tessl-labs/skill-review-optimizer
Automate iterative skill improvement using tessl skill review. Use when optimizing skills, improving skill quality scores, iterating on skill design based on tessl feedback, or systematically enhancing skill descriptions and content. Runs tessl reviews, parses scores and suggestions, identifies missing metadata fields, rewrites descriptions with concrete actions, restructures content sections, adjusts frontmatter fields, and guides incremental refinement until target scores are achieved.
Overall
score
100%
Does it follow best practices?
Validation for skill structure
Activation
100%This is a strong skill description that excels across all dimensions. It provides specific concrete actions, includes natural trigger terms that users would actually say, explicitly states both what the skill does and when to use it, and occupies a clear niche that won't conflict with other skills. The description is comprehensive yet focused.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions: 'Runs tessl reviews, parses scores and suggestions, identifies missing metadata fields, rewrites descriptions with concrete actions, restructures content sections, adjusts frontmatter fields, and guides incremental refinement until target scores are achieved.' | 3 / 3 |
Completeness | Clearly answers both what (automates iterative skill improvement, runs reviews, parses scores, rewrites descriptions, etc.) AND when ('Use when optimizing skills, improving skill quality scores, iterating on skill design based on tessl feedback'). | 3 / 3 |
Trigger Term Quality | Includes natural keywords users would say: 'skill improvement', 'skill quality scores', 'skill design', 'tessl feedback', 'skill descriptions', 'tessl review'. These are terms a user working with tessl skills would naturally use. | 3 / 3 |
Distinctiveness Conflict Risk | Very specific niche around 'tessl skill review' tooling with distinct triggers like 'tessl feedback', 'skill quality scores', and 'frontmatter fields'. Unlikely to conflict with general coding or documentation skills. | 3 / 3 |
Total | 12 / 12 Passed |
Implementation
100%This is a well-crafted skill that demonstrates excellent token efficiency while providing fully actionable guidance. The workflow is clearly sequenced with explicit validation checkpoints and feedback loops for iteration. Progressive disclosure is handled well with appropriate references to supporting documentation.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Content is lean and efficient, assuming Claude's competence. No unnecessary explanations of basic concepts, every section serves a clear purpose. | 3 / 3 |
Actionability | Provides concrete, executable commands (python3 scripts/optimize_skill.py), specific YAML examples for metadata fixes, and clear target criteria. Copy-paste ready. | 3 / 3 |
Workflow Clarity | Clear 7-step workflow with explicit validation checkpoint ('If score decreased or unchanged after 3 iterations...'), feedback loop (improve → review cycle), and specific stopping criteria. | 3 / 3 |
Progressive Disclosure | Well-structured overview with clear one-level-deep references to STRATEGIES.md and SCORING_GUIDE.md. Content appropriately split between quick start and detailed reference materials. | 3 / 3 |
Total | 12 / 12 Passed |
Validation
100%Validation — 16 / 16 Passed
Validation for skill structure
No warnings or errors.
Install with Tessl CLI
npx tessl i tessl-labs/skill-review-optimizerReviewed
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