performance-profiling

Performance profiling principles. Measurement, analysis, and optimization techniques.

Quality

39%

Does it follow best practices?

Impact

—

No eval scenarios have been run

Securityby

Advisory

Suggest reviewing before use

Fix and improve this skill with Tessl

tessl review fix ./.agent/skills/performance-profiling/SKILL.md

Quality

Content

64%

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

This skill excels at conciseness, using tables effectively to pack maximum information into minimal tokens. However, it reads more as a reference card than an actionable skill - it tells Claude what to look for but not exactly how to do it with executable examples. The workflow is clear conceptually but lacks the validation feedback loops important for profiling tasks.

Suggestions

Add executable code examples for at least one profiling scenario (e.g., how to run and interpret DevTools Performance programmatically or via Puppeteer)

Include explicit validation steps in the workflow, such as 'Compare metrics before/after: if LCP improved by <10%, investigate further'

Add concrete output examples showing what good vs bad profiling results look like

Dimension	Reasoning	Score
Conciseness	Extremely lean and efficient use of tables to convey information. No unnecessary explanations of concepts Claude already knows. Every section delivers actionable reference data without padding.	3 / 3
Actionability	Provides good reference tables and a clear workflow, but lacks executable code examples beyond the script reference. The profiling workflow is conceptual rather than showing concrete commands or code snippets for each tool.	2 / 3
Workflow Clarity	The 4-step process is clearly outlined, but lacks explicit validation checkpoints or feedback loops. No guidance on what to do if validation fails or how to confirm improvements quantitatively.	2 / 3
Progressive Disclosure	Content is well-organized with clear sections, but everything is inline in one file. References to external tools are mentioned but no links to detailed documentation or separate files for advanced topics like memory profiling deep-dives.	2 / 3
	Total	9 / 12 Passed

Description

14%

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 description is too abstract and lacks actionable detail. It reads like a topic heading rather than a skill description, using only high-level nouns without concrete actions or clear usage triggers. The absence of specific techniques, tools, or a 'Use when' clause makes it difficult for Claude to know when to select this skill over others.

Suggestions

Add a 'Use when...' clause with specific trigger scenarios like 'Use when the user mentions slow code, bottlenecks, CPU/memory issues, or asks to benchmark performance'

Replace abstract nouns with concrete actions: 'Profile CPU and memory usage, identify bottlenecks, analyze flame graphs, optimize hot paths'

Include specific technologies or contexts to improve distinctiveness: 'Python profiling with cProfile, JavaScript performance debugging, database query optimization'

Dimension	Reasoning	Score
Specificity	The description uses vague, abstract language like 'principles', 'measurement', 'analysis', and 'optimization techniques' without listing any concrete actions. It doesn't specify what is being profiled, measured, or optimized.	1 / 3
Completeness	The description weakly addresses 'what' with abstract nouns and completely lacks any 'when' guidance. There is no 'Use when...' clause or explicit trigger guidance.	1 / 3
Trigger Term Quality	Contains some relevant keywords ('performance profiling', 'optimization') that users might say, but misses common variations like 'slow code', 'bottleneck', 'CPU usage', 'memory leak', 'benchmark', or specific tool names.	2 / 3
Distinctiveness Conflict Risk	Very generic description that could conflict with many skills - any skill involving code optimization, database tuning, system monitoring, or general debugging could overlap with these vague terms.	1 / 3
	Total	5 / 12 Passed

Validation

90%

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 — 10 / 11 Passed

Validation for skill structure

Criteria	Description	Result
allowed_tools_field	'allowed-tools' contains unusual tool name(s)	Warning

	Total	10 / 11 Passed

Repository: lchenrique/politron-ide
Commit: 7114206

Reviewed: 5 months ago

Table of Contents

Discovery Implementation Validation

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