each section on GitHub.

GitHub Code Review Skill

AI-Powered Code Review: Deploy specialized review agents to perform comprehensive, intelligent code reviews that go beyond traditional static analysis.

🎯 Quick Start

Simple Review

# Initialize review swarm for PR
gh pr view 123 --json files,diff | npx ruv-swarm github review-init --pr 123

# Post review status
gh pr comment 123 --body "🔍 Multi-agent code review initiated"

Complete Review Workflow

# Get PR context with gh CLI
PR_DATA=$(gh pr view 123 --json files,additions,deletions,title,body)
PR_DIFF=$(gh pr diff 123)

# Initialize comprehensive review
npx ruv-swarm github review-init \
  --pr 123 \
  --pr-data "$PR_DATA" \
  --diff "$PR_DIFF" \
  --agents "security,performance,style,architecture,accessibility" \
  --depth comprehensive

📚 Table of Contents

Read the full file on GitHub · 1,141 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. yesterday First seen · 1,141 lines · 15 tokens per session scan A 6ed59c79ed71

Subscribe to this mod's changes

github-code-review is a skill published in the GitHub repository aegntic/cldcde (11 stars, last pushed 5d ago), licensed MIT. It adds 15 tokens to every session and 6,644 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 1 finding (runs shell commands). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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