Borrowing it
Nothing to install: this file belongs to satoh-y-0323/claude-code-conductor. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/satoh-y-0323/claude-code-conductor/main/.claude/skills/doc/SKILL.mdgit clone --depth 1 https://github.com/satoh-y-0323/claude-code-conductorWrote 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/satoh-y-0323/claude-code-conductor/doc)<a href="https://agentmods.dev/skills/satoh-y-0323/claude-code-conductor/doc"><img src="https://agentmods.dev/badge/skills/satoh-y-0323/claude-code-conductor/doc.svg" alt="Measured on agentmods" 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 | $0.00038 | $0.01539 |
| Opus 5 | $0.00019 | $0.00770 |
| Sonnet 5 | $0.00008 | $0.00308 |
| Haiku 4.5 | $0.00004 | $0.00154 |
Grade A, and why
doc 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 yesterday.
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 — 180 lines — stays where its author put it; the contents beside it link to each section on GitHub.
doc
ドキュメントを対話形式でヒアリングして生成する。 対話部分は親 Claude が担当し、生成は doc-writer エージェントが行う。
Step 1: ドキュメント種類の選択
AskUserQuestion ツール:
{
"questions": [{
"question": "作成するドキュメントの種類を選択してください",
"options": [
{ "label": "mermaid図", "description": "フロー図・クラス図・ER図・シーケンス図など" },
{ "label": "README", "description": "プロジェクト概要・セットアップ手順・使い方など" },
{ "label": "操作手順書・運用手順書", "description": "画面操作・コマンド手順など" },
{ "label": "API仕様書", "description": "エンドポイント・リクエスト/レスポンス定義など" }
]
}]
}
「その他」が選ばれた場合(Other 入力): 自由記述の内容をそのまま記録する。
Step 2: 対象ファイル・ディレクトリの指定
AskUserQuestion ツール:
{
"questions": [{
"question": "ドキュメント化する対象ファイル・ディレクトリを教えてください(例: src/api/、models/user.py)"
}]
}
Step 3: 読み手の確認
AskUserQuestion ツール:
{
"questions": [{
"question": "このドキュメントの読み手は誰ですか?",
"options": [
{ "label": "開発チームの新メンバー", "description": "コードを読み始める人" },
{ "label": "開発チーム内", "description": "既存メンバーへの共有・引継ぎ" },
{ "label": "運用・保守担当", "description": "エンジニアだがコードを書かない" },
{ "label": "業務担当・非エンジニア", "description": "システムの利用者・管理者" }
]
}]
}
「外部レビュアー・顧客・発注者」や「その他」が選ばれた場合(Other 入力): 自由記述の内容をそのまま記録する。
Step 4: 目的の確認
AskUserQuestion ツール:
{
"questions": [{
"question": "このドキュメントを作る目的を教えてください",
"options": [
{ "label": "全体把握・初見理解のため" },
{ "label": "引継ぎ・担当交代のため" },
{ "label": "レビュー・承認を得るため" },
{ "label": "障害時の調査・対応のため" }
]
}]
}
「新メンバーのオンボーディング」や「その他」が選ばれた場合(Other 入力): 自由記述の内容をそのまま記録する。
Step 5: 粒度の確認
mermaid図が選ばれた場合: 必須。 それ以外の場合: AskUserQuestion で確認する(不要であれば Other で「指定なし」と入力してもらう)。
AskUserQuestion ツール:
{
"questions": [{
"question": "どのレベルの粒度で記述しますか?",
"options": [
{ "label": "高レベル", "description": "モジュール・サービス単位。全体の流れを一目で把握できる" },
{ "label": "中レベル", "description": "クラス・関数単位。主要な処理の繋がりがわかる" },
{ "label": "低レベル", "description": "メソッド・フィールド単位。詳細な実装がわかる" }
]
}]
}
Step 6: 出力先の確認
AskUserQuestion ツール:
{
"questions": [{
"question": "ドキュメントの出力先を選択してください",
"options": [
{ "label": "レポートとして保存", "description": ".claude/reports/doc-{名前}.md に保存(一時保管)" },
{ "label": "プロジェクト内の指定パスに保存", "description": "次の入力でパスを指定する(例: docs/architecture.md)" },
{ "label": "ここに表示するだけ", "description": "ファイル保存せずチャットに出力" }
]
}]
}
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.
- yesterday First seen · 180 lines · 38 tokens per session scan A 85d3ad9c1606
doc is a skill published in the GitHub repository satoh-y-0323/claude-code-conductor (1 stars, last pushed 2d ago), licensed MIT. It adds 38 tokens to every session and 1,539 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 2026-09-04.
Other skills, from other repositories
pdf-processor
Extracts text and tables from PDF files, fills forms, and merges documents. Use when working with PDF files or when the user mentions PDFs, forms, or document extraction.
stream-chain
Stream-JSON chaining for multi-agent pipelines, data transformation, and sequential workflows.
agent-orchestrator
Meta-skill que orquestra todos os agentes do ecossistema. Scan automatico de skills, match por capacidades, coordenacao de workflows multi-skill e registry management.
foundry-hosted-agent-validation
Step-by-step process for validating a Python Foundry hosted agent sample (under python/samples/04-hosting/foundry-hosted-agents/) end to end — running it locally (native runtime and azd ai agent run) and after deploying it to an Azure AI Foundry project with azd. Use this when asked to validate a hosted agent sample.
doc-reader
Read any common document/data file — PDF, Word (.docx), Excel (.xlsx/.xls), PowerPoint (.pptx), images (OCR), CSV/TSV, plain text, JSON/YAML/TOML, HTML/XML, and most source-code files. Use the readdocument tool.
csv-workbench
Analyze CSV files in /mnt/data and return concise numeric summaries.