prometheus-configuration
Set up Prometheus for comprehensive metric collection, storage, and monitoring of infrastructure and applications. Use when implementing metrics collection, setting up monitoring infrastructure, or configuring alerting systems.
Install with Tessl CLI
npx tessl i github:Dicklesworthstone/pi_agent_rust --skill prometheus-configuration82
Quality
73%
Does it follow best practices?
Impact
94%
1.22xAverage score across 3 eval scenarios
Optimize this skill with Tessl
npx tessl skill review --optimize ./tests/ext_conformance/artifacts/agents-wshobson/observability-monitoring/skills/prometheus-configuration/SKILL.mdDiscovery
75%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 solid description with good structure including an explicit 'Use when' clause and clear Prometheus-specific focus. The main weaknesses are moderate specificity (could list more concrete actions) and trigger term coverage (missing common related terms like 'observability', 'PromQL', or 'scraping').
Suggestions
Add more specific concrete actions like 'configure scrape targets', 'write PromQL queries', 'define alert rules', or 'set up exporters'
Expand trigger terms to include related concepts users might mention: 'observability', 'PromQL', 'scraping', 'exporters', 'time-series metrics'
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Names the domain (Prometheus, monitoring) and some actions (metric collection, storage, monitoring, alerting), but lacks specific concrete actions like 'configure scrape targets', 'write PromQL queries', or 'set up alert rules'. | 2 / 3 |
Completeness | Clearly answers both what (set up Prometheus for metric collection, storage, and monitoring) and when (implementing metrics collection, setting up monitoring infrastructure, configuring alerting systems) with an explicit 'Use when' clause. | 3 / 3 |
Trigger Term Quality | Includes relevant keywords like 'Prometheus', 'metrics collection', 'monitoring infrastructure', and 'alerting systems', but misses common variations users might say like 'observability', 'scraping', 'PromQL', 'Grafana integration', or 'time-series database'. | 2 / 3 |
Distinctiveness Conflict Risk | The explicit mention of 'Prometheus' creates a clear niche that distinguishes it from generic monitoring skills or other monitoring tools like Datadog, Grafana, or CloudWatch. | 3 / 3 |
Total | 10 / 12 Passed |
Implementation
72%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This is a comprehensive Prometheus configuration skill with excellent actionability through complete, executable examples. The progressive disclosure is well-handled with clear references to supporting files. However, it could be more concise by removing redundant sections and would benefit from an explicit workflow that integrates validation steps into the configuration process.
Suggestions
Remove the 'Purpose' and 'When to Use' sections as they duplicate information already in the skill description and are inferable by Claude
Add an explicit numbered workflow at the top showing: 1) Create config -> 2) Validate with promtool -> 3) Deploy -> 4) Verify targets, with clear checkpoints and error recovery steps
Condense the 'Best Practices' section into a brief checklist or move to a reference file, as many items are general knowledge Claude already has
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill includes some unnecessary sections like 'Purpose' and 'When to Use' that repeat information Claude can infer. The architecture diagram and best practices list add value but could be more condensed. Overall mostly efficient but has padding. | 2 / 3 |
Actionability | Provides fully executable code examples throughout - Helm commands, Docker Compose files, complete YAML configurations, and validation commands. All examples are copy-paste ready with realistic values. | 3 / 3 |
Workflow Clarity | While individual sections are clear, there's no explicit end-to-end workflow with validation checkpoints. The validation section exists but isn't integrated into a 'configure -> validate -> deploy' sequence with feedback loops for error recovery. | 2 / 3 |
Progressive Disclosure | Well-structured with clear sections and appropriate references to external files (assets/prometheus.yml.template, references/scrape-configs.md, etc.). Navigation is clear with one-level-deep references and related skills linked at the end. | 3 / 3 |
Total | 10 / 12 Passed |
Validation
100%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 11 / 11 Passed
Validation for skill structure
No warnings or errors.
- Reviewed
Table of Contents
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