review-pr

review-pr is a command for Claude Code, GitHub Copilot from rjmurillo/ai-agents. It costs 7 tokens per session (1,525 once invoked), scanned A, original, MIT.

A pull-request review command that checks changed files from Git and examines code, tests, comments, errors, and types with separate review agents. A pull request is a proposed set of code changes submitted for review before it is merged.

In plain words
What is it for?
Use it to review a pull request, check test coverage, find silent error handling, assess type changes, and simplify code for clarity.
Why use it?
It helps catch quality problems and missing or weak tests without requiring one person to inspect every concern manually. You can review everything or ask for specific review areas.

Command for Claude CodeGitHub Copilot

Written for Claude Code and GitHub Copilot: argument-hint in frontmatter, but also a Copilot chat mode or prompt. Also seen: mentions AGENTS.md.

Good fit Use it to review a pull request, check test coverage, find silent error handling, assess type changes, and simplify code for clarity.

Compare 6 commands from other repositories ↓
Install with agentmods
npx agentmods add commands/rjmurillo/ai-agents/review-pr
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.

Clone the repo
git clone --depth 1 https://github.com/rjmurillo/ai-agents

Made for: Claude Code, GitHub Copilot.

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/commands/rjmurillo/ai-agents/review-pr/github.svg)](https://agentmods.dev/commands/rjmurillo/ai-agents/review-pr)
Your own site
<a href="https://agentmods.dev/commands/rjmurillo/ai-agents/review-pr"><img src="https://agentmods.dev/badge/commands/rjmurillo/ai-agents/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/commands/rjmurillo/ai-agents/review-pr"><img src="https://agentmods.dev/badge/commands/rjmurillo/ai-agents/review-pr.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 7 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,525 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 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 $0.00007 $0.01525
Opus 5.5 $0.00003 $0.00610
Sonnet 5.5 $0.00001 $0.00305
Haiku 4.5 $0.00001 $0.00153

Measured 7d ago against content hash c371b1b79632, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, 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 7d 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.

.github/prompts/review-pr.prompt.md · 262 lines

How it starts

The opening of the file, as written. The whole thing — 262 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Comprehensive PR Review

Run a comprehensive pull request review using multiple specialized agents, each focusing on a different aspect of code quality.

Review Aspects (optional): "$ARGUMENTS"

Review Workflow

  1. Determine Review Scope

    • Check git status to identify changed files
    • Parse arguments to see if user requested specific review aspects
    • Default: Run all applicable reviews
  2. Available Review Aspects:

    • comments - Analyze code comment accuracy and maintainability
    • tests - Review test coverage quality and completeness
    • errors - Check error handling for silent failures
    • types - Analyze type design and invariants (if new types added)
    • code - General code review for project guidelines
    • simplify - Simplify code for clarity and maintainability
    • all - Run all applicable reviews (default)
  3. Identify Changed Files

    • Run git diff --name-only to see modified files
    • Check if PR already exists: gh pr view
    • Identify file types and what reviews apply
  4. Determine Applicable Reviews

    Based on changes:

    • Always applicable: code-reviewer (general quality)
    • If test files changed: pr-test-analyzer
    • If comments/docs added: comment-analyzer
    • If error handling changed: silent-failure-hunter
    • If types added/modified: type-design-analyzer
    • After passing review: code-simplifier (polish and refine)
  5. Launch Review Agents

    Sequential approach (one at a time):

    • Easier to understand and act on
    • Each report is complete before next
    • Good for interactive review

    Parallel approach (user can request):

    • Launch all agents simultaneously
    • Faster for comprehensive review
    • Results come back together
  6. Aggregate Results

    After agents complete, summarize:

    • Critical Issues (must fix before merge)
    • Important Issues (should fix)
    • Suggestions (nice to have)
    • Positive Observations (what's good)

Read the full file on GitHub · 262 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. 7d ago First seen · 262 lines · 7 tokens per session scan A c371b1b79632

Subscribe to this mod's changes

review-pr is a command published in the GitHub repository rjmurillo/ai-agents (48 stars, last pushed today), licensed MIT. It adds 7 tokens to every session and 1,525 once invoked, about $0.0000 per session on Opus 5.5. 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 2026-10-09.