Flaky Test Risk Check

Flaky Test Risk Check is a skill for Claude Code from s977043/river-review. It costs 18 tokens per session (1,056 once invoked), scanned A, original, MIT.

A review check for tests that may give different results across runs. Such tests are often called flaky tests.

In plain words
What is it for?
It is for reviewing changed test files and suggesting fixes such as controlling timers, fixing random values, mocking network or database calls, isolating test data, and cleaning up after each test.
Why use it?
It helps identify tests that depend on timing, random values, the current time, external services, shared state, or execution order, so failures are less likely to be misleading.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the river-review plugin — 138 skills, 18 commands, 5 agents, 3 hooks shipped together

Good fit It is for reviewing changed test files and suggesting fixes such as controlling timers, fixing random values, mocking network or database calls, isolating test data, and cleaning up after each test.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/s977043/river-review/flaky-test
Install

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.

Any agent
npx skills add s977043/river-review --skill flaky-test
Clone the repo
git clone --depth 1 https://github.com/s977043/river-review

Made for: Claude Code.

Or install river-review, the plugin that ships this one along with the rest of its 138 skills, 18 commands, 5 agents, 3 hooks.

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 Flaky Test Risk Check

README.md
[![agentmods](https://agentmods.dev/badge/skills/s977043/river-review/flaky-test.svg)](https://agentmods.dev/skills/s977043/river-review/flaky-test)
Your own site
<a href="https://agentmods.dev/skills/s977043/river-review/flaky-test"><img src="https://agentmods.dev/badge/skills/s977043/river-review/flaky-test.svg" alt="Measured on agentmods" height="20"></a>
Per session 18 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,056 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.
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 $0.00018 $0.01056
Opus 5 $0.00009 $0.00528
Sonnet 5 $0.00004 $0.00211
Haiku 4.5 $0.00002 $0.00106

Measured 8d ago against content hash 819a73bda850, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

Flaky Test Risk Check 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 8d 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.

skills/downstream/flaky-test/SKILL.md · 87 lines

What it actually says

Pattern declaration

Primary pattern: Reviewer Secondary patterns: Inversion Why: Flakyテストリスク検出はチェックリスト型評価が主だが、テストファイルが差分に含まれない場合は実行を止める必要がある。

Rule / ルール

  • テストを決定的にし、実行順や環境依存を避ける。
  • タイミング依存(sleep/timeout)、乱数、時刻依存のまま放置しない。
  • ネットワークや外部サービス呼び出しはモック/スタブに置き換える。

Heuristics / 判定の手がかり

  • setTimeout/sleep/waitFor で待ち時間を固定している。
  • Math.random()/Date.now()/new Date() をシード・固定値なしで使っている。
  • ネットワーク/DB/ファイル I/O への直接依存がある(モックが無い)。
  • 並列実行で共有状態を操作している、またはテスト順序に依存している。
  • await の Promise が残っている、cleanup が afterEach で行われていない。

Good / Bad Examples

  • Good: vi.useFakeTimers(); jest.runAllTimers(); でタイマーを制御。
  • Good: Math.random = () => 0.42; などで乱数を固定。
  • Bad: await sleep(1000); に依存するテスト。
  • Bad: 実際の外部 API を呼ぶ統合テストをユニットテストに混在させる。

Actions / 改善案

  • タイマー/日時/乱数をモックし、シードを固定する。
  • ネットワーク・DB・外部サービスをモック/スタブ化し、リトライやバックオフをテストしない。
  • 共有状態を隔離し、beforeEach/afterEach でクリーンアップする。
  • 並列実行に耐えるようテストデータを分離し、副作用を最小化する。

Non-goals / 扱わないこと

  • E2E/負荷試験の設計や実行環境のチューニング。
  • テストフレームワークの全面移行。
  • 監視/アラートの設計。

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。

  • 差分にテストファイル(*.test.*, *.spec.*, tests/**/*)の変更が含まれている
  • 差分にテストの実行内容に影響する変更がある(コメントや説明文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: flaky-test — Flakyテストリスク検出の対象となるテスト変更が検出されない

False-positive guards / 抑制条件

  • テスト対象が純粋関数で、時間・乱数・外部I/Oを一切使っていない。
  • すでにフェイクタイマー/固定シードが導入済みで、差分で逸脱がない。

評価指標(Evaluation)

  • 合格基準: 指摘が差分に紐づき、根拠と次アクションが説明されている。
  • 不合格基準: 差分と無関係な指摘、根拠のない断定、抑制条件の無視。

人間に返す条件(Human Handoff)

  • 仕様や意図が不明確で解釈が分かれる場合は質問として返す。
  • 影響範囲が広い設計判断やトレードオフは人間レビューへ返す。
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. 8d ago First seen · 87 lines · 18 tokens per session scan A 819a73bda850

Subscribe to this mod's changes

Flaky Test Risk Check is a skill published in the GitHub repository s977043/river-review (3 stars, last pushed today), licensed MIT. It adds 18 tokens to every session and 1,056 once invoked, about $0.0001 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.

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