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 eaglesakura/agent-skills --skill markdown-searchgit clone --depth 1 https://github.com/eaglesakura/agent-skillsWrote 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/eaglesakura/agent-skills/markdown-search)<a href="https://agentmods.dev/skills/eaglesakura/agent-skills/markdown-search"><img src="https://agentmods.dev/badge/skills/eaglesakura/agent-skills/markdown-search/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/eaglesakura/agent-skills/markdown-search"><img src="https://agentmods.dev/badge/skills/eaglesakura/agent-skills/markdown-search.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 | $0.00162 | $0.01727 |
| Opus 5.5 | $0.00065 | $0.00691 |
| Sonnet 5.5 | $0.00032 | $0.00345 |
| Haiku 4.5 | $0.00016 | $0.00173 |
Grade A, and why
markdown-search scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 116 lines — stays where its author put it; the contents beside it link to each section on GitHub.
ドキュメント検索(Context 最適化)
実装・設計・レビューの前に、既存ドキュメントから必要最小限だけを Context に載せる SKILL である。 全文をいきなり読まず、見出し一覧(行範囲)→ 指定範囲 →(必要なら)全文 の順で深さを上げる。
段階の意図は references/context-loading.md を参照する。
いつ使うか
- コーディング・詳細設計・レビュー前のナレッジ収集
- 「どこに書いてあるか」を探すとき
### DO:/### DO NOT:を横断したいとき- 大きな
*.mdを読む前に構造だけ把握したいとき
優先して見る配置
リポジトリルート(.git があるディレクトリ)からの相対パス:
AGENTS.mdやRule/Instructionによって指定されたプロジェクト固有ディレクトリdocs/: 標準ドキュメントディレクトリREADME.md: 標準README.cursor/skills/.agents/skills/apm_modules/.ai-agent/memory/(場所はworkspace-layout/ 用途はworkspace-agent-temporary)
同梱スクリプト
行範囲付き TOC と範囲抽出は、この SKILL の scripts/md_section.py を使う(Python 3 / 標準ライブラリのみ)。
SKILL_DIR は本 SKILL.md があるディレクトリ(.cursor/skills/・.agents/skills/・packages/.../.apm/skills/ いずれでも可)。
SCRIPT="$SKILL_DIR/scripts/md_section.py"
# Stage 1: 見出し + 行範囲(子見出しを含む終端)
# 内容 SHA-256 が同一のファイルは、先に現れた 1 件だけ対象にする(コピー二重ロード防止)
python3 "$SCRIPT" toc path/to/file.md
python3 "$SCRIPT" toc --max-level 2 path/to/dir
python3 "$SCRIPT" toc --grep 'DO NOT' path/to/file.md
# 内容重複を落とした path 一覧だけ欲しいとき
python3 "$SCRIPT" unique path/to/directory
python3 "$SCRIPT" unique -v path/a.md path/b.md # 除外した path を stderr に出す
# Stage 2: 指定範囲だけ出力
python3 "$SCRIPT" print path/to/file.md 629 637
python3 "$SCRIPT" print path/to/file.md --at 675
python3 "$SCRIPT" print path/to/file.md --title '循環参照'
path:start-end が既に分かっているときは sed -n 'start,endp' file でもよい。
コードフェンス内の # は見出し扱いにしない。終端は同レベル以上の次見出しの直前(末尾空行は trim)。
toc / unique は既定で内容ハッシュ重複を除外する。意図的に全コピーを見たいときだけ toc --keep-duplicates を使う。
把握手順(3 段階)
Stage 1 — 見出し一覧と行範囲を取る
- 対象 path(ファイルまたは少数の候補)を決め、TOC を取る
- 複数ファイル横断の当たり付けは
--max-level 2から始め、必要ならレベルを下げる - 出力の
path:start-endと見出しテキストだけで関連性を判断する(この時点で本文を読まない) - HQ / APM で同内容が複数 path にコピーされていることがある。内容ハッシュが一致するファイルは先頭 1 件だけを候補にし、以降の Stage でも同じ本文を二重ロードしない
DO / DO NOT を探すときも、まず TOC か見出し grep で当たりを付ける。
横断検索の前に unique で重複を落とし、一致する内容は最初の 1 ファイルだけを対象にする:
What ships with it
3 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.
- 2mo ago First seen · 116 lines · 162 tokens per session scan A 976ee7728a01
markdown-search is a skill published in the GitHub repository eaglesakura/agent-skills (2 stars, last pushed 1mo ago), licensed MIT. It adds 162 tokens to every session and 1,727 once invoked, about $0.0006 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.
markdown-search compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| markdown-searcheaglesakura/agent-skills | Skill | 2 | 1mo ago | MIT | A | 162 | Claude Code, Codex |
| imagegenopenai/codex | Skill | 134k | today | Apache-2.0 | A | 113 | Codex |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | today | MIT | A | 200 | Claude Code, Codex |
| playwright-climicrosoft/playwright | Skill | 99k | today | Apache-2.0 | A | 19 | Claude Code |
| systematic-debuggingobra/superpowers | Skill | 314k | 4d ago | MIT | A | 21 | Claude Code |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | today | MIT | A | 95 | Claude Code |
| chat-pet-sprite-creationmicrosoft/vscode | Skill | 195k | today | MIT | A | 53 | Claude Code, Codex |