performance-optimization
Optimize application performance for speed, efficiency, and scalability. Use when improving page load times, reducing bundle size, optimizing database queries, or fixing performance bottlenecks. Handles React optimization, lazy loading, caching, code splitting, and profiling.
85
78%
Does it follow best practices?
Impact
100%
1.04xAverage score across 3 eval scenarios
Passed
No known issues
Optimize this skill with Tessl
npx tessl skill review --optimize ./.agent-skills/performance-optimization/SKILL.mdQuality
Discovery
92%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 skill description that clearly articulates specific capabilities and includes an explicit 'Use when...' clause with natural trigger terms. The description covers both frontend (React, bundle size, lazy loading) and backend (database queries, caching) performance concerns, though this breadth could create some overlap with more specialized skills.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions: 'improving page load times, reducing bundle size, optimizing database queries, fixing performance bottlenecks, React optimization, lazy loading, caching, code splitting, and profiling.' | 3 / 3 |
Completeness | Clearly answers both what ('Optimize application performance for speed, efficiency, and scalability') and when ('Use when improving page load times, reducing bundle size, optimizing database queries, or fixing performance bottlenecks') with explicit trigger guidance. | 3 / 3 |
Trigger Term Quality | Includes natural keywords users would say: 'page load times', 'bundle size', 'database queries', 'performance bottlenecks', 'React optimization', 'lazy loading', 'caching', 'code splitting', 'profiling' - these are terms developers naturally use when discussing performance issues. | 3 / 3 |
Distinctiveness Conflict Risk | While performance optimization is a clear domain, terms like 'React optimization' and 'database queries' could overlap with React-specific skills or database skills. The scope is broad enough that it might conflict with more specialized skills. | 2 / 3 |
Total | 11 / 12 Passed |
Implementation
64%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This is a solid, actionable performance optimization skill with excellent concrete code examples covering frontend and backend optimization. The main weaknesses are the lack of validation checkpoints between optimization steps (measure -> optimize -> verify cycle), unnecessary metadata/placeholder sections, and the monolithic structure that could benefit from progressive disclosure to separate files.
Suggestions
Add explicit validation steps after each optimization phase (e.g., 'Re-run Lighthouse after React optimizations to verify improvement before proceeding to bundle optimization')
Remove the empty 'Examples' placeholder section and the metadata block (version, tags, related skills) which don't provide actionable guidance
Consider splitting detailed code examples into separate reference files (e.g., REACT_OPTIMIZATION.md, DATABASE_OPTIMIZATION.md) with SKILL.md as a concise overview
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill is mostly efficient with good code examples, but includes some unnecessary sections like the metadata block with version info, related skills, and tags that don't add actionable value. The 'Examples' section at the end is empty placeholder content. | 2 / 3 |
Actionability | Provides fully executable, copy-paste ready code examples across multiple domains (React, TypeScript, SQL, bash). Each optimization technique includes concrete before/after examples with clear ❌/✅ annotations. | 3 / 3 |
Workflow Clarity | Steps are clearly numbered (1-5) with logical progression from measurement to optimization. However, there are no explicit validation checkpoints or feedback loops - no guidance on verifying optimizations worked before moving to the next step. | 2 / 3 |
Progressive Disclosure | Content is well-structured with clear sections and a checklist summary. However, the skill is quite long (~200 lines of content) and could benefit from splitting detailed examples into separate reference files. External references are provided but inline content is heavy. | 2 / 3 |
Total | 9 / 12 Passed |
Validation
90%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 10 / 11 Passed
Validation for skill structure
| Criteria | Description | Result |
|---|---|---|
metadata_version | 'metadata.version' is missing | Warning |
Total | 10 / 11 Passed | |
- Repository
- supercent-io/skills-template
- Commit
c033769
- Reviewed
Table of Contents
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