egapro: Skill for Claude Code

.claude/skills/review/SKILL.md

review is a skill for Claude Code from SocialGouv/egapro. It costs 41 tokens per session (2,273 once invoked), scanned A, original, Apache-2.0.

A command for handling comments on pull requests, which are proposed code changes reviewed before merging. It detects whether the review concerns a feature, task, bug, or the current branch, then delegates fixes in a separate worktree.

In plain words
What is it for?
It is for fetching review comments, fixing requested changes, validating the result, pushing updates, and responding to reviewers.
Why use it?
It gathers unresolved feedback, applies changes, rechecks them, and replies to review threads without doing all the work in the main working directory.

Skill for Claude Code

Written for Claude Code: $ARGUMENTS substitution. Also seen: reads .claude/ paths; positional $N argument.

This is SocialGouv/egapro's own configuration. It tells Claude Code how to work on egapro itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything egapro configures →

Needs its repository: it runs a file that does not travel with it, so clone the repository first. The line is (cd "$WT_PATH" && bash scripts/setup-worktree.sh "$INDEX").

Reuse

Borrowing it

Nothing to install: this file belongs to SocialGouv/egapro. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/SocialGouv/egapro/alpha/.claude/skills/review/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/SocialGouv/egapro

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 review

README.md
[![agentmods](https://agentmods.dev/badge/skills/socialgouv/egapro/review/github.svg)](https://agentmods.dev/skills/socialgouv/egapro/review)
Your own site
<a href="https://agentmods.dev/skills/socialgouv/egapro/review"><img src="https://agentmods.dev/badge/skills/socialgouv/egapro/review/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

Your own site · 80×15
<a href="https://agentmods.dev/skills/socialgouv/egapro/review"><img src="https://agentmods.dev/badge/skills/socialgouv/egapro/review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 41 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,273 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. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 1 finding, up to high

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • high Privilege Escalation · line 121
    Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.
    Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
How audits are shown
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 $0.00041 $0.02273
Opus 5 $0.00020 $0.01137
Sonnet 5 $0.00008 $0.00455
Haiku 4.5 $0.00004 $0.00227

Measured 5d ago against content hash a2b726fbaded, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

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 5d 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/skills/review/SKILL.md · 194 lines

How it starts

The opening of the file, as written. The whole thing — 194 lines — stays where its author put it; the contents beside it link to each section on GitHub.

/review

Délègue à l'agent review-fixer dans un worktree dédié pour : lire les commentaires non résolus, appliquer les fixes, valider, push, répondre aux threads. Trois modes auto-détectés :

Mode Trigger Scope du review
epic Issue type Feature Toutes les sub-task PRs liées à la feature + la PR finale epic/<N> → alpha. Les fixes sont appliqués sur la branche d'intégration epic/<N> (les sub-tasks sont déjà squash-mergées dedans).
task Issue type Task La PR du ticket en review. Fixes sur la branche head du PR.
bug Issue type Bug La PR du bug en review. Fixes sur la branche head du PR.
(no-arg) Aucun argument, sur une branche de PR La PR de la branche courante (équivalent task/bug single-PR).

Globalement le fonctionnement reste identique au précédent /review : fetch, fix, re-validate, reply. La nouveauté c'est que le travail réel se passe dans un agent qui tourne en worktree (comme code-dev pour /implement), pas dans le main context.


Step 0 — Détecter le mode

ARG_HEAD="$(echo "$ARGUMENTS" | awk '{print $1}')"
case "$ARG_HEAD" in
  '#'[0-9]*|[0-9]*)
    ID="${ARG_HEAD#\#}"
    # ID peut être un issue number ou un PR number — on essaie d'abord issue
    ;;
  https://github.com/*/issues/*)
    ID="$(echo "$ARG_HEAD" | sed -E 's#.*/issues/([0-9]+).*#\1#')"
    ;;
  https://github.com/*/pull/*)
    ID="$(echo "$ARG_HEAD" | sed -E 's#.*/pull/([0-9]+).*#\1#')"
    IS_PR=1
    ;;
  *)
    ID=""
    ;;
esac

Cas A — argument fourni

  • Si l'argument est un numéro d'issue : gh issue view <ID> --json number,issueType,labels → brancher selon issueType.name (Feature/Task/Bug).
  • Si l'argument est un numéro de PR : gh pr view <ID> --json closingIssuesReferences → trouver l'issue liée → brancher selon son type.
  • Type absent ou ambigu → demander à l'utilisateur quel mode utiliser.

Cas B — pas d'argument

  • Si la branche courante est une PR branch (gh pr view --json number réussit) → mode task ou bug selon l'issue liée à cette PR. PR = la PR courante.
  • Sinon : lister les PRs ouvertes avec des reviews non adressées (gh pr list --state open --json number,title,reviewDecision --jq '.[] | select(.reviewDecision == "REVIEW_REQUIRED" or .reviewDecision == "CHANGES_REQUESTED")') et demander laquelle traiter.

Read the full file on GitHub · 194 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. 5d ago First seen · 194 lines · 41 tokens per session scan A a2b726fbaded

Subscribe to this mod's changes

review is a skill published in the GitHub repository SocialGouv/egapro (12 stars, last pushed today), licensed Apache-2.0. It adds 41 tokens to every session and 2,273 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 2026-09-04.

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