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

—

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

Content

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

This skill is almost entirely boilerplate and template filler with no actionable content. It lacks any concrete code examples, specific profiling commands, tool configurations, or executable workflows. Every section describes what the skill does in abstract terms without providing Claude any actual guidance on how to perform profiling tasks.

Suggestions

Replace abstract descriptions with concrete, executable profiling commands for each supported stack (e.g., `node --prof`, `py-spy`, `async-profiler` commands with actual flags and usage patterns).

Add real code examples showing how to instrument and profile applications, including how to interpret output (e.g., flame graph reading, heap snapshot analysis).

Remove all boilerplate sections (Prerequisites, Instructions, Output, Error Handling, Resources) that contain only generic placeholder text, and replace with specific validation steps and error recovery workflows.

Define what the 'application-profiler plugin' actually is and how to invoke it, or remove references to it if it doesn't exist as a concrete tool.

Dimension	Reasoning	Score
Conciseness	Extremely verbose with extensive padding. Sections like 'Overview', 'How It Works', 'When to Use This Skill', 'Integration', 'Prerequisites', 'Instructions', 'Output', 'Error Handling', and 'Resources' are all filler that explain nothing Claude doesn't already know. The entire file reads like a template with boilerplate rather than actionable content.	1 / 3
Actionability	No concrete code, commands, or executable guidance anywhere. Examples describe what the skill 'will do' in abstract terms ('Activate the application-profiler plugin') without showing any 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 vague.	1 / 3
Workflow Clarity	The 'How It Works' section lists abstract steps like 'Identifies main application entry points' without any concrete commands, validation checkpoints, or error recovery loops. The 'Instructions' section is generic boilerplate with no real sequencing. There is no validation or feedback mechanism described for any step.	1 / 3
Progressive Disclosure	No bundle files exist, yet the content is a monolithic wall of vague sections with no meaningful structure. References to 'Project documentation' and 'Related skills and commands' point nowhere. The content that is present is all filler that could be drastically condensed, and there's no useful layering of information.	1 / 3
	Total	4 / 12 Passed

Description

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', truncated text with 'the...'), uses first/third person inconsistently, and the trigger terms, while present, are too broad and could conflict with other optimization-related skills. The garbled opening and truncation significantly undermine professionalism and clarity.

Suggestions

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

Add more specific and varied trigger terms such as 'slow', 'profiling', 'benchmark', 'latency', 'memory leak', 'CPU usage' to improve trigger term coverage.

Narrow the scope to distinguish from other optimization skills — specify what type of applications or languages this applies to (e.g., 'Python applications', 'web services') to reduce conflict risk.

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.	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. Trigger with phrases like optimize, performance, or 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', 'benchmark', 'latency', 'CPU', 'memory leak', etc.	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 the scope enough to a clear niche.	2 / 3
	Total	9 / 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: 00c0702

Reviewed: 4 days ago

Table of Contents

Discovery Implementation Validation

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