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.
72
58%
Does it follow best practices?
Impact
94%
1.22xAverage score across 3 eval scenarios
Advisory
Suggest reviewing before use
Optimize this skill with Tessl
npx tessl skill review --optimize ./tests/ext_conformance/artifacts/agents-wshobson/observability-monitoring/skills/prometheus-configuration/SKILL.mdQuality
Discovery
67%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 has a solid structure with an explicit 'Use when' clause and names the specific tool (Prometheus), which is good. However, it lacks granular concrete actions (e.g., configuring scrape targets, writing PromQL, setting up Alertmanager) and misses common trigger terms users might use. The broad monitoring/alerting language could cause overlap with other monitoring tool skills.
Suggestions
Add more specific concrete actions like 'configure scrape targets, write PromQL queries, set up Alertmanager rules, define recording rules' to improve specificity.
Include additional natural trigger terms users might say, such as 'PromQL', 'scrape config', 'exporters', 'node_exporter', 'time series database', or 'prometheus.yml'.
Sharpen distinctiveness by clarifying what differentiates this from other monitoring tools (e.g., 'Use when specifically working with Prometheus, not Datadog or other SaaS monitoring platforms').
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Names the domain (Prometheus, monitoring) and some actions (metric collection, storage, monitoring, alerting), but doesn't list multiple concrete specific actions like configuring scrape targets, writing PromQL queries, setting up Alertmanager rules, or creating recording rules. | 2 / 3 |
Completeness | Clearly answers both 'what' (set up Prometheus for metric collection, storage, and monitoring) and 'when' (explicit 'Use when' clause covering metrics collection, monitoring infrastructure, and alerting systems). | 3 / 3 |
Trigger Term Quality | Includes relevant keywords like 'Prometheus', 'metrics collection', 'monitoring infrastructure', and 'alerting systems', but misses common user variations like 'PromQL', 'scrape config', 'Grafana', 'exporters', 'node_exporter', 'time series', or 'dashboards'. | 2 / 3 |
Distinctiveness Conflict Risk | Mentioning 'Prometheus' specifically helps distinguish it, but the broad terms 'monitoring infrastructure' and 'alerting systems' could overlap with skills for Grafana, Datadog, Nagios, or other monitoring tools. | 2 / 3 |
Total | 9 / 12 Passed |
Implementation
50%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
The skill provides excellent, concrete, executable Prometheus configurations covering installation, scraping, recording rules, alerts, and validation. However, it is significantly over-verbose—much of the content (architecture diagrams, purpose sections, best practices lists) is common knowledge for Claude and wastes tokens. The workflow could be improved by integrating validation into a clear sequential process rather than listing it as a separate section.
Suggestions
Remove the architecture diagram, 'Purpose', 'When to Use', and 'Best Practices' sections—Claude already knows Prometheus concepts and these consume tokens without adding actionable value.
Move the detailed scrape configuration variants and recording rule examples into the referenced files (references/scrape-configs.md, references/recording-rules.md) and keep only the core prometheus.yml in the main skill.
Create an explicit numbered workflow: 1) Install → 2) Configure prometheus.yml → 3) Add rules → 4) Validate with promtool (fix and re-validate if errors) → 5) Deploy/restart → 6) Verify targets are up.
Consolidate the duplicate scrape config examples—the 'Scrape Configurations' section repeats patterns already shown in the main prometheus.yml.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill is extremely verbose at ~300+ lines. It explains Prometheus architecture (which Claude already knows), includes a 'When to Use' section restating the description, provides an ASCII diagram, and lists 10 best practices that are common knowledge. The architecture overview, purpose section, and much of the explanatory text add no value for Claude. | 1 / 3 |
Actionability | The skill provides fully executable, copy-paste ready configurations: complete prometheus.yml, Helm install commands, Docker Compose files, recording rules, alert rules, and validation commands. All code blocks are concrete and specific rather than pseudocode. | 3 / 3 |
Workflow Clarity | While there is a validation section with promtool commands, there's no clear sequenced workflow tying installation → configuration → validation → deployment together. The validation steps exist but aren't integrated into a feedback loop (e.g., 'validate before deploying, fix errors, re-validate'). For a configuration-heavy skill involving infrastