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agentic-engineering

評価ファースト実行、分解、コスト対応モデルルーティングを使用してエージェニックエンジニアとして動作します。

Quality

65%

Does it follow best practices?

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SecuritybySnyk

Passed

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Fix and improve this skill with Tessl

tessl review fix ./docs/ja-JP/skills/agentic-engineering/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

72%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

The body is an exemplary token-efficient policy document: terse, well-organized sections that assume Claude's competence. Its main weakness is executability detail — the eval-first loop and task-decomposition rules would be far more actionable with one concrete example and an explicit regression-handling step.

Suggestions

Add a short worked example of one task unit (goal, completion criterion, primary risk, chosen tier) to make the decomposition and routing guidance copy-paste concrete.

Extend the eval-first loop with an explicit regression-handling step (e.g., 'if the delta is negative, revert and re-decompose the unit') to close the validation gap.

Show a minimal cost-tracking template (model, token estimate, retries, wall-clock, pass/fail) so the コスト規律 section can be applied verbatim.

DimensionReasoningScore

Conciseness

The body is pure lean policy — terse bullet lists ("15 分単位ルール", the tier table, the tracking fields) with zero padding and no explanation of concepts Claude already knows. Every token earns its place.

5 / 5

Actionability

Concrete elements exist (the Haiku/Sonnet/Opus routing table, the escalation rule, per-task tracking fields), but key details are missing — '完了基準を定義する' and '障害シグネチャをキャプチャする' give no how, and no example of an eval or a task unit is shown.

3 / 5

Workflow Clarity

The eval-first loop is a clear 4-step sequence with a compare-delta checkpoint ('評価を再実行し、デルタを比較する'), but the error-recovery path when the delta is negative is left implicit, matching the 'checkpoints missing or implicit' anchor rather than anchor 4.

3 / 5

Progressive Disclosure

A compact, well-sectioned, self-contained skill (~57 lines) with no external reference needs and no nested references; under the simple-skill exception, well-organized sections alone merit the top score.

5 / 5

Total

16

/

20

Passed

Description

42%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

The description communicates a clear identity and methodology but functions as a capability label rather than a trigger. It lacks any 'when to use' guidance and uses jargon-heavy terms that users are unlikely to voice naturally.

Suggestions

Add an explicit 'Use when...' clause (e.g., 'Use when AI agents perform implementation work and humans gate quality and risk') to satisfy the missing trigger guidance that currently caps completeness at 3.

Include natural trigger terms users would actually say, such as 'AIエージェント', 'エージェントワークフロー', 'モデルルーティング', 'タスク分解', rather than only compound jargon like 'エージェニックエンジニア'.

Replace abstract method names with one or two concrete capabilities (e.g., 'define completion criteria before implementation, run evaluations to catch regressions, route tasks to Haiku/Sonnet/Opus by complexity') to raise specificity.

DimensionReasoningScore

Specificity

Names the domain ("エージェニックエンジニア") and three methodology actions ("評価ファースト実行、分解、コスト対応モデルルーティング"), but these are abstract method labels rather than the concrete capabilities of anchor 4.

3 / 5

Completeness

The 'what' is stated clearly (operate as an agentic engineer using these methods), but there is no 'Use when...' clause or equivalent trigger guidance, which caps completeness at 3 per the judging guidelines.

3 / 5

Trigger Term Quality

The description is built from technical jargon ("エージェニックエンジニア", "コスト対応モデルルーティング") that users would rarely say naturally; common phrasings like "AIエージェントに実装させたい" or "エージェントワークフロー" are absent, matching the 'missing the natural phrases users say' anchor.

2 / 5

Distinctiveness Conflict Risk

The agentic-engineering/model-routing niche is somewhat specific, but the description could still overlap with general development-workflow or AI-coding skills, matching the 'somewhat specific but could still overlap' anchor.

3 / 5

Total

11

/

20

Passed

Validation

93%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

Total

15

/

16

Passed

Repository

affaan-m/ECC

Path

docs/ja-JP/skills/agentic-engineering/SKILL.md

Reviewed

Table of Contents

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