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-performancegit 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-performance)<a href="https://agentmods.dev/skills/s977043/river-review/river-review-performance"><img src="https://agentmods.dev/badge/skills/s977043/river-review/river-review-performance/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-performance"><img src="https://agentmods.dev/badge/skills/s977043/river-review/river-review-performance.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 | $0.00049 | $0.01836 |
| Opus 5.5 | $0.00020 | $0.00734 |
| Sonnet 5.5 | $0.00010 | $0.00367 |
| Haiku 4.5 | $0.00005 | $0.00184 |
Grade A, and why
river-review-performance 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 1mo 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 — 137 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Performance Review（パフォーマンスレビュー）
パフォーマンス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
- データベースクエリの追加・変更時
- ループ処理やバッチ処理の変更時
- キャッシュ戦略の変更時
- 大量データの処理ロジック変更時
Routing / ルーティング
| キーワード | スキルID | 説明 |
|---|---|---|
| キャッシュ, TTL | cache-strategy-consistency |
参照のみ。実行は river-review-architecture（理由） |
| 障害, 監視, メトリクス | failure-modes-observability |
障害モードと可観測性 |
| ログ, トレース | logging-observability |
ロギング・可観測性 |
| SLO, レイテンシ | operability-slo |
運用性・SLO |
cache-strategy-consistency の帰属について
cache-strategy-consistency はキャッシュ戦略という語感から performance の懸念に見えるが、実体は設計ドキュメント（docs/spec/RFC 等）のキャッシュ戦略記述をレビューする upstream スキル（applyTo が docs/**/*.md 等の docs 系のみ、Pre-execution Gate も「差分に設計ドキュメントの変更がある」ことを要求）である。本エントリ（phase midstream、applyTo が code/sql）とはドメインが異なるため、ドメイン一貫性を優先し実行は river-review-architecture（phase upstream、docs 系 applyTo を保有）に据え置く。本表には到達性のための参照行として掲載するのみで、performance 側に重複するアクティブなキーワードルートは追加しない。
デフォルト動作
- キーワード指定なし → 以下のヒューリスティクスで判定:
- ループ内I/O → N+1クエリ検出
- 大量データ処理 → メモリ効率チェック
- 外部API呼び出し → タイムアウト・リトライ検証
Execution Flow / 実行フロー
1. 変更内容の分析
├─ ループ内I/O → N+1クエリ検出を優先
├─ 大量データ処理 → メモリ効率チェックを優先
├─ 外部API呼び出し → タイムアウト・リトライ検証を優先
└─ キーワード指定あり → 該当スキルを直接選択
2. スキルの実行
├─ cache-strategy-consistency: キャッシュ戦略の一貫性
├─ failure-modes-observability: 障害モードと可観測性
├─ logging-observability: ロギング・可観測性
└─ operability-slo: 運用性・SLO
3. 統合
├─ 重複する指摘の除去
└─ Checklistに基づくパフォーマンスチェックの補完
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.
- 1mo ago First seen · 137 lines · 49 tokens per session scan A e78e651a6793
river-review-performance is a skill published in the GitHub repository s977043/river-review (7 stars, last pushed yesterday), licensed MIT. It adds 49 tokens to every session and 1,836 once invoked, about $0.0002 per session on Opus 5.5. 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.
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