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 KunanonJ/ai-skills-hub --skill codebase-onboardinggit clone --depth 1 https://github.com/KunanonJ/ai-skills-hubWrote 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/kunanonj/ai-skills-hub/codebase-onboarding)<a href="https://agentmods.dev/skills/kunanonj/ai-skills-hub/codebase-onboarding"><img src="https://agentmods.dev/badge/skills/kunanonj/ai-skills-hub/codebase-onboarding.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 | $0.00086 | $0.00605 |
| Opus 5 | $0.00043 | $0.00302 |
| Sonnet 5 | $0.00017 | $0.00121 |
| Haiku 4.5 | $0.00009 | $0.00060 |
Grade A, and why
codebase-onboarding 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.
What it actually says
コードベースオンボーディング
体系的に不慣れなコードベースを分析し、構造化オンボーディングガイドを作成。新しいプロジェクトに参加するか、既存リポでClaude Codeを初めてセットアップする開発者向けに設計。
使用時期
- Claude Codeでプロジェクトを初めて開く
- 新しいチームまたはリポに参加
- ユーザーが「このコードベースを理解する手助けをしてください」と求める
- ユーザーがプロジェクトのCLAUDE.mdを生成するよう要求
- ユーザーが「オンボード」または「このリポを説明」と言う
動作方法
フェーズ1：偵察
すべてのファイルを読まずにプロジェクトについての生の信号を集めます。これらのチェックを並行して実行：
1. パッケージマニフェスト検出
→ package.json, go.mod, Cargo.toml, pyproject.toml, pom.xml
2. フレームワークフィンガープリント
→ next.config、nuxt.config、angular.json、vite.config
3. エントリポイント識別
→ main.*、index.*、app.*、server.*
4. ディレクトリ構造スナップショット
→ ディレクトリツリーの最上位2レベル
5. コンフィグとツール検出
→ .eslintrc、.prettierrc、tsconfig.json、Dockerfile
6. テスト構造検出
→ tests/、__tests__/、*.spec.ts、jest.config.*
フェーズ2：アーキテクチャマップ
主要なモジュールとそれらの関係を特定します。
フェーズ3：規約とスタイル
コード規約、命名パターン、プロジェクト固有のパターンを特定。
出力
- アーキテクチャマップ
- 主要なエントリポイントと流れ
- 規約とスタイルガイド
- スターターCLAUDE.md
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 · 59 lines · 86 tokens per session scan A 1be561bc9449
codebase-onboarding is a skill published in the GitHub repository KunanonJ/ai-skills-hub (4 stars, last pushed 1mo ago), licensed MIT. It adds 86 tokens to every session and 605 once invoked, about $0.0004 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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