collecting-infrastructure-metrics
Collect comprehensive infrastructure performance metrics across compute, storage, network, containers, load balancers, and databases. Use when monitoring system performance or troubleshooting infrastructure issues. Trigger with phrases like "collect infrastructure metrics", "monitor server performance", or "track system resources".
44
46%
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/infrastructure-metrics-collector/skills/collecting-infrastructure-metrics/SKILL.mdQuality
Discovery
92%Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.
This is a well-crafted skill description that clearly communicates its purpose, lists specific capability domains, and provides explicit trigger guidance. Its main weakness is the broad scope covering many infrastructure areas, which could create overlap with more specialized monitoring skills. The description follows good practices with third-person voice, explicit 'Use when' clause, and natural trigger phrases.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific infrastructure domains: compute, storage, network, containers, load balancers, and databases. The description names concrete areas of capability beyond just a vague 'monitors infrastructure'. | 3 / 3 |
Completeness | Clearly answers both 'what' (collect comprehensive infrastructure performance metrics across multiple domains) and 'when' (explicit 'Use when monitoring system performance or troubleshooting infrastructure issues' plus trigger phrases). | 3 / 3 |
Trigger Term Quality | Includes natural trigger phrases like 'collect infrastructure metrics', 'monitor server performance', 'track system resources', plus domain terms like compute, storage, network, containers, load balancers, and databases that users would naturally mention. | 3 / 3 |
Distinctiveness Conflict Risk | While it specifies infrastructure metrics collection across multiple domains, it could overlap with more specific monitoring skills (e.g., a dedicated database monitoring skill or container monitoring skill). The broad scope covering six domains increases potential conflict with narrower skills. | 2 / 3 |
Total | 11 / 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 reads like a marketing overview or README rather than actionable instructions for Claude. It lacks any concrete code, configuration examples, or executable commands, instead describing what monitoring involves at a conceptual level that Claude already understands. The content is both verbose and empty of substance—it uses many tokens to say very little that's actionable.
Suggestions
Replace the abstract descriptions with concrete, executable configuration snippets for each monitoring tool (e.g., a Prometheus scrape config YAML, a Datadog agent config, a CloudWatch CLI command).
Add specific validation steps after each configuration action, such as 'Run `curl localhost:9090/targets` to verify Prometheus is scraping endpoints' or 'Check `datadog-agent status` to confirm agent is running'.
Remove sections that explain concepts Claude already knows (Overview, How It Works, When to Use, Best Practices, Integration) and replace them with a concise quick-start section with real commands.
Create separate reference files for each monitoring tool's configuration details and link to them from a lean SKILL.md overview to improve progressive disclosure.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The content is verbose and padded with information Claude already knows. Sections like 'Overview', 'How It Works', 'When to Use This Skill', 'Best Practices', and 'Integration' explain general monitoring concepts without adding actionable value. The 'Examples' describe what the skill 'will do' rather than showing concrete code or commands. | 1 / 3 |
Actionability | There is no executable code, no concrete commands, no configuration snippets, and no copy-paste ready examples anywhere in the skill. Everything is described at a high level ('Configure Prometheus to collect CPU metrics') without showing how. The examples describe outcomes rather than providing actual implementation steps. | 1 / 3 |
Workflow Clarity | The 'Instructions' section lists 6 high-level steps but none include specific commands, validation checkpoints, or feedback loops. For infrastructure configuration involving agent installation and metrics setup, there are no verification steps to confirm agents are running, metrics are being collected, or dashboards are functional. | 1 / 3 |
Progressive Disclosure | The content is a monolithic wall of text with no references to external files, no bundle files to support it, and no structured navigation. Content that could be split (e.g., per-agent configuration guides, dashboard templates, alert rule examples) is instead described vaguely inline without any actual detail. | 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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