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 careerchain-ys/stdd --skill reverse-engineering-feature-specgit clone --depth 1 https://github.com/careerchain-ys/stddWrote 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/careerchain-ys/stdd/reverse-engineering-feature-spec)<a href="https://agentmods.dev/skills/careerchain-ys/stdd/reverse-engineering-feature-spec"><img src="https://agentmods.dev/badge/skills/careerchain-ys/stdd/reverse-engineering-feature-spec/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/careerchain-ys/stdd/reverse-engineering-feature-spec"><img src="https://agentmods.dev/badge/skills/careerchain-ys/stdd/reverse-engineering-feature-spec.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 | $0.00137 | $0.06667 |
| Opus 5.5 | $0.00055 | $0.02667 |
| Sonnet 5.5 | $0.00027 | $0.01333 |
| Haiku 4.5 | $0.00014 | $0.00667 |
Grade A, and why
reverse-engineering-feature-spec 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 — 500 lines — stays where its author put it; the contents beside it link to each section on GitHub.
feature spec のリバースエンジニアリング
既に動いている 機能 / ページ単位の実装コードを精読し、その挙動を正確に反映した feature 階層の Spec ドキュメント（REQUIREMENTS.md + TECH_DESIGN.md + TEST_PLAN.md）とテスト（E2E / Unit / Integration）を作成する。
前提（推奨）: プロジェクト全体の common 階層（
docs/common/REQUIREMENTS.md+ARCHITECTURE.md+TABLE_DEFINITION.md+API_SPEC.md）が未作成なら、先にreverse-engineering-common-specスキルで作成しておくと、レイヤ規約・共有ドメインモデル・テーブル定義・API 契約を踏まえられて精度が上がる。既にある場合は本スキルから始める。データモデル・API は common 階層が SSoT のため、feature 側では common のTABLE_DEFINITION.md/API_SPEC.mdを参照する。
最重要原則
Specに記載する文言は正確に実装を反映すること
リバースエンジニアリングでは、**実装が真実（Source of Truth）**である。Specは実装の挙動を忠実にドキュメント化したものであり、理想論や推測で書いてはならない。
❌ 悪い例: 実装を確認せずに一般的な仕様を書く
- 「電話番号は10〜11桁の数字」 ← バリデーション定義（例: Zod スキーマ）を確認していない
- 「戻るボタンで前のステップに戻る」 ← 実際のボタンラベルは「前へ」
✅ 良い例: 実装を確認してから書く
- 「電話番号は10文字以上（数字とハイフンのみ許可）」 ← バリデーション定義（例: Zod スキーマ）を確認
- 「「前へ」ボタンで前のステップに戻る」 ← ビューのボタンテキストを確認
具体的な確認項目（「確認元」はソースの種別。括弧内は代表スタックでの一例なので、採用スタックに読み替えること）:
| 項目 | 確認元（ソースの種別） | よくある間違い |
|---|---|---|
| ボタンラベル | ビュー/テンプレート内のテキスト（例: JSX） | 「送信」と書いたが実際は「保存」 |
| バリデーションルール | バリデーション定義（例: Zod スキーマ schema.ts） |
桁数・形式を想像で書く |
| エラーメッセージ | バリデーション定義のメッセージ（例: Zod の message） | 一般的なメッセージを推測で書く |
| フォーム項目名 | ラベル要素（例: <label> / getByLabel / aria-label） |
項目名を想像で書く |
| ページ遷移先 | ルーティング/リダイレクト（例: router.push() / redirect()） |
パスを想像で書く |
| API呼び出し | ハンドラ/通信層（例: Server Actions / fetch） | エンドポイントを想像で書く |
| DB操作 | データアクセス層のメソッド（例: repository 層） | テーブル名・カラム名を想像で書く |
| 型定義 | ドメインモデルの型（例: domain/models 配下） |
フィールド名を想像で書く |
詳細: 正確性ガイド
Quick Start
前提条件
- 対象機能が既に動いている実装コードがある
- 対応するSpecドキュメント（REQUIREMENTS.md / TECH_DESIGN.md / TEST_PLAN.md）が存在しない、または不十分
作業フロー
1. 実装コードリーディング（精読）
↓
2. REQUIREMENTS.md作成（ユーザー視点の挙動を記述）
↓
3. Playwright MCPでUIキャプチャ → Figmaファイル作成
↓
4. TECH_DESIGN.md作成（ロジック設計中心の技術設計。データモデル/APIは common 参照）
↓
4.5 TEST_PLAN.md作成（テスト戦略）
↓
5. E2Eテスト作成
↓
6. Unit / Integrationテスト作成（必要に応じて）
↓
7. /verifying-consistency で整合性チェック
↓
8. 不整合の修正（Specを実装に合わせる）
What ships with it
2 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 · 500 lines · 137 tokens per session scan A f6600287ffa2
reverse-engineering-feature-spec is a skill published in the GitHub repository careerchain-ys/stdd (2 stars, last pushed 3mo ago), licensed Apache-2.0. It adds 137 tokens to every session and 6,667 once invoked, about $0.0005 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.
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