Agent skill

Review PR

by ThinkFlowLab in ThinkFlowLab/system1-agents

Review pull requests for system1-agents with high-confidence, evidence-based feedback.

Apache-2.0Auto-check passedDevelopment

Install Review PR

skills CLI
$ npx skills add ThinkFlowLab/system1-agents --skill review-pr -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install ThinkFlowLab/system1-agents review-pr --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/ThinkFlowLab/system1-agents.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.claude/skills/review-pr .claude/skills/review-pr && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
review-pr
GitHub stars
126
Token cost
~851 tokens
SKILL.md length
432 words
Files
1
Skills in repo
5
Repo updated
First seen
Licence
Apache-2.0

At a glance

Review pull requests for system1-agents with high-confidence, evidence-based feedback.

  • Works in 6 steps: Correct — the issue is real and… → Prioritized — label as blocker, major,… → Actionable — include a concrete fix or… → …
  • The user asks to review a PR
  • SKILL.md covers Quality contract, Review focus for this repository, Process and Output format, plus 1 more section
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Review PR is an agent skill from ThinkFlowLab/system1-agents. Review pull requests for system1-agents with high-confidence, evidence-based feedback. Use when the user asks to review a PR, a diff, or code changes in this repository.

Its SKILL.md is about 850 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Development, covering Pull requests. The repository describes itself as: System 1 decision models (Jev, Laya, Cua-S1) as brain for agents: Browser use, computer use, games and robotics. The licence is Apache-2.0.

When your agent uses it

  • The user asks to review a PR
  • Code changes in this repository

Example prompts

  • “/review-pr”

Workflow steps

6 steps, taken from the first numbered list in SKILL.md.

  1. Correct — the issue is real and reproducible.
  2. Prioritized — label as blocker, major, minor, or nit.
  3. Actionable — include a concrete fix or next step.
  4. Evidence-backed — cite file, line, test, or command.
  5. Concise — one problem per comment; no essays.
  6. Calibrated — if uncertain, say so; do not assert.

What it can do on your machine

Read from SKILL.md and the folder at commit 3a2c2c6. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Review PR loads about 851 tokens when it runs. Until then it costs about 45 tokens; SKILL.md has 432 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~45
When it runs · the whole SKILL.md, loaded when a task matches
~851

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from ThinkFlowLab/system1-agents at commit 3a2c2c6, republished under its Apache-2.0 licence (© ThinkFlowLab). 432 words, ~851 tokens.

Download SKILL.mdSave it as .claude/skills/review-pr/SKILL.md (or your agent's skills folder).
name
review-pr
description
Review pull requests for system1-agents with high-confidence, evidence-based feedback. Use when the user asks to review a PR, a diff, or code changes in this repository.

Review PR

You are a senior maintainer reviewing a pull request for system1-agents. Your job is to find real problems that CI cannot prove, not to restate style preferences or summarize the diff.

CodeRabbit reads this file as review guidelines (.coderabbit.yaml), so the quality contract and the review focus below apply to its comments on every pull request. The process and the output format are for a review run by hand, for example by a maintainer with Claude Code; CodeRabbit keeps its own comment layout.

Quality contract

Every comment must satisfy all six criteria:

  1. Correct — the issue is real and reproducible.
  2. Prioritized — label as blocker, major, minor, or nit.
  3. Actionable — include a concrete fix or next step.
  4. Evidence-backed — cite file, line, test, or command.
  5. Concise — one problem per comment; no essays.
  6. Calibrated — if uncertain, say so; do not assert.

If a comment cannot meet all six, omit it.

Review focus for this repository

  • System 1 decision path: Jev invocation, model selection, fallback behavior, and deterministic replay.
  • Multi-model comparison: benchmark fairness, random seeds, caching, concurrency, and result aggregation.
  • Async/concurrency: asyncio cancellation, timeouts, resource cleanup, and race conditions.
  • Public API compatibility: type hints, backward compatibility, and documented behavior.
  • Tests: new tests cover edge cases, error paths, model-unavailable scenarios, and regressions.
  • Performance: token usage, latency, memory, and unnecessary model calls.
  • Security: API keys, prompt injection, log redaction, and dependency changes.
Show full SKILL.md (199 more words)Show less

Process

  1. For a pull request, read its title and description and every issue it closes or links. For a branch with no pull request, ask the user for the change's purpose and any issues it addresses before reviewing. Then read the changed files.

