review-pr

A multi-agent review process for a GitHub pull request, which is a proposed set of code changes awaiting review.

In plain words
What is it for?
Use it to review a pull request by number or URL, with an option to skip most interactive questions.
Why use it?
It checks the proposed changes from several specialized viewpoints and can publish structured feedback on GitHub.

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/etr/groundwork/review-pr
Any agent
npx skills add etr/groundwork --skill review-pr
Clone the repo
git clone --depth 1 https://github.com/etr/groundwork

Made for: Claude Code, Codex.

Per session 40 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,238 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 $0.00040 $0.04238
Opus 5 $0.00020 $0.02119
Sonnet 5 $0.00008 $0.00848
Haiku 4.5 $0.00004 $0.00424

Measured 2d ago against content hash 41b518aab8c5, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, 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 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.

skills/review-pr/SKILL.md · 421 lines

How it starts

The opening of the file, as written. The whole thing — 421 lines — stays where its author put it; the contents beside it link to each section on GitHub.

PR Review Skill

Multi-agent PR review that runs specialized agents against PR changes and posts structured feedback to GitHub.

Non-Interactive Mode Detection

Check for non-interactive mode from either source:

  1. If the argument string contains --no-interactive → strip it from the argument before PR number parsing, set non_interactive = true
  2. If session context contains GROUNDWORK_BATCH_MODE=true → set non_interactive = true

If either condition is met, all AskUserQuestion prompts below are replaced with their documented auto-decision — except the pre-flight model check, which always prompts.

Pre-flight: Model Recommendation

Your current effort level is {{effort_level}}.

Skip this step silently if effort is high, xhigh, or max (the scale is low < medium < high < xhigh < max, so xhigh and max are already above high) AND you are Sonnet or Opus. If effort is low or medium (i.e. below high), you MUST show the recommendation prompt — regardless of model. If you are not Sonnet or Opus, you MUST show the recommendation prompt - regardless of effort level.

Otherwise → always prompt (even in non-interactive mode) using AskUserQuestion:

{
  "questions": [{
    "question": "Do you want to switch? Multi-agent orchestration and deduplication judgment across 6-8 agents benefits from consistent reasoning.\n\nTo switch: cancel, run `/effort high` (and `/model sonnet` if on Haiku), then re-invoke this skill.",
    "header": "Recommended: Sonnet or Opus at high effort",
    "options": [
      { "label": "Continue" },
      { "label": "Cancel — I'll switch first" }
    ],
    "multiSelect": false
  }]
}

If the user selects "Cancel — I'll switch first": output the switching commands above and stop. Do not proceed with the skill.

Step 1: Parse PR Identifier

Extract the PR number from the user's input. Accept any of these formats:

  • Numeric: 42
  • With hash: #42
  • Full URL: https://github.com/owner/repo/pull/42

Read the full file on GitHub · 421 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. 2d ago First seen · 421 lines · 40 tokens per session scan A 41b518aab8c5

Subscribe to this mod's changes

review-pr is a skill published in the GitHub repository etr/groundwork (42 stars, last pushed 21d ago), licensed MIT. It adds 40 tokens to every session and 4,238 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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