monitoring-cpu-usage

Monitor this skill enables AI assistant to monitor and analyze cpu usage patterns within applications. it helps identify cpu hotspots, analyze algorithmic complexity, and detect blocking operations. use this skill when the user asks to "monitor cpu usage", "opt... Use when setting up monitoring or observability. Trigger with phrases like 'monitor', 'metrics', or 'alerts'.

Quality

29%

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/cpu-usage-monitor/skills/monitoring-cpu-usage/SKILL.md

Quality

Discovery

59%

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 suffers from an identity crisis: it starts as a CPU-specific monitoring skill but then broadens its trigger scope to generic monitoring and observability, creating high conflict risk. The truncation ('opt...') suggests the description was cut off, losing potentially useful detail. The explicit 'Use when' clause is a strength, but the mismatch between specific capabilities and overly broad triggers undermines its effectiveness.

Suggestions

Align the trigger terms with the actual CPU-specific scope — use phrases like 'CPU hotspot', 'CPU profiling', 'algorithmic complexity', 'blocking operations' instead of generic 'metrics' or 'alerts'.

Fix the truncated text ('opt...') to ensure the full description is readable and complete.

Narrow the 'Use when' clause to CPU-specific scenarios to avoid conflicting with general monitoring or observability skills.

Dimension	Reasoning	Score
Specificity	The description names the domain (CPU monitoring) and lists some actions like 'identify cpu hotspots, analyze algorithmic complexity, and detect blocking operations', but the truncation ('opt...') cuts off potentially more specific capabilities, and the second half shifts to generic monitoring/observability language.	2 / 3
Completeness	The description answers both 'what' (monitor and analyze CPU usage patterns, identify hotspots, analyze complexity, detect blocking operations) and 'when' (explicit 'Use when setting up monitoring or observability' with trigger phrases). Both are present and explicit.	3 / 3
Trigger Term Quality	Includes some natural trigger terms like 'monitor cpu usage', 'monitor', 'metrics', 'alerts', but there's a mismatch between the CPU-specific first half and the generic monitoring triggers in the second half. Missing terms like 'performance', 'profiling', 'CPU bottleneck', 'slow', etc.	2 / 3
Distinctiveness Conflict Risk	The description is internally conflicted — the first half is about CPU-specific analysis while the second half broadens to generic 'monitoring or observability' with triggers like 'metrics' and 'alerts', which would easily conflict with any general monitoring, APM, or alerting skill.	1 / 3
	Total	8 / 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 is almost entirely generic boilerplate with no actionable content. It describes what a CPU monitoring skill would theoretically do without providing any concrete tools, code, commands, or techniques. Multiple sections are filler ('The skill produces structured output relevant to the task') and the referenced 'cpu-usage-monitor plugin' is never defined or explained.

Suggestions

Replace the abstract descriptions with concrete, executable code examples showing actual CPU profiling techniques (e.g., using cProfile, py-spy, or perf) with specific commands and code snippets.

Remove all generic boilerplate sections (Instructions, Output, Error Handling, Resources) that contain no skill-specific information and waste tokens.

Define what the 'cpu-usage-monitor plugin' actually is — provide installation, invocation commands, and expected output formats, or remove the reference if it doesn't exist.

Add concrete before/after code examples showing specific CPU optimizations (e.g., replacing an O(n²) loop with an O(n log n) approach) rather than just describing what the skill 'will do'.

Dimension	Reasoning	Score
Conciseness	Extremely verbose with extensive padding. Explains obvious concepts Claude already knows ('This skill empowers Claude to analyze code...'), includes vague filler sections like 'Output: The skill produces structured output relevant to the task', and the 'Instructions' section is entirely generic boilerplate with no actual information.	1 / 3
Actionability	No concrete code, commands, or executable guidance anywhere. The entire skill describes what it will do in abstract terms ('The skill will analyze...') without providing any actual tools, commands, code snippets, or specific techniques. References to a 'cpu-usage-monitor plugin' with no details on how to invoke it or what it actually is.	1 / 3
Workflow Clarity	The 'How It Works' section lists three abstract steps with no specifics. The 'Instructions' section is four completely generic lines ('Invoke this skill when the trigger conditions are met') that provide zero workflow guidance. No validation checkpoints, no concrete sequencing, no error recovery loops.	1 / 3
Progressive Disclosure	Monolithic wall of text with no references to external files, no bundle files, and no structured navigation. Content is poorly organized with multiple redundant sections (Overview, How It Works, When to Use, Examples all repeat similar vague information). Sections like 'Resources' point to nothing specific ('Project documentation', 'Related skills and commands').	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: 4801da6

Reviewed: 5 days ago

Table of Contents

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