  2. Check the change against its purpose, and report a mismatch like any other finding:

    • the diff fixes the symptom the issue describes;
    • nothing changes that the issue and description do not call for;
    • nothing the issue or description asks for is missing;
    • the description says what the diff does.

    With no linked issue, check against the description, or against the purpose the user gave for a branch without a pull request, and say there is no issue.

  3. Run or inspect the relevant tests when possible.

  4. Identify only issues that CI cannot prove.

  5. Produce a short review with at most 5 high-confidence comments.

  6. If there are no blocking issues, say so explicitly.

Output format

## Review summary
<one paragraph: what changed and overall risk>

## Findings
### [blocker|major|minor|nit] <title>
- **Where**: `path/to/file.py:123`
- **Evidence**: <test, command, or reasoning>
- **Why it matters**: <impact>
- **Suggested fix**: <concrete change>

## Questions
- <only if genuinely needed>

Do not

  • Do not comment on formatting, naming, or style unless it causes a bug.
  • Do not repeat CI failures.
  • Do not speculate without evidence.
  • Do not approve or request changes on behalf of a human maintainer.

© ThinkFlowLab, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in .claude/skills/review-pr of ThinkFlowLab/system1-agents.

Open the folder on GitHubat commit 3a2c2c6

Compare with similar skills

Review PR next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Review PR compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Review PR this skillThinkFlowLab/system1-agents126—~851Automated safety check: PassApache-2.0
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PR Babysitteropeninterpreter/openinterpreter69k3 repos~4.2kAutomated safety check: PassApache-2.0
Check PRonyx-dot-app/onyx32k2 repos~2.3kAutomated safety check: PassMIT
PR Design DocOpenHands/OpenHands90k—~2.4kAutomated safety check: PassMIT
WooCommerce Code Reviewwoocommerce/woocommerce11k3 repos~1.1kAutomated safety check: PassCustom licence

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Categories

Questions about Review PR

What does Review PR do?

Review pull requests for system1-agents with high-confidence, evidence-based feedback. Review PR is an agent skill from ThinkFlowLab/system1-agents. Review pull requests for system1-agents with high-confidence, evidence-based feedback.

When should I use Review PR?

Review PR fits situations like: the user asks to review a PR; code changes in this repository.

How do I install Review PR in Claude Code?

Run `npx skills add ThinkFlowLab/system1-agents --skill review-pr -a claude-code`. Or copy the skill folder (.claude/skills/review-pr in ThinkFlowLab/system1-agents) into .claude/skills/review-pr in your project. Claude Code loads it when a task matches its description.

How do I install Review PR in Codex?

Run `npx skills add ThinkFlowLab/system1-agents --skill review-pr -a codex`. Or copy the skill folder (.claude/skills/review-pr in ThinkFlowLab/system1-agents) into .agents/skills/review-pr in your project. Codex loads it when a task matches its description.

Can I use Review PR in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add ThinkFlowLab/system1-agents --skill review-pr -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/review-pr, .gemini/skills/review-pr, .github/skills/review-pr and .opencode/skills/review-pr in your project.

What does Review PR need to run?

SKILL.md names no scripts, command-line tools or credentials: Review PR is instructions for the agent only.

Does Review PR access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Review PR safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Review PR use?

Review PR is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Review PR use?

About 851 tokens (SKILL.md is roughly 3.4k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Review PR?

Skills that share tags, products or a category with Review PR: Finishing a Development Branch (obra/superpowers, 297k stars), PR Babysitter (openinterpreter/openinterpreter, 69k stars), Check PR (onyx-dot-app/onyx, 32k stars) and PR Design Doc (OpenHands/OpenHands, 90k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Review PR?

ThinkFlowLab (a GitHub organization) maintains it in ThinkFlowLab/system1-agents, which has 126 GitHub stars. The repository holds 5 skills in this directory. The repository was last updated on October 8, 2026.

Source: ThinkFlowLab/system1-agents on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.