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prompt-optimizer

Analyze raw prompts, identify intent and gaps, match ECC components (skills/commands/agents/hooks), and output a ready-to-paste optimized prompt. Advisory role only — never executes the task itself. TRIGGER when: user says "optimize prompt", "improve my prompt", "how to write a prompt for", "help me prompt", "rewrite this prompt", or explicitly asks to enhance prompt quality. Also triggers on Chinese equivalents: "优化prompt", "改进prompt", "怎么写prompt", "帮我优化这个指令". DO NOT TRIGGER when: user wants the task executed directly, or says "just do it" / "直接做". DO NOT TRIGGER when user says "优化代码", "优化性能", "optimize performance", "optimize this code" — those are refactoring/performance tasks, not prompt optimization.

Quality

90%

Does it follow best practices?

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SecuritybySnyk

Passed

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SKILL.md
Quality
Evals
Security

Quality

Content

77%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 content is highly actionable and the 6-phase pipeline is clearly sequenced with explicit clarification gates and failure fallbacks, supported by complete worked examples. The main weaknesses are token efficiency — duplicated trigger lists from the frontmatter and version-specific model recommendations that will age — and a monolithic single-file structure where the long example section could be offloaded to a reference file.

Suggestions

Move two of the three worked examples (e.g., Example 2 and 3) to a references/examples.md file and keep one representative example inline, leaving a clearly signaled one-level-deep reference so SKILL.md stays an overview.

Replace hardcoded model version names ("Sonnet 4.6", "Opus 4.6") with capability-based guidance (e.g., "use the strongest reasoning model for planning") or isolate them in a marked versionable section so they can be updated without touching the core instructions.

Remove the "When to Use" and "Do Not Use When" bullet lists that duplicate the frontmatter description verbatim, or compress them into a one-line pointer to reduce redundant tokens.

DimensionReasoningScore

Conciseness

The body is mostly efficient — dense mapping tables instead of prose, and no explanations of concepts Claude already knows — but it can be tightened: the "When to Use" / "Do Not Use When" lists duplicate the frontmatter description almost verbatim, and time-sensitive version numbers ("Sonnet 4.6", "Opus 4.6", "Next.js 15", "Go 1.22" in the model-recommendation table and examples) are not isolated in a deprecated/versioned section, which the guidelines explicitly penalize. This sits between 'efficient with minor trims' (4) and 'could be tightened' (3), noticeably below the midpoint given the duplication and version-drift risk.

3 / 5

Actionability

Guidance is fully executable for an instruction-only skill: exact detection heuristics ("package.json → Node.js / TypeScript"), intent and tech-stack mapping tables, a precisely specified 5-section output format with per-intent quick patterns, and three complete copy-paste-ready worked examples covering the common cases (vague Chinese prompt, moderate English prompt, EPIC project). This matches the anchor for copy-paste-ready output with examples covering common cases.

5 / 5

Workflow Clarity

The instruction "Run this 6-phase pipeline sequentially" is backed by explicitly numbered Phase 0–5, each with concrete inputs and outputs. Validation checkpoints are explicit, not implicit: Phase 4's checklist with the gate "If 3+ critical items are missing, ask the user up to 3 clarification questions", Phase 0's failure fallback ("If no project files are found... flag 'tech stack unknown'"), and the guardrail for "just do it" / "直接做" requests. The skill is advisory-only, so the destructive/batch validation cap does not apply.

5 / 5

Progressive Disclosure

The skill is a single ~380-line file with no references/, scripts/, or assets/ directories. Section headers are well organized, but the ~120-line Examples section and the large intent/tech-stack matching tables are inlined content that would fit one-level-deep reference files (e.g. references/examples.md), keeping SKILL.md as an overview. This matches 'some structure but content that should be separate is inline'; it is above a 2 because the operational tables are needed at runtime and navigation within the file is clear.

3 / 5

Total

16

/

20

Passed

Description

100%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.

An exemplary description: it states concrete capabilities in third person, defines explicit positive and negative trigger phrases in both English and Chinese, and explicitly disambiguates from adjacent skills (refactoring/performance optimization, direct execution). Every dimension lands at the top anchor with no fluff or over-claiming.

DimensionReasoningScore

Specificity

The description lists four concrete actions — "Analyze raw prompts, identify intent and gaps, match ECC components (skills/commands/agents/hooks), and output a ready-to-paste optimized prompt" — and even delimits the role boundary ("Advisory role only — never executes the task itself"). This matches the anchor for multiple specific concrete actions with comprehensive coverage; a 4 would require minor gaps, but every capability of the skill is named.

5 / 5

Completeness

Both 'what' (analyze, match ECC components, output optimized prompt) and 'when' (explicit "TRIGGER when:" and "DO NOT TRIGGER when:" clauses with quoted concrete phrases) are clearly and explicitly stated. The when-clause is maximally explicit, exceeding the level-4 anchor where 'when' could be more specific.

5 / 5

Trigger Term Quality

Trigger phrases are comprehensive and natural in two languages: "optimize prompt", "improve my prompt", "how to write a prompt for", "help me prompt", "rewrite this prompt" plus Chinese equivalents "优化prompt", "改进prompt", "怎么写prompt", "帮我优化这个指令". Coverage includes the full range of synonyms users would plausibly say, matching the comprehensive-coverage anchor rather than the 'a few natural terms missing' anchor.

5 / 5

Distinctiveness Conflict Risk

The skill occupies a clear niche (prompt optimization) and actively disambiguates against its nearest conflicts: "DO NOT TRIGGER when user says '优化代码', '优化性能', 'optimize performance', 'optimize this code' — those are refactoring/performance tasks" and against direct execution requests. This is minimal conflict risk with distinct triggers, matching the level-5 anchor.

5 / 5

Total

20

/

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

valeriibeck-star/claude-skills

Path

skills/prompt-optimizer/SKILL.md

Reviewed

Table of Contents

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