profiling-application-performance

Execute this skill enables AI assistant to profile application performance, analyzing cpu usage, memory consumption, and execution time. it is triggered when the user requests performance analysis, bottleneck identification, or optimization recommendations. the... Use when optimizing performance. Trigger with phrases like 'optimize', 'performance', or 'speed up'.

Quality

33%

Does it follow best practices?

Impact

Pending

No eval scenarios have been run

Securityby

Passed

No known issues

Optimize this skill with Tessl

npx tessl skill review --optimize ./plugins/performance/application-profiler/skills/profiling-application-performance/SKILL.md

Quality

Discovery

67%

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 covers both what the skill does and when to use it, which is good for completeness. However, it suffers from poor formatting ('Execute this skill enables AI assistant', truncation with 'the...'), uses first/third person inconsistently, and the trigger terms are somewhat generic, risking overlap with other optimization-focused skills. The specificity of capabilities is moderate but undermined by the garbled opening and truncation.

Suggestions

Clean up the malformed opening ('Execute this skill enables AI assistant') and the truncation ('the...') — rewrite in proper third person voice like 'Profiles application performance by analyzing CPU usage, memory consumption, and execution time.'

Add more distinctive trigger terms and natural user phrases such as 'slow', 'profiling', 'benchmark', 'latency', 'memory leak', 'CPU usage' to improve trigger term coverage and reduce conflict risk with generic optimization skills.

Narrow the scope to distinguish from other optimization skills — specify that this is for runtime/application profiling rather than general code optimization.

Dimension	Reasoning	Score
Specificity	Names the domain (performance profiling) and some actions (analyzing CPU usage, memory consumption, execution time, bottleneck identification, optimization recommendations), but the description is muddled with formatting issues ('Execute this skill enables AI assistant') and truncated ('the...'), reducing clarity of the concrete actions listed.	2 / 3
Completeness	Explicitly answers both 'what' (profile application performance, analyze CPU/memory/execution time, identify bottlenecks, provide optimization recommendations) and 'when' (Use when optimizing performance, triggered by phrases like 'optimize', 'performance', 'speed up').	3 / 3
Trigger Term Quality	Includes some natural trigger terms like 'optimize', 'performance', 'speed up', 'bottleneck identification', and 'performance analysis', but misses common variations like 'slow', 'profiling', 'latency', 'benchmark', 'CPU', 'memory leak', or 'execution time'.	2 / 3
Distinctiveness Conflict Risk	The performance profiling niche is somewhat specific, but broad terms like 'optimize' and 'performance' could easily overlap with other optimization-related skills (e.g., database optimization, code refactoring, build optimization). The description doesn't narrow sufficiently to application runtime profiling.	2 / 3
	Total	9 / 12 Passed

Implementation

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

This skill content is almost entirely devoid of actionable information. It reads like a marketing description or placeholder template rather than an operational guide for Claude. Every section describes what the skill does in abstract terms without providing any concrete commands, code examples, tool invocations, or specific profiling techniques for any of the mentioned stacks (Node.js, Python, Java).

Suggestions

Replace abstract descriptions with concrete, executable profiling commands for each stack (e.g., `node --prof app.js`, `python -m cProfile script.py`, `jcmd <pid> JFR.start`).

Add actual code examples showing how to interpret profiling output, including sample output snippets and what to look for in each.

Remove filler sections (Overview, When to Use, Integration, Prerequisites, Instructions, Output, Error Handling, Resources) that contain only generic platitudes, and consolidate into a lean quick-start with stack-specific subsections.

Add a concrete workflow with validation steps, e.g., 'Run profiler → parse output → identify top N hotspots → suggest specific optimization patterns → verify improvement with re-profile'.

Dimension	Reasoning	Score
Conciseness	Extremely verbose with no actionable density. Explains concepts Claude already knows (what profiling is, what CPU usage means), includes filler sections like 'Overview', 'When to Use', 'Integration', 'Prerequisites', 'Instructions', 'Output', 'Error Handling', and 'Resources' that are all vague platitudes adding no real information. Nearly every section could be deleted without losing useful content.	1 / 3
Actionability	No concrete code, commands, or executable guidance anywhere. The examples describe what the skill 'will do' in abstract terms rather than showing actual profiling commands, code snippets, or tool invocations. Instructions like 'Invoke this skill when the trigger conditions are met' and 'Provide necessary context and parameters' are completely vacuous.	1 / 3
Workflow Clarity	The 'How It Works' section lists abstract steps like 'Identify Application Stack' and 'Analyze Performance Metrics' without any concrete commands, tool calls, or validation checkpoints. There are no feedback loops, no error recovery steps, and no actual workflow that Claude could follow to perform profiling.	1 / 3
Progressive Disclosure	Monolithic wall of text with many sections that are all shallow and vague. No references to external files, no clear hierarchy of information. The 'Resources' section just says 'Project documentation' and 'Related skills and commands' without any actual links or file references.	1 / 3
	Total	4 / 12 Passed

Validation

81%

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 — 9 / 11 Passed

Validation for skill structure

Criteria	Description	Result
allowed_tools_field	'allowed-tools' contains unusual tool name(s)	Warning
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata	Warning

	Total	9 / 11 Passed

Repository: jeremylongshore/claude-code-plugins-plus-skills
Commit: c8a915c

Reviewed: 4 days ago

Table of Contents

Discovery Implementation Validation

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