tessl-labs/skill-optimizer
Optimize your skills and tiles: review SKILL.md quality, generate eval scenarios, run evals, compare across models, diagnose gaps, and re-run until scores improve.
88
93%
Does it follow best practices?
Impact
88%
1.07xAverage score across 24 eval scenarios
Passed
No known issues
This plugin was archived by the owner on May 19, 2026
Reason: Tile archived: Superceded by tessl/skill-optimizer - go to https://tessl.io/registry/tessl/skill-optimizer
94%
Run the full optimization cycle for a tile — review best practices, generate eval scenarios, run evals, diagnose gaps, fix, and re-run until scores improve. Use when someone says "optimize my skill", "improve my tile", "run evals", "benchmark my tile", or wants to measure and improve how well a tile helps agents solve tasks.
90%
Generate eval scenarios from a tile, run baseline evals, and present results. Use when setting up evaluation pipelines, running benchmarks, generating test scenarios for a tile, or measuring how well a skill helps agents solve tasks.
90%
Run task evals, analyze results, diagnose failures, apply targeted fixes, and re-run to verify improvements. Use when debugging evaluation scores, fixing failing or regressed criteria, improving tile content after an eval run, or iterating on agent performance test results.
85%
Run task evals across multiple Claude models, compare results side-by-side, and optimise. Use when you want to understand how a skill performs across different models, identify model-specific gaps versus universal tile issues, or validate a skill before publishing it to the registry.
100%
Review and improve your SKILL.md with actionable recommendations. Reads skill bundle (SKILL.md + related docs), validates syntax, explains rubric, shows before/after scores. Use when reviewing skill quality, improving a skill file, checking skill scoring, making your skill better, or learning the skill rubric. This is the standalone review skill — for the full optimization cycle (review + evals + improve), use the `optimize-skill-performance-and-instructions` skill instead.
Quality
Discovery
100%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 strong description that clearly articulates a specific optimization workflow for tiles/skills. It excels at providing both concrete actions and explicit trigger conditions with natural language variations. The description effectively carves out a distinct niche around evaluation and improvement cycles.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions: 'review best practices, generate eval scenarios, run evals, diagnose gaps, fix, and re-run until scores improve' - this clearly describes a multi-step optimization workflow. | 3 / 3 |
Completeness | Clearly answers both what (full optimization cycle with specific steps) AND when (explicit 'Use when...' clause with multiple trigger phrases and a conceptual trigger about measuring/improving tile performance). | 3 / 3 |
Trigger Term Quality | Includes natural keywords users would say: 'optimize my skill', 'improve my tile', 'run evals', 'benchmark my tile', plus the broader concept of 'measure and improve'. Good coverage of variations. | 3 / 3 |
Distinctiveness Conflict Risk | Clear niche focused on tile/skill optimization and evaluation cycles. The specific terminology ('tile', 'eval scenarios', 'benchmark') and the combination of actions creates a distinct identity unlikely to conflict with general coding or documentation skills. | 3 / 3 |
Total | 12 / 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 orchestration skill that clearly sequences three sub-skills with explicit decision points, iteration limits, and stopping conditions. The workflow clarity is excellent with entry/exit criteria and a helpful ASCII diagram. The main weakness is that actionability could be improved with concrete invocation examples or CLI commands rather than abstract 'invoke the skill' references.
Suggestions
Add concrete examples of how to invoke each sub-skill (e.g., exact command syntax or tool calls)
Include a sample output for the final report template showing realistic values to clarify expected format
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The content is lean and efficient, assuming Claude knows how to invoke sub-skills and interpret results. No unnecessary explanations of what evals are or how optimization works—just the sequencing and decision points. | 3 / 3 |
Actionability | Provides clear sequencing and decision criteria, but lacks concrete commands or code examples. References to sub-skills are abstract ('invoke the skill') rather than showing exact invocation syntax or CLI commands. | 2 / 3 |
Workflow Clarity | Excellent multi-step workflow with clear entry/exit criteria, explicit decision points, iteration limits, and stopping conditions. The ASCII diagram and numbered steps make the sequence unambiguous. | 3 / 3 |
Progressive Disclosure | Appropriately delegates detailed instructions to sub-skills (optimize-skill-instructions, setup-skill-performance, optimize-skill-performance) rather than duplicating them. Clear overview with well-signaled handoffs. | 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