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.
npx skills add s977043/river-review --skill war-gamegit clone --depth 1 https://github.com/s977043/river-reviewWrote 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/s977043/river-review/war-game)<a href="https://agentmods.dev/skills/s977043/river-review/war-game"><img src="https://agentmods.dev/badge/skills/s977043/river-review/war-game/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/s977043/river-review/war-game"><img src="https://agentmods.dev/badge/skills/s977043/river-review/war-game.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00050 | $0.01700 |
| Opus 5 | $0.00025 | $0.00850 |
| Sonnet 5 | $0.00010 | $0.00340 |
| Haiku 4.5 | $0.00005 | $0.00170 |
Grade A, and why
War Game 敵対的シミュレーション 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 6d 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 — 130 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Pattern declaration
Primary pattern: Reviewer Secondary patterns: Inversion Why: 攻撃シナリオ分析はチェックリスト型評価が主だが、攻撃面のない変更では実行を止めるゲートが必要
Goal / 目的
- 攻撃者の視点に立ち、変更がどのように悪用されうるかを具体的なシナリオとして描写することで、機能比較表やチェックリストでは見えない防御の盲点を発見する。
- 「自分がこのシステムを壊すとしたら、どこを突くか」を体系的に分析する。
Non-goals / 扱わないこと
- 既知の脆弱性パターンの機械的チェック(SQLi, XSS等は
security-basicの役割)。 - ペネトレーションテストの代替(実際の攻撃コードは生成しない)。
- ビジネスロジックの正当性判断。
Pre-execution Gate / 実行前ゲート
このスキルは以下の条件がすべて満たされない限りNO_REVIEWを返す。
- 差分にセキュリティ関連コード(api/, routes/, auth/, config/, middleware/等)の変更が含まれている
- テストコード・フィクスチャ・ドキュメントのみの変更ではない
- inputContextにdiffが含まれている
ゲート不成立時の出力: NO_REVIEW: war-game — 攻撃面を持つ変更が検出されない
False-positive guards / 抑制条件
- すでにセキュリティレビュー済みの箇所で、緩和策が差分内に確認できる場合は抑制。
Rule / ルール
攻撃者ペルソナ
変更内容に応じて、以下のペルソナの中から最も関連性の高いものを選択する:
- 外部攻撃者: 認証バイパス、入力操作、API悪用
- 認証済み悪意ユーザー: 権限昇格、他者データアクセス、レート制限回避
- 内部脅威者: 設定改ざん、ログ改竄、バックドア設置
- 自動化ボット: 大量リクエスト、クレデンシャルスタッフィング、スクレイピング
分析フレームワーク
- 攻撃面の特定: 変更が新たに露出する攻撃面(エンドポイント、入力、状態遷移)を列挙。
- 攻撃シナリオの構築: 選択したペルソナの立場で、具体的な攻撃手順を記述。
- 防御ギャップの評価: 現在の防御策と攻撃シナリオの間のギャップを特定。
- 防御策の提案: ギャップを埋める最小限の変更を提案。
制約
- 攻撃シナリオは最大 5 件。悪用可能性が高いものを優先。
- 各シナリオには「ペルソナ」「攻撃手順」「影響」「防御ギャップ」を含める。
- 実際の攻撃コードやエクスプロイトは生成しない。攻撃の概念と経路のみ記述。
Evidence / 根拠の取り方
- 攻撃面は差分の具体的な行に紐づける(
<file>:<line>)。 - 攻撃手順は入力→処理→出力の流れで追跡可能にする。
- 既知の攻撃手法(OWASP Top 10等)との対応を示す。
Output / 出力フォーマット
すべて日本語。
(war-game):1: [要約] 攻撃者視点で最も危険な露出は〈1文〉
<file>:<line>: [攻撃シナリオ1] <タイトル>
ペルソナ: <外部攻撃者|認証済み悪意ユーザー|内部脅威者|自動化ボット>
攻撃手順: <step1 → step2 → step3>
影響: <データ漏洩|サービス停止|権限昇格|...>
防御ギャップ: <現在の防御で不足している点>
Fix: <最小限の防御策>
<file>:<line>: [攻撃シナリオ2] ...
Good / Bad Examples
Good
src/api/routes/users.mjs:28: [攻撃シナリオ] IDOR によるユーザー情報の水平権限昇格
ペルソナ: 認証済み悪意ユーザー
攻撃手順: 自分のJWTで /api/users/:id の :id を他ユーザーIDに差し替え → レスポンスに他者のプロフィール情報
影響: 全ユーザーの個人情報漏洩
防御ギャップ: ルートハンドラ内でJWTのsubとリクエストの:idの一致を検証していない
Fix: ミドルウェアで req.user.id === params.id を検証、不一致は 403
Bad
What ships with it
2 files 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.
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.
- 6d ago First seen · 130 lines · 50 tokens per session scan A 017305ad689b
War Game 敵対的シミュレーション is a skill published in the GitHub repository s977043/river-review (3 stars, last pushed today), licensed MIT. It adds 50 tokens to every session and 1,700 once invoked, about $0.0003 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 2026-09-03.
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omnicreate-gitlab
Use when creating a GitLab merge request (OmniForge). Auto-populates title and description from commits, supports draft MRs, labels, assignees, reviewers, and issue linking.