Borrowing it
Nothing to install: this file belongs to abeyuya/actions-mention-to-slack. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/abeyuya/actions-mention-to-slack/master/.claude/skills/post-pr-review/SKILL.mdgit clone --depth 1 https://github.com/abeyuya/actions-mention-to-slackWrote 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.
[](https://agentmods.dev/skills/abeyuya/actions-mention-to-slack/post-pr-review)<a href="https://agentmods.dev/skills/abeyuya/actions-mention-to-slack/post-pr-review"><img src="https://agentmods.dev/badge/skills/abeyuya/actions-mention-to-slack/post-pr-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.
<a href="https://agentmods.dev/skills/abeyuya/actions-mention-to-slack/post-pr-review"><img src="https://agentmods.dev/badge/skills/abeyuya/actions-mention-to-slack/post-pr-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00078 | $0.01369 |
| Opus 5 | $0.00039 | $0.00685 |
| Sonnet 5 | $0.00016 | $0.00274 |
| Haiku 4.5 | $0.00008 | $0.00137 |
Grade A, and why
post-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 13d 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.
How it starts
The opening of the file, as written. The whole thing — 86 lines — stays where its author put it; the contents beside it link to each section on GitHub.
post-pr-review skill
PR レビュー結果を 1回の API コールで「1つの Review」として投稿 する手順を提供する skill。 人間レビュアーの "Submit Review" と同じ構造で投稿する。
守ること
- レビュー結果は 必ず1回の API コール で投稿する。
- 個別投稿系のツール (
mcp__github_inline_comment__create_inline_comment、gh pr comment等) は 使わない。 eventは 常にCOMMENT。APPROVE/REQUEST_CHANGESは使わない (Bot がマージブロックや承認権を持つことを避けるため)。- インラインコメントの本文フォーマット (重要度ラベル等) は caller のレビュー方針に従う。本 skill は手続きのみを担い、レビュー文面の規約は規定しない。
- 総括
bodyの先頭には AI 自動投稿マーカーを必ず付与する (詳細は「手順 1」参照)。認証主体が人間 PAT でも投稿内容は AI 生成であることを明示するため。caller 側で事前に付与する必要はなく、本 skill が一律に prepend する。エージェント名 (Claude Code / Codex / Cursor 等) はマーカーに含めない (本 skill は複数の AI エージェントから呼ばれうる前提)。
入力 (caller から prompt 経由で渡される想定)
OWNER/REPO/PR_NUMBER: 対象 PR の識別情報- レビュー本文 (総括 + インラインコメント配列)
COMMIT_ID(任意): レビューを紐づける head commit の SHA。caller 側でgh pr view ... --json commitsの末尾oidを取得できる場合は渡すことを推奨。指定があれば手順 1 の JSON および手順 2 の API リクエストに含める (force-push / rebase で行ズレが起きた際の誤コメント防止に有効)。未指定なら省略 (GitHub 側で最新 commit を採用)。
手順
1. body 先頭に AI 自動投稿マーカーを付与し、/tmp/review.json を Write ツールで書き出す
heredoc や cat リダイレクトは使わず、必ず Write ツールで書く。
caller から渡された総括本文 (Markdown 可) はマーカーと区切り線 (---) の後ろに連結する。指摘なしの場合 (comments が []) も同じマーカーを付ける。
マーカー文言 (エージェント非依存・固定):
> **[AI 自動投稿]** このレビューは AI エージェントによって自動生成されました。レビュー内容の判断は AI が行っています。
---
<caller から渡された総括本文 (指摘なし時は「特に指摘なし」相当)>
スキーマは以下のとおり (body は上記マーカー込みの文字列):
{
"commit_id": "9f8e7d6c1a2b3c4d5e6f7890abcdef1234567890",
"body": "> **[AI 自動投稿]** このレビューは AI エージェントによって自動生成されました。レビュー内容の判断は AI が行っています。\n\n---\n\n総括コメント本文 (Markdown可)",
"event": "COMMENT",
"comments": [
{
"path": "src/example.ts",
"line": 42,
"side": "RIGHT",
"body": "[should] ここの処理は..."
},
{
"path": "src/example.ts",
"start_line": 50,
"start_side": "RIGHT",
"line": 55,
"side": "RIGHT",
"body": "[must] この複数行ブロックは..."
}
]
}
- 単一行コメントは
path/line/sideを指定する。 - 複数行範囲のコメントは上記に加えて
start_line/start_sideを併用する (start_lineはlineより前の行)。 commit_idは caller からCOMMIT_IDが渡された場合のみ含める (詳細は「入力」参照)。- 指摘がない場合:
bodyはマーカー + 区切り線 + 「特に指摘なし」相当の文言、commentsは[]、eventはCOMMENTで投稿する。 - インラインコメント (
comments[].body) には個別マーカーを付けない (Review 本文側のマーカーで帰属は十分であり、[must]等の重要度ラベルとの衝突や冗長さも避けるため)。
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.
- 13d ago First seen · 86 lines · 78 tokens per session scan A 5802f437a6ac
post-pr-review is a skill published in the GitHub repository abeyuya/actions-mention-to-slack (58 stars, last pushed yesterday), licensed MIT. It adds 78 tokens to every session and 1,369 once invoked, about $0.0004 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.
Other skills, from other repositories
robin
Use whenever an agent creates, updates, reviews, or completes a GitHub pull request. Detect whether Robin is installed in the repository; when it is, automatically drive the PR through a bounded review, verified-fix, reply, thread-resolution, re-review, authorized-merge, and cleanup loop without requiring the user to…
bellwether
Bring the current PR to a mergeable state: CI green, all review comments resolved, no merge conflicts. Self-contained — watches CI, fixes issues, watches again until merge-ready. Use when the user wants to keep a PR green, auto-fix CI, resolve review comments, or says "get this merged".
pr-review
AI-assisted review of one or more GitHub Pull Requests. Offloads deterministic checks (lint, complexity, duplication, security, perf) to repo linters via self-contained scripts, then applies LLM judgment to what linters cannot catch and posts high-signal findings after a single human approval. Pass one or many PRs…
pr-address-comments
Read a remote GitHub PR's review comments, implement fixes on the PR branch, then reply to and resolve addressed threads (REST reply + GraphQL resolveReviewThread). Use for /pr-address-comments, a single PR URL or number, when not using the parallel batch skill pr-address-comments-all. Requires gh and a git checkout…
watch-pr
Watch a GitHub pull request for CI status, reviews, comments, merge conflicts, and terminal states using the gh-watch extension. Use when the user wants to monitor a PR, wait for CI, or track PR progress.
manage-merge-queue
Prepare, review, enqueue, and land GitHub pull requests through a provider-neutral agent merge queue. Use when a PR becomes ready, configured review feedback must be addressed, the user says deploy, or queued changes need safe conflict-aware ordering.