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.

Quality

63%

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tessl review fix ./skills/performance-optimization/SKILL.md

The canonical home for this skill is performance-optimization in addyosmani/agent-skills

Quality

Content

77%Scale 1-3

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 code examples. Its main weakness is length — the document tries to be both an overview and a detailed reference, which hurts conciseness and progressive disclosure. The Common Rationalizations and Red Flags sections add bulk without proportional value for an AI agent that doesn't need motivational nudges.

Suggestions

Move the detailed anti-pattern code examples (N+1 queries, image optimization, React re-renders, caching, bundle splitting) into the referenced `references/performance-checklist.md` and keep only brief summaries with links in the main SKILL.md.

Remove or significantly trim the 'Common Rationalizations' table — it's motivational content that doesn't help Claude execute performance optimization tasks.

Dimension	Reasoning	Score
Conciseness	The skill is generally well-structured but includes some content Claude already knows (e.g., the 'Common Rationalizations' table is motivational rather than actionable, the 'When NOT to use' explanation is somewhat obvious). The image optimization example is extremely verbose with the full <picture> element covering multiple formats and breakpoints — a shorter example with a note about extending would suffice. The decision tree and anti-pattern examples are valuable but the overall document is quite long (~250 lines).	2 / 3
Actionability	The skill provides fully executable code examples across multiple domains: N+1 query fixes with Prisma, React memoization patterns, image optimization HTML, caching implementations, bundle splitting with lazy/Suspense, and CI enforcement commands. The bad/good pattern pairs are concrete and copy-paste ready.	3 / 3
Workflow Clarity	The 5-step optimization workflow (Measure → Identify → Fix → Verify → Guard) is clearly sequenced with explicit validation. The verification checklist at the end provides concrete checkpoints. The diagnostic decision tree helps identify which step to take based on symptoms. The feedback loop of 'measure, fix, measure again' is emphasized throughout.	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 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. The diagnostic tree, bottleneck tables, and extensive code examples all inline make this somewhat monolithic.	2 / 3
	Total	10 / 12 Passed

Description

49%Scale 1-3

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 a well-structured 'Use when...' clause that provides explicit trigger guidance, which is its main strength. However, it is severely lacking in specificity — it doesn't describe any concrete actions the skill performs beyond the vague 'optimizes application performance'. The broad scope also creates high conflict risk with other performance-related skills.

Suggestions

Replace 'Optimizes application performance' with specific concrete actions, e.g., 'Reduces bundle sizes, implements lazy loading, optimizes rendering performance, improves caching strategies, and minimizes network requests.'

Narrow the scope to a specific domain (e.g., web frontend, backend APIs, database queries) to reduce conflict risk with other potential performance-related skills.

Add more natural trigger terms users would say, such as 'slow page', 'speed up', 'latency', 'Time to First Byte', 'Largest Contentful Paint', or specific file types/frameworks.

Dimension	Reasoning	Score
Specificity	The description says 'Optimizes application performance' which is vague and abstract. It does not list any concrete actions like 'minify assets', 'lazy-load images', 'reduce bundle size', or 'optimize database queries'. The only semi-specific term is 'Core Web Vitals' but that describes a measurement, not an action the skill performs.	1 / 3
Completeness	The description answers both 'what' (optimizes application performance) and 'when' with explicit trigger clauses ('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'). Both parts are present and explicit.	3 / 3
Trigger Term Quality	Includes some relevant keywords like 'performance', 'Core Web Vitals', 'load times', 'profiling', 'bottlenecks', and 'performance regressions'. However, it misses many natural user terms like 'slow', 'speed up', 'latency', 'rendering', 'bundle size', 'caching', 'optimization', or specific framework terms.	2 / 3
Distinctiveness Conflict Risk	'Optimizes application performance' is extremely broad and could conflict with many skills — frontend optimization, backend optimization, database tuning, network optimization, build tooling, etc. Without specifying what type of application or what kind of performance (rendering, API response, build time), this could easily trigger incorrectly.	1 / 3
	Total	7 / 12 Passed

Validation

100%

Warnings & errors only

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: finlay611/agent-skills
Path: skills/performance-optimization/SKILL.md
Commit: 22df069

Reviewed: 4 days ago

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