better-code-review-graph: Skill for Claude Code

.agents/skills/review-pr/SKILL.md

review-pr is a skill for Claude Code from n24q02m/better-code-review-graph. It costs 27 tokens per session (577 once invoked), scanned A, original, Apache-2.0.

A code-review workflow for a pull request or branch, using a knowledge graph to understand how changed code connects to the rest of the project.

In plain words
What is it for?
Use it to compare changes with a base branch, inspect affected files and functions, assess their blast radius, and produce a structured review.
Why use it?
It reveals affected callers and higher-risk areas, so a review can consider the wider impact instead of only reading the changed lines.

Skill for Claude Code

Written for Claude Code: argument-hint in frontmatter. Also seen: installed under .agents/ (shared by several agents).

This is n24q02m/better-code-review-graph's own configuration. It tells Claude Code how to work on better-code-review-graph itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything better-code-review-graph configures →

Part of the better-code-review-graph plugin — 7 skills, 3 hooks, 1 MCP server shipped together

Reuse

Borrowing it

Nothing to install: this file belongs to n24q02m/better-code-review-graph. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/n24q02m/better-code-review-graph/main/.agents/skills/review-pr/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/n24q02m/better-code-review-graph

Made for: Claude Code.

Or install better-code-review-graph, the plugin that ships this one along with the rest of its 7 skills, 3 hooks, 1 MCP server.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for review-pr

README.md
[![agentmods](https://agentmods.dev/badge/skills/n24q02m/better-code-review-graph/review-pr/github.svg)](https://agentmods.dev/skills/n24q02m/better-code-review-graph/review-pr)
Your own site
<a href="https://agentmods.dev/skills/n24q02m/better-code-review-graph/review-pr"><img src="https://agentmods.dev/badge/skills/n24q02m/better-code-review-graph/review-pr/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for review-pr

Your own site · 80×15
<a href="https://agentmods.dev/skills/n24q02m/better-code-review-graph/review-pr"><img src="https://agentmods.dev/badge/skills/n24q02m/better-code-review-graph/review-pr.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 27 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 577 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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 5.1 $0.00027 $0.00577
Opus 5 $0.00014 $0.00289
Sonnet 5 $0.00005 $0.00115
Haiku 4.5 $0.00003 $0.00058

Measured 9d ago against content hash 389c26372540, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

review-pr scanned grade A with 0 findings 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 9d ago.

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.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

.agents/skills/review-pr/SKILL.md · 67 lines

How it starts

The opening of the file, as written. The whole thing — 67 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Review PR

Perform a comprehensive code review of a pull request or branch diff using the knowledge graph.

Token optimization: Before starting, call help(topic="graph") for the full actions reference. Never include full files unless explicitly asked.

Steps

  1. Identify the changes for the PR:

    • If a PR number or branch is provided, use git diff main...<branch> to get changed files
    • Otherwise auto-detect from the current branch vs main/master
  2. Update the graph by calling graph(action="build", base="main") to ensure the graph reflects the current state.

  3. Get the full review context by calling review(base="main"):

    • This uses main (or the specified base branch) as the diff base
    • Returns all changed files across all commits in the PR
  4. Analyze impact by calling query(action="impact", base="main"):

    • Review the blast radius across the entire PR
    • Identify high-risk areas (widely depended-upon code)
  5. Deep-dive each changed file:

    • Read the full source of files with significant changes
    • Use query(action="query", pattern="callers_of", target=<func>) for high-risk functions
    • Use query(action="query", pattern="tests_for", target=<func>) to verify test coverage
    • Check for breaking changes in public APIs
  6. Generate structured review output:

    ## PR Review: <title>
    
    ### Summary
    <1-3 sentence overview>
    
    ### Risk Assessment
    - **Overall risk**: Low / Medium / High
    - **Blast radius**: X files, Y functions impacted
    - **Test coverage**: N changed functions covered / M total
    
    ### File-by-File Review
    #### <file_path>
    - Changes: <description>
    - Impact: <who depends on this>
    - Issues: <bugs, style, concerns>
    
    ### Missing Tests
    - <function_name> in <file> - no test coverage found
    
    ### Recommendations
    1. <actionable suggestion>
    2. <actionable suggestion>
    

Tips

  • For large PRs, focus on the highest-impact files first (most dependents)
  • Use query(action="search", search_query=<term>) to find related code the PR might have missed
  • Check if renamed/moved functions have updated all callers

Read the full file on GitHub · 67 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. 9d ago First seen · 67 lines · 27 tokens per session scan A 389c26372540

Subscribe to this mod's changes

review-pr is a skill published in the GitHub repository n24q02m/better-code-review-graph (67 stars, last pushed today), licensed Apache-2.0. It adds 27 tokens to every session and 577 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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