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'.
33
29%
Does it follow best practices?
Impact
—
No eval scenarios have been run
Passed
No known issues
Optimize this skill with Tessl
npx tessl skill review --optimize ./plugins/performance/cpu-usage-monitor/skills/monitoring-cpu-usage/SKILL.mdQuality
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 mismatch between specific capabilities and overly broad trigger terms undermines its effectiveness for skill selection.
Suggestions
Align the trigger terms with the actual CPU-focused capabilities — use phrases like 'CPU profiling', 'CPU bottleneck', 'performance hotspot', 'algorithmic complexity' 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 rather than broad 'monitoring or observability' to reduce conflict with other monitoring-related 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 overlap heavily with any general monitoring, APM, or observability skill. | 1 / 3 |
Total | 8 / 12 Passed |
Implementation
0%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 with no actionable content. It describes what CPU monitoring conceptually involves but provides zero concrete guidance—no code examples, no specific tools or commands, no profiling techniques, and no real workflow. The generic sections (Prerequisites, Error Handling, Resources, Instructions) contain placeholder text that wastes tokens without adding value.
Suggestions
Replace the abstract 'How It Works' and 'Examples' sections with concrete, executable code showing actual CPU profiling (e.g., using cProfile, py-spy, or similar tools) with real input/output examples.
Remove all boilerplate sections that contain only generic placeholder content (Prerequisites, Error Handling, Resources, Output, Integration) to dramatically improve conciseness.
Add a concrete workflow with specific commands for profiling, analyzing output, and validating optimizations—e.g., 'Run `python -m cProfile -s cumtime script.py > profile.txt`, then analyze the top 10 functions by cumulative time.'
Define what the 'cpu-usage-monitor plugin' actually is, how to invoke it, and what its output looks like, or remove the reference if it doesn't exist.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Extremely verbose with extensive padding. Explains obvious concepts Claude already knows ('This skill empowers Claude to analyze code...'), includes generic boilerplate sections (Prerequisites, Error Handling, Resources, Integration) with no substantive content, and the 'Instructions' section is entirely vacuous ('Invoke this skill when the trigger conditions are met'). | 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 how to actually perform CPU analysis. There are no specific tools, commands, profiling techniques, or code snippets. References to a 'cpu-usage-monitor plugin' with no details on how to invoke it. | 1 / 3 |
Workflow Clarity | The 'How It Works' section lists three abstract steps with no concrete details. The 'Instructions' section is entirely generic ('Invoke this skill when the trigger conditions are met'). No validation checkpoints, no feedback loops, no actual workflow that Claude could follow to perform CPU monitoring or analysis. | 1 / 3 |
Progressive Disclosure | Monolithic wall of text with no references to external files and no bundle files provided. Content is poorly organized with multiple boilerplate sections (Prerequisites, Error Handling, Resources, Output) that contain only placeholder-level content, adding noise without value. | 1 / 3 |
Total | 4 / 12 Passed |
Validation
81%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 | |
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