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.
Install with Tessl CLI
npx tessl i github:fernandezbaptiste/claude-code-skills --skill prompt-optimizer86
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npx tessl skill review --optimize ./path/to/skillValidation for skill structure
Discovery
82%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 solid description that excels at providing explicit trigger guidance and natural user phrases. The EARS methodology reference adds domain specificity, but the actual capabilities could be more concrete with specific actions beyond 'transform'. The trigger terms, while good, may overlap with general prompt improvement skills.
Suggestions
Add more specific concrete actions like 'parse requirements into EARS syntax', 'generate ubiquitous/event-driven/state-driven requirement templates', or 'validate requirement completeness'
Differentiate more clearly from general prompt improvement by emphasizing the formal requirements engineering aspect, e.g., 'for software specifications' or 'formal requirement documents'
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Names the domain (EARS methodology, requirements) and the general action (transform vague prompts into specifications), but doesn't list multiple concrete actions like 'parse requirements', 'generate EARS templates', 'validate syntax'. | 2 / 3 |
Completeness | Clearly answers both what (transform vague prompts into precise specifications using EARS) and when (explicit 'Triggers include' clause with specific phrases and conditions). | 3 / 3 |
Trigger Term Quality | Includes natural trigger phrases users would say: 'optimize my prompt', 'improve this requirement', 'make this more specific', plus contextual triggers like 'loose requirements' and 'ambiguous feature descriptions'. | 3 / 3 |
Distinctiveness Conflict Risk | The EARS methodology provides some distinctiveness, but 'optimize my prompt' and 'improve this requirement' could overlap with general prompt engineering or writing improvement skills. | 2 / 3 |
Total | 10 / 12 Passed |
Implementation
85%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 excellent actionability and progressive disclosure. The six-step workflow provides clear, executable guidance with concrete examples and proper validation checkpoints. Minor verbosity in the overview and some redundancy between sections (quality criteria vs. do's/don'ts) slightly reduce token efficiency, but overall this is a strong skill document.
Suggestions
Trim the overview section by removing the methodology attribution and condensing the four-layer enhancement description into the workflow itself
Consolidate the 'Quality criteria' subsection and 'Quick Reference Do's/Don'ts' section to eliminate redundancy
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The content is mostly efficient but includes some unnecessary explanation. The overview section explains what EARS is and includes attribution that could be trimmed. Some sections like 'Quality criteria' and 'Do's/Don'ts' repeat concepts already covered in the workflow. | 2 / 3 |
Actionability | Provides highly concrete, actionable guidance with specific EARS patterns, transformation checklists, real before/after examples, and a complete output template. The six-step workflow gives clear executable steps with specific criteria. | 3 / 3 |
Workflow Clarity | The six-step workflow is clearly sequenced with explicit phases, checklists, and decision points. Each step has clear inputs/outputs. The transformation checklist provides validation checkpoints for the EARS conversion process. | 3 / 3 |
Progressive Disclosure | Excellent structure with a clear overview, detailed workflow in the main file, and well-signaled one-level-deep references to four specialized files (ears_syntax.md, domain_theories.md, examples.md, advanced_techniques.md). Includes guidance on when to load each reference. | 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.
Validation — 11 / 11 Passed
Validation for skill structure
No warnings or errors.
- Reviewed
Table of Contents
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