detecting-memory-leaks

Detect potential memory leaks and analyze memory usage patterns in code. Use when troubleshooting performance issues related to memory growth or identifying leak sources. Trigger with phrases like "detect memory leaks", "analyze memory usage", or "find memory issues".

Quality

—

Does it follow best practices?

Impact

—

No eval scenarios have been run

Securityby

Passed

No known issues

Quality

Content

35%

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

The body is well-organized into sections but describes what the skill does rather than giving Claude concrete, executable guidance, and it fails to connect to the bundled scripts and references that would make it actionable. Workflow steps lack validation checkpoints.

Suggestions

Replace the abstract Instructions with concrete, executable guidance — show how to invoke analyze_memory.py and generate_report.py with real commands and expected output.

Add a validation/verification checkpoint to the workflow so findings are confirmed (e.g. cross-check a suspected leak with a profiling run) before the report is generated.

Link the existing bundle files from the body (e.g. 'See scripts/analyze_memory.py for the analysis driver') and move the generic Resources bullets into references/ to improve progressive disclosure.

Dimension	Reasoning	Score
Conciseness	Sections like Overview, How It Works, and When to Use restate the description and could be trimmed, but it avoids explaining basic concepts Claude already knows.	2 / 3
Actionability	The Instructions list abstract steps ('Analyze code for common memory leak patterns') with no executable code or commands, and the bundled scripts are never referenced or shown in use.	1 / 3
Workflow Clarity	A numbered sequence exists (Instructions 1-6), but there are no validation checkpoints or feedback loops for verifying findings before reporting.	2 / 3
Progressive Disclosure	The body has clear sections but does not signal the actual bundle files (analyze_memory.py, generate_report.py, references/, assets/), and content that could live in references is kept inline.	2 / 3
	Total	7 / 12 Passed

Description

90%

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

A well-constructed description that clearly states purpose, usage conditions, and natural trigger phrases for a distinct niche. Its only weakness is moderate specificity, naming two fairly general actions rather than a richer set of concrete capabilities.

Dimension	Reasoning	Score
Specificity	Names the domain and two actions ('Detect potential memory leaks and analyze memory usage patterns in code') but stops short of the multiple specific concrete actions that define the top anchor.	2 / 3
Completeness	It states what the skill does and gives explicit trigger guidance via a 'Use when...' clause plus 'Trigger with phrases like...', satisfying both what and when.	3 / 3
Trigger Term Quality	Phrases like 'detect memory leaks', 'analyze memory usage', and 'find memory issues' are natural terms a user would actually say, giving good coverage.	3 / 3
Distinctiveness Conflict Risk	The memory-leak niche is clear and all triggers are memory-specific, making it unlikely to fire for an unrelated skill.	3 / 3
	Total	11 / 12 Passed

Validation

87%

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 — 14 / 16 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	14 / 16 Passed

Repository: jeremylongshore/claude-code-plugins-plus-skills
Commit: 3022dd3

Reviewed: 1 day ago

Table of Contents

Discovery Implementation Validation

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