pr-review

pr-review is a command for Claude Code from RoboFinSystems/robosystems. It costs 19 tokens per session (1,600 once invoked), scanned A, original, Apache-2.0.

A pull-request review command that collects the request's details, code changes, checks, and existing feedback before giving a verdict.

In plain words
What is it for?
Reviewing a pull request from its URL or number, examining its diff and comments, checking metadata and automated results, and summarizing the review.
Why use it?
It brings the review context together so important comments, status checks, and parts of the diff are less likely to be overlooked.

Command for Claude Code

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 commands/robofinsystems/robosystems/pr-review
Clone the repo
git clone --depth 1 https://github.com/RoboFinSystems/robosystems

Made for: Claude Code.

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 pr-review

README.md
[![agentmods](https://agentmods.dev/badge/commands/robofinsystems/robosystems/pr-review.svg)](https://agentmods.dev/commands/robofinsystems/robosystems/pr-review)
Your own site
<a href="https://agentmods.dev/commands/robofinsystems/robosystems/pr-review"><img src="https://agentmods.dev/badge/commands/robofinsystems/robosystems/pr-review.svg" alt="Measured on agentmods" height="20"></a>
Per session 19 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,600 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. 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 $0.00019 $0.01600
Opus 5 $0.00010 $0.00800
Sonnet 5 $0.00004 $0.00320
Haiku 4.5 $0.00002 $0.00160

Measured 4d ago against content hash f0239ec22228, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

pr-review 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 4d 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.

.claude/commands/pr-review.md · 120 lines

How it starts

The opening of the file, as written. The whole thing — 120 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Review a pull request by gathering all PR metadata, diff, and review comments, then provide a comprehensive review summary.

Instructions

1. Identify the PR

The user may provide a PR URL, number, or nothing:

  • URL provided (e.g., https://github.com/RoboFinSystems/robosystems/pull/577): Extract the repo and PR number
  • Number provided (e.g., 577): Use the current repository
  • Nothing provided: Detect from the current branch using gh pr view --json number,url — if no open PR exists for the current branch, ask the user which PR to review

2. Gather PR Data

Run these gh commands to collect all context:

# PR metadata + conversation comments in one call
gh pr view <NUMBER> --json number,url,title,body,author,state,isDraft,labels,comments,reviews,reviewDecision,latestReviews,reviewRequests,statusCheckRollup,mergeStateStatus,headRefName,headRefOid,baseRefName,additions,deletions,changedFiles,files,closingIssuesReferences,createdAt,updatedAt

# PR diff (the actual code changes)
gh pr diff <NUMBER>

# Inline review comments — no --json equivalent exists, so this call is still required
gh api repos/$(gh repo view --json nameWithOwner -q .nameWithOwner)/pulls/<NUMBER>/comments --paginate

Field notes:

  • reviews not reviewersreviewers is not a valid field and errors.
  • reviewDecision is the single field that answers "has this been approved."
  • comments covers the top-level conversation, so no separate issues/<n>/comments call is needed.
  • closingIssuesReferences gives the linked issue (needed for step 5's requirements check); files gives per-file add/delete counts (needed for triaging a large diff); headRefOid is the HEAD SHA.
  • Keep --paginate bare. Adding -q/--jq makes gh emit one JSON document per page instead of a merged array, and --slurp can't be combined with --jq. Pipe to jq after the call, not through it.

3. Categorize Review Feedback

Organize all comments and checks into categories:

Read the full file on GitHub · 120 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. 4d ago First seen · 120 lines · 19 tokens per session scan A f0239ec22228

Subscribe to this mod's changes

pr-review is a command published in the GitHub repository RoboFinSystems/robosystems (24 stars, last pushed yesterday), licensed Apache-2.0. It adds 19 tokens to every session and 1,600 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.