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 river-review-securitygit 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/river-review-security)<a href="https://agentmods.dev/skills/s977043/river-review/river-review-security"><img src="https://agentmods.dev/badge/skills/s977043/river-review/river-review-security/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/river-review-security"><img src="https://agentmods.dev/badge/skills/s977043/river-review/river-review-security.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 | $0.00055 | $0.00805 |
| Opus 5 | $0.00028 | $0.00402 |
| Sonnet 5 | $0.00011 | $0.00161 |
| Haiku 4.5 | $0.00006 | $0.00081 |
Grade A, and why
river-review-security 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 10d 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.
What it actually says
Security Review（セキュリティレビュー）
セキュリティに影響する変更を検出し、適切な個別スキルで検証する。
When to Use / いつ使うか
- 認証・認可に関わるコード変更時
- 外部入力の処理ロジック変更時
- 機密データの取り扱い変更時
- セキュリティ関連の設定変更時
Routing / ルーティング
| キーワード | スキルID | 説明 |
|---|---|---|
| 脆弱性, XSS, SQLi, インジェクション | security-basic |
基本セキュリティチェック |
| プライバシー, 個人情報, GDPR | security-privacy-design |
プライバシー設計 |
| 認可, 権限, アクセス制御 | trust-boundaries-authz |
信頼境界・認可設計 |
デフォルト動作
- キーワード指定なし →
security-basicを実行 - セキュリティ関連ファイル（auth/, middleware/）→ 全スキル実行
Execution Flow / 実行フロー
1. 変更内容の分類
├─ 認証・認可コード → trust-boundaries-authz を優先
├─ データ処理コード → security-privacy-design を優先
└─ 一般コード → security-basic を実行
2. 各スキルの実行
├─ security-basic: OWASP Top 10チェック
├─ security-privacy-design: プライバシー影響分析
└─ trust-boundaries-authz: 認可モデル検証
3. 統合サマリの生成
Output Format / 出力形式
<file>:<line>: <message>
- Finding: 何が問題か（1文）
- Severity: critical / major / minor
- Impact: 何が困るか（短く）
- Fix: 次の一手（最小の修正案）
他スキルとの関係
| スキル | 関係 | 棲み分け |
|---|---|---|
adversarial-review (War Game) |
補完 | security は既知パターン検出、War Game は未知の攻撃経路発見 |
river-review-architecture |
補完 | security は「脆弱性」、architecture は「構造的安全性」 |
References
- ROUTING.md: 詳細なルーティングルール
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.
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.
- 10d ago First seen · 83 lines · 55 tokens per session scan A 82e929655560
river-review-security is a skill published in the GitHub repository s977043/river-review (3 stars, last pushed yesterday), licensed MIT. It adds 55 tokens to every session and 805 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 2026-08-31.
Other skills, from other repositories
review-all
Multi-agent code review for diffs (project-agnostic). Covers standards, bugs, security, DRY, smells, perf, tests, API contracts, a11y/i18n. Verifies each finding to eliminate false positives. Use for /review-all, pre-PR/pre-commit review, or auditing uncommitted/staged changes.
logic-health
Sweep a directory, module, or full codebase for logic correctness and produce a scored health dashboard with systemic patterns. Trigger when the user requests a health view — "audit the whole codebase", "health check", "health overview", "logic health overview", "audit src/", "audit auth and payments modules", "where…
logic-diff
Compare two code versions for semantic equivalence via semi-formal tracing of both versions side-by-side. Trigger when the user shares a refactor, rewrite, migration, or A/B implementation and wants to confirm behavior is unchanged — "did I break anything", "is this equivalent", "are these equivalent", "semantically…
omnicheck-gitlab
Use when checking if MR review findings have been applied — verifies both OmniForge-generated and human reviewer comments against the current diff, posts nudge replies on unaddressed threads.
omnicheck-github
Use when checking if PR review findings have been applied — verifies both OmniForge-generated and human reviewer comments against the current diff, posts nudge replies on unaddressed threads.
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.