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performance-optimization

Optimizes application performance. Use when performance requirements exist, when you suspect performance regressions, or when Core Web Vitals or load times need improvement. Use when profiling reveals bottlenecks that need fixing.

59

Quality

67%

Does it follow best practices?

Impact

No eval scenarios have been run

SecuritybySnyk

Passed

No known issues

Optimize this skill with Tessl

npx tessl skill review --optimize ./skills/performance-optimization/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

77%

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

This is a strong, actionable performance optimization skill with excellent workflow structure and concrete, executable examples. Its main weakness is length — the document tries to be both an overview and a detailed reference, which undermines conciseness and progressive disclosure. The Common Rationalizations table and overly detailed image optimization example could be trimmed or moved to reference files.

Suggestions

Move the detailed anti-pattern code examples (especially the extensive image optimization picture element) to the referenced `references/performance-checklist.md`, keeping only brief patterns or one-liners in the main SKILL.md

Remove or significantly trim the 'Common Rationalizations' table — it's motivational content that doesn't help Claude perform the task

DimensionReasoningScore

Conciseness

The skill is generally well-structured but includes some unnecessary content that Claude already knows — the 'Common Rationalizations' table is motivational rather than actionable, the 'When NOT to use' explanation is somewhat obvious, and the image optimization example is excessively verbose (the full picture element with multiple source variants is overkill when a concise pattern would suffice). The decision tree and anti-pattern tables are valuable but the overall document is longer than it needs to be.

2 / 3

Actionability

The skill provides fully executable code examples across multiple domains — N+1 query fixes, React memoization, caching patterns, image optimization, bundle splitting, and measurement commands. The diagnostic decision tree is particularly actionable, mapping symptoms directly to investigation steps. Code examples are copy-paste ready with clear BAD/GOOD contrasts.

3 / 3

Workflow Clarity

The 5-step optimization workflow (Measure → Identify → Fix → Verify → Guard) is clearly sequenced with explicit validation checkpoints. The verification checklist at the end provides a concrete feedback loop, and the workflow explicitly requires measurement before and after changes. The 'Guard' step addresses regression prevention.

3 / 3

Progressive Disclosure

The skill references `references/performance-checklist.md` for detailed checklists, but no bundle files are provided to verify this exists. The main document itself is quite long and could benefit from splitting the anti-pattern examples into a separate reference file, keeping the SKILL.md as a leaner overview with pointers. The inline content is well-organized with clear sections, but the volume of inline examples works against progressive disclosure principles.

2 / 3

Total

10

/

12

Passed

Description

57%

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

The description has strong completeness with explicit 'Use when' triggers covering multiple scenarios, but suffers from vague capability specification—it never lists concrete actions beyond the generic 'optimizes application performance.' The trigger terms are decent but could be more comprehensive, and the broad scope creates moderate conflict risk with other performance-related skills.

Suggestions

Replace the vague 'Optimizes application performance' with specific concrete actions, e.g., 'Profiles CPU and memory usage, reduces bundle sizes, implements lazy loading, optimizes render paths, and improves caching strategies.'

Add more natural trigger terms users would say, such as 'slow page', 'latency', 'LCP', 'FCP', 'TTI', 'memory leak', 'bundle size', 'rendering performance'.

Clarify the scope (web frontend, backend, full-stack) to reduce conflict risk with other optimization-focused skills.

DimensionReasoningScore

Specificity

The description says 'Optimizes application performance' which is vague and abstract. It does not list any concrete actions like 'profile CPU usage', 'reduce bundle size', 'lazy-load images', or 'minimize render-blocking resources'. The actions mentioned are all high-level abstractions.

1 / 3

Completeness

The description clearly answers both 'what' (optimizes application performance) and 'when' with explicit trigger conditions: performance requirements, suspected regressions, Core Web Vitals/load time issues, and profiling bottlenecks. The 'Use when...' clause is present and detailed.

3 / 3

Trigger Term Quality

Includes some relevant terms like 'Core Web Vitals', 'load times', 'profiling', 'bottlenecks', and 'performance regressions' which users might naturally mention. However, it misses many common variations like 'slow page', 'latency', 'bundle size', 'rendering', 'caching', 'memory leak', 'FCP', 'LCP', 'TTI'.

2 / 3

Distinctiveness Conflict Risk

'Application performance' is broad and could overlap with skills focused on database optimization, frontend optimization, backend optimization, or DevOps monitoring. The mention of 'Core Web Vitals' narrows it somewhat toward web/frontend performance, but the overall scope remains ambiguous.

2 / 3

Total

8

/

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.

Validation11 / 11 Passed

Validation for skill structure

No warnings or errors.

Repository
addyosmani/agent-skills
Reviewed

Table of Contents

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