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 loulanyue/awesome-claude-notes --skill iterative-retrievalgit clone --depth 1 https://github.com/loulanyue/awesome-claude-notesWrote 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/loulanyue/awesome-claude-notes/iterative-retrieval)<a href="https://agentmods.dev/skills/loulanyue/awesome-claude-notes/iterative-retrieval"><img src="https://agentmods.dev/badge/skills/loulanyue/awesome-claude-notes/iterative-retrieval/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/loulanyue/awesome-claude-notes/iterative-retrieval"><img src="https://agentmods.dev/badge/skills/loulanyue/awesome-claude-notes/iterative-retrieval.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Agent Snooping · line 4 Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
- medium Agent Snooping · line 206 Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
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 | $0.00042 | $0.02046 |
| Opus 5 | $0.00021 | $0.01023 |
| Sonnet 5 | $0.00008 | $0.00409 |
| Haiku 4.5 | $0.00004 | $0.00205 |
Grade A, and why
iterative-retrieval 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 7d 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 — 212 lines — stays where its author put it; the contents beside it link to each section on GitHub.
反復検索パターン
マルチエージェントワークフローにおける「コンテキスト問題」を解決します。サブエージェントは作業を開始するまで、どのコンテキストが必要かわかりません。
問題
サブエージェントは限定的なコンテキストで起動されます。以下を知りません:
- どのファイルに関連するコードが含まれているか
- コードベースにどのようなパターンが存在するか
- プロジェクトがどのような用語を使用しているか
標準的なアプローチは失敗します:
- すべてを送信: コンテキスト制限を超える
- 何も送信しない: エージェントに重要な情報が不足
- 必要なものを推測: しばしば間違い
解決策: 反復検索
コンテキストを段階的に洗練する4フェーズのループ:
┌─────────────────────────────────────────────┐
│ │
│ ┌──────────┐ ┌──────────┐ │
│ │ DISPATCH │─────▶│ EVALUATE │ │
│ └──────────┘ └──────────┘ │
│ ▲ │ │
│ │ ▼ │
│ ┌──────────┐ ┌──────────┐ │
│ │ LOOP │◀─────│ REFINE │ │
│ └──────────┘ └──────────┘ │
│ │
│ 最大3サイクル、その後続行 │
└─────────────────────────────────────────────┘
フェーズ1: DISPATCH
候補ファイルを収集する初期の広範なクエリ:
// 高レベルの意図から開始
const initialQuery = {
patterns: ['src/**/*.ts', 'lib/**/*.ts'],
keywords: ['authentication', 'user', 'session'],
excludes: ['*.test.ts', '*.spec.ts']
};
// 検索エージェントにディスパッチ
const candidates = await retrieveFiles(initialQuery);
フェーズ2: EVALUATE
取得したコンテンツの関連性を評価:
function evaluateRelevance(files, task) {
return files.map(file => ({
path: file.path,
relevance: scoreRelevance(file.content, task),
reason: explainRelevance(file.content, task),
missingContext: identifyGaps(file.content, task)
}));
}
スコアリング基準:
- 高(0.8-1.0): ターゲット機能を直接実装
- 中(0.5-0.7): 関連するパターンや型を含む
- 低(0.2-0.4): 間接的に関連
- なし(0-0.2): 関連なし、除外
フェーズ3: REFINE
評価に基づいて検索基準を更新:
function refineQuery(evaluation, previousQuery) {
return {
// 高関連性ファイルで発見された新しいパターンを追加
patterns: [...previousQuery.patterns, ...extractPatterns(evaluation)],
// コードベースで見つかった用語を追加
keywords: [...previousQuery.keywords, ...extractKeywords(evaluation)],
// 確認された無関係なパスを除外
excludes: [...previousQuery.excludes, ...evaluation
.filter(e => e.relevance < 0.2)
.map(e => e.path)
],
// 特定のギャップをターゲット
focusAreas: evaluation
.flatMap(e => e.missingContext)
.filter(unique)
};
}
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.
- 7d ago First seen · 212 lines · 42 tokens per session scan A f66bd6ed5153
iterative-retrieval is a skill published in the GitHub repository loulanyue/awesome-claude-notes (270 stars, last pushed 7d ago), licensed MIT. It adds 42 tokens to every session and 2,046 once invoked, about $0.0002 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.
Other skills, from other repositories
durable-session-state
Persist plans, scope decisions, evidence, and reviewer/critic verdicts to durable files during long or multi-phase tasks so work survives context compaction, session resumes, and handoffs. Use for swarm-mode tasks, before context grows large, when recording approval gates, and when resuming after compaction or a…
lane-memory
A file-based store for durable project facts that cannot be reliably inferred from source code or its module map.
fable-context-thrift
Use at the start of any multi-step task and during exploration — before reading files, searching, or re-checking completed work, especially when tempted to read whole files, re-verify known facts, or run independent lookups one at a time.
handoff
Structured session handoff — preserves context for seamless continuation across sessions.
lesson-learned
Extract learnings and save as memory files (file-based memory system). Use when: "lesson learned", "what did we learn", "learning", "remember".
context-budget
Analyzes where context tokens are being spent and identifies optimization opportunities. Use when sessions feel slow or context is running out.