performance-optimizer
Performance analysis, profiling techniques, bottleneck identification, and optimization strategies for code and systems. Use when the user needs to improve performance, reduce resource usage, or identify and fix performance bottlenecks.
78
Quality
73%
Does it follow best practices?
Impact
Pending
No eval scenarios have been run
Passed
No known issues
Optimize this skill with Tessl
npx tessl skill review --optimize ./claude/skills/performance-optimizer/SKILL.mdQuality
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 with good completeness and trigger term coverage. The explicit 'Use when' clause with multiple trigger scenarios is a strength. However, the capabilities listed are somewhat abstract categories rather than concrete actions, and the broad scope of 'code and systems' creates some potential for overlap with related skills.
Suggestions
Add more concrete specific actions like 'profile CPU/memory usage', 'analyze query execution plans', 'identify memory leaks' to improve specificity
Consider narrowing scope or adding distinguishing details (e.g., 'for backend services' or 'for database queries') to reduce conflict risk with other optimization-related skills
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Names the domain (performance analysis) and lists several actions (profiling techniques, bottleneck identification, optimization strategies), but these are somewhat abstract categories rather than concrete specific actions like 'profile CPU usage' or 'analyze memory allocation'. | 2 / 3 |
Completeness | Clearly answers both what (performance analysis, profiling, bottleneck identification, optimization strategies) AND when (explicit 'Use when' clause covering improving performance, reducing resource usage, fixing bottlenecks). | 3 / 3 |
Trigger Term Quality | Good coverage of natural terms users would say: 'performance', 'profiling', 'bottleneck', 'optimization', 'resource usage'. These are terms users naturally use when seeking performance help. | 3 / 3 |
Distinctiveness Conflict Risk | While performance-focused, the broad scope of 'code and systems' could overlap with debugging skills, code review skills, or system administration skills. The triggers are somewhat generic and could conflict with optimization-related skills in other domains. | 2 / 3 |
Total | 10 / 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 comprehensive performance optimization skill with excellent actionable code examples across multiple languages and domains. However, it's overly long for a SKILL.md file, mixing high-level guidance with detailed reference material that should be split into separate files. The workflow could benefit from more explicit validation checkpoints, especially for operations that could impact production systems.
Suggestions
Split detailed sections (Database Optimization, Web Performance, Memory Optimization) into separate reference files and link to them from the main skill
Add explicit validation checkpoints in the workflow, e.g., 'Before applying optimization: verify baseline metrics are captured and tests pass'
Remove explanatory content Claude already knows (e.g., the 80/20 rule explanation, 'Never optimize without profiling' rationale) to reduce token usage
Add a feedback loop for the optimization process: 'If performance regression detected → rollback → re-profile → try alternative approach'
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | While the content is generally well-organized, it includes some unnecessary explanations Claude would already know (e.g., explaining what the 80/20 rule is, basic concepts like 'measure first'). Some sections could be tightened, though most code examples are appropriately concise. | 2 / 3 |
Actionability | Excellent executable code examples across multiple languages (Python, JavaScript, SQL, Bash). Commands are copy-paste ready with specific tool invocations, and before/after code comparisons clearly demonstrate the optimization patterns. | 3 / 3 |
Workflow Clarity | The 4-step process (Measure → Find → Optimize → Verify) provides a clear sequence, but lacks explicit validation checkpoints and feedback loops. For performance optimization involving potentially destructive changes, there should be more explicit 'verify before proceeding' gates. | 2 / 3 |
Progressive Disclosure | Content is well-structured with clear headers, but it's a monolithic 300+ line document with no references to external files for detailed topics like database optimization or web performance. These sections could be split into separate reference files with links from the main skill. | 2 / 3 |
Total | 9 / 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.
- Repository
- einverne/dotfiles
- Commit
b1b2fe0
- Reviewed
Table of Contents
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