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prompt-optimizer

Transform vague prompts into precise, well-structured specifications using EARS (Easy Approach to Requirements Syntax) methodology. This skill should be used when users provide loose requirements, ambiguous feature descriptions, or need to enhance prompts for AI-generated code, products, or documents. Triggers include requests to "optimize my prompt", "improve this requirement", "make this more specific", or when raw requirements lack detail and structure.

88

1.62x
Quality

83%

Does it follow best practices?

Impact

96%

1.62x

Average score across 3 eval scenarios

SecuritybySnyk

Passed

No known issues

SKILL.md
Quality
Evals
Security

Quality

Content

77%

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

This is a well-structured skill with strong actionability and clear workflow sequencing. The EARS methodology is presented with concrete patterns, examples, and checklists that make it immediately usable. The main weaknesses are moderate verbosity (attribution, some explanatory padding) and the fact that referenced bundle files don't exist, undermining the progressive disclosure strategy.

Suggestions

Remove the attribution paragraph and tighten the overview — Claude doesn't need the backstory of the methodology's inspiration.

Provide the referenced bundle files (references/ears_syntax.md, references/domain_theories.md, etc.) or remove the references to avoid broken navigation.

Move the detailed domain theory mappings and the full output template to reference files to reduce the main SKILL.md length and improve progressive disclosure.

DimensionReasoningScore

Conciseness

The skill is moderately efficient but includes some unnecessary verbosity. The attribution paragraph and some explanatory text (e.g., explaining what EARS stands for, the domain theory selection process) could be tightened. The methodology overview and step descriptions contain padding that Claude doesn't need, though the core content is useful.

2 / 3

Actionability

The skill provides highly concrete, actionable guidance with specific EARS patterns, a clear before/after transformation example, a detailed transformation checklist, concrete example formats, and a complete output template. Each step has specific instructions rather than vague descriptions.

3 / 3

Workflow Clarity

The six-step workflow is clearly sequenced with explicit inputs/outputs at each stage. The transformation checklist serves as a validation checkpoint in Step 2, and the final Step 6 provides a structured output format that acts as a completeness check. The workflow is logical and each step builds on the previous one.

3 / 3

Progressive Disclosure

The skill references four external files (ears_syntax.md, domain_theories.md, examples.md, advanced_techniques.md) with clear navigation signals and loading guidance. However, no bundle files were provided, meaning these references are broken. Additionally, the main SKILL.md is quite long and some inline content (like the full output template and domain theory mappings) could have been offloaded to the referenced files to keep the overview leaner.

2 / 3

Total

10

/

12

Passed

Description

89%

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

This is a well-crafted description that clearly communicates both purpose and trigger conditions. The EARS methodology reference provides strong distinctiveness, and the explicit trigger phrases are natural and comprehensive. The main weakness is that the 'what' portion could enumerate more specific concrete actions beyond the general 'transform' verb.

Suggestions

Add more specific concrete actions to the capability list, e.g., 'Parses ambiguous requirements, applies EARS syntax patterns (ubiquitous, event-driven, state-driven, optional, unwanted), and outputs structured specification documents.'

DimensionReasoningScore

Specificity

The description names the domain (prompt/requirement transformation) and mentions the EARS methodology, but the concrete actions are limited to 'transform vague prompts into precise, well-structured specifications' — it doesn't list multiple distinct actions like parsing, structuring, categorizing, or outputting in specific formats.

2 / 3

Completeness

Clearly answers both 'what' (transform vague prompts into precise specifications using EARS methodology) and 'when' (explicit 'Use when' equivalent with trigger phrases and situational descriptions like 'when raw requirements lack detail and structure').

3 / 3

Trigger Term Quality

Includes strong natural trigger terms: 'optimize my prompt', 'improve this requirement', 'make this more specific', 'loose requirements', 'ambiguous feature descriptions'. These are phrases users would naturally say when needing this skill.

3 / 3

Distinctiveness Conflict Risk

The EARS methodology reference and the specific focus on prompt/requirement refinement create a clear niche. The trigger terms are distinct enough ('optimize my prompt', 'improve this requirement') to avoid conflicting with general coding or document skills.

3 / 3

Total

11

/

12

Passed

Validation

100%

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

Validation11 / 11 Passed

Validation for skill structure

No warnings or errors.

Repository
daymade/claude-code-skills
Reviewed

Table of Contents

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