Conciseness

The ~45-line body is pure directives with zero padding and no explanation of concepts Claude already knows — e.g.「レビュー対象：動作のリグレッション／セキュリティの前提／データの整合性／障害処理／ロールアウトの安全性」. Every token earns its place, matching the 'lean and efficient; assumes Claude's competence' anchor; there are no instances of over-explanation that would justify a 4.

Actionability

The guidance is principle-level —「計画の品質はタイピングスピードより重要」「曖昧な作業を明確に分解する」— with no commands, code, templates, examples, or step-level specifics for an instruction-only skill. It rises above anchor 1 only because bullets like「操作されたドメインに対する必須のリグレッションカバレッジ」and「明示的なエッジケースのアサーション」give concrete high-level hints; it stays at 2 because the specific steps to execute anything are missing.

Workflow Clarity

The sections (プロセスの変化、アーキテクチャ要件、コードレビュー、採用と評価シグナル、テスト標準) are parallel principle lists with no sequenced workflow, checkpoints, or validation steps for applying them. This is a multi-faceted guidance skill rather than a single unambiguous-action skill, so the simple-skill exception does not apply; it sits at anchor 2 rather than 1 only because each section is internally coherent and thematically ordered.

Progressive Disclosure

At ~45 lines with no bundle files (references/, scripts/, assets/ are absent and no file paths are cited), the body is organized into clearly headed, well-scoped sections that cover the whole topic without needing external references. This matches the rubric's exception allowing a 5 for short, well-organized skills with no need for external files.

Specificity

The description names its domain —「AI エージェントが大量の実装出力を生成するチームのためのエンジニアリング運用モデル」— but lists no concrete actions or capabilities whatsoever. It matches anchor 2 ('names the domain but actions are minimal or generic'): not 3 because no concrete actions (e.g., process design, review standards) are stated, and not 1 because the domain and audience are clearly identified.

Completeness

It provides only a categorical 'what' (an「エンジニアリング運用モデル」) and no 'when' at all — there is no 'Use when...' clause or equivalent trigger guidance, which caps completeness at 3 by guideline. The 'what' is too vague to count as a 'clear what' (anchor 3), so it lands on anchor 2 ('has a vague what and no when').

Trigger Term Quality

「AI エージェント」 is a keyword users might plausibly say, but「エンジニアリング運用モデル」 is abstract jargon no user would utter when they need this skill. Natural phrases like「AI ファースト開発」「エージェントによるコード生成」「AI チームのコードレビュー」 are absent, matching anchor 2 ('one or two generic keywords; missing the natural phrases users say') rather than 3.

Distinctiveness Conflict Risk

The framing around teams where AI agents generate large volumes of implementation output carves out a recognizable niche, but the description could overlap with any AI-assisted development process, prompt-engineering, or code-review skill. It matches anchor 3 ('somewhat specific but could still overlap with similar skills') — not 4 because no distinct triggers are given.