agent-reference-skills: Skill for Claude Code

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

implement-review-pr is a skill for Claude Code, Codex from Fandhe-AI/agent-reference-skills. It costs 97 tokens per session (2,172 once invoked), scanned A, original, no licence file.

A reviewer for GitHub pull requests, which are proposed code changes, checking automated test results, code quality, common security risks, and commit-message conventions.

In plain words
What is it for?
Use it to review a numbered GitHub pull request, including its CI checks, OWASP Top 10 security risks, and Conventional Commits compliance.
Why use it?
It brings the main pull-request checks into one review and can record an approval, requested changes, or a comment on GitHub.

Skill for Claude CodeCodex

Written for Claude Code: user-invocable in frontmatter. Also seen: model in frontmatter; installed under .agents/ (shared by several agents).

This is Fandhe-AI/agent-reference-skills's own configuration. It tells Claude Code and Codex how to work on agent-reference-skills 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 agent-reference-skills configures →

Reuse

Borrowing it

Nothing to install: this file belongs to Fandhe-AI/agent-reference-skills. 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/Fandhe-AI/agent-reference-skills/main/.agents/skills/implement-review-pr/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/Fandhe-AI/agent-reference-skills

Made for: Claude Code, Codex.

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 implement-review-pr

README.md
[![agentmods](https://agentmods.dev/badge/skills/fandhe-ai/agent-reference-skills/implement-review-pr/github.svg)](https://agentmods.dev/skills/fandhe-ai/agent-reference-skills/implement-review-pr)
Your own site
<a href="https://agentmods.dev/skills/fandhe-ai/agent-reference-skills/implement-review-pr"><img src="https://agentmods.dev/badge/skills/fandhe-ai/agent-reference-skills/implement-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 implement-review-pr

Your own site · 80×15
<a href="https://agentmods.dev/skills/fandhe-ai/agent-reference-skills/implement-review-pr"><img src="https://agentmods.dev/badge/skills/fandhe-ai/agent-reference-skills/implement-review-pr.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 97 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,172 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.
Origin unknown 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 $0.00097 $0.02172
Opus 5 $0.00048 $0.01086
Sonnet 5 $0.00019 $0.00434
Haiku 4.5 $0.00010 $0.00217

Measured 8d ago against content hash 21fcea051e8c, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

implement-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 8d 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/implement-review-pr/SKILL.md · 174 lines

The source is not reproduced here

No licence file

A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.

Read it on GitHub

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. 8d ago First seen · 174 lines · 97 tokens per session scan A 21fcea051e8c

Subscribe to this mod's changes

implement-review-pr is a skill published in the GitHub repository Fandhe-AI/agent-reference-skills (3 stars, last pushed today), with no licence file. It adds 97 tokens to every session and 2,172 once invoked, about $0.0005 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 2026-08-31.