setup-pr-review

A setup guide that adds an OpenHands automated pull-request review workflow to a GitHub repository.

In plain words
What is it for?
Use it to create the GitHub Actions workflow, choose OpenHands or your own language-model provider, and configure the required API key.
Why use it?
It automates code reviews for pull requests and can post comments directly on changed lines.

Skill for Claude CodeCodex

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 skills/openhands/extensions/setup-pr-review
Any agent
npx skills add OpenHands/extensions --skill setup-pr-review
Clone the repo
git clone --depth 1 https://github.com/OpenHands/extensions

Made for: Claude Code, Codex.

Per session 44 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 730 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 $0.00044 $0.00730
Opus 5 $0.00022 $0.00365
Sonnet 5 $0.00009 $0.00146
Haiku 4.5 $0.00004 $0.00073

Measured 2d ago against content hash 70b8d5fb4461, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

setup-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 2d 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.

plugins/onboarding/skills/setup-pr-review/SKILL.md · 73 lines

How it starts

The opening of the file, as written. The whole thing — 73 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Set Up OpenHands PR Review

Add the PR review workflow to a GitHub repository so an OpenHands agent can review pull requests and post inline comments.

Docs: https://docs.all-hands.dev/sdk/guides/github-workflows/pr-review

Step 1: Create the workflow file

Create .github/workflows/pr-review.yml in the target repo. Fetch the latest example from https://docs.all-hands.dev/sdk/guides/github-workflows/pr-review and use it as the starting template. The workflow calls the OpenHands/extensions/plugins/pr-review composite action directly.

Step 2: Configure the LLM

Ask the user whether they are using the OpenHands app (app.all-hands.dev) or their own LLM provider (e.g. Anthropic, OpenAI directly).

OpenHands app (default)

OpenHands app users already have access to an LLM API key through the OpenHands litellm proxy. Tell them:

Go to https://app.all-hands.dev → Account → API Keys → OpenHands LLM Key, and copy your key. Then add it as a GitHub repository secret: Settings → Secrets and variables → Actions → New repository secret. Name it LLM_API_KEY.

Set these inputs in the workflow with: block:

  • llm-model: litellm_proxy/claude-sonnet-4-5-20250929
  • llm-base-url: https://llm-proxy.app.all-hands.dev

Own LLM provider

If the user has their own API key (e.g. from Anthropic or OpenAI), tell them to add it as a repository secret named LLM_API_KEY using the same path above. Leave llm-base-url unset and set llm-model to the provider-prefixed model name (e.g. anthropic/claude-sonnet-4-5-20250929).

You cannot create secrets — the user must do it manually. Do not ask for the key value. Just tell them where to put it.

Step 3: Ask the user for preferences

Present these options and apply any requested changes to the workflow file:

Review style (default: roasted)

  • roasted — Linus Torvalds-style, blunt, focuses on data structures and simplicity.
  • standard — balanced, covers style/readability/security.

When to trigger (default: on-demand only)

  • On-demand: add review-this label or request openhands-agent as reviewer.
  • Automatic: review every new PR. Add opened and ready_for_review to on.pull_request.types and matching conditions to the if: block.

Read the full file on GitHub · 73 lines

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. 2d ago First seen · 73 lines · 44 tokens per session scan A 70b8d5fb4461

Subscribe to this mod's changes

setup-pr-review is a skill published in the GitHub repository OpenHands/extensions (137 stars, last pushed 4d ago), licensed MIT. It adds 44 tokens to every session and 730 once invoked, about $0.0002 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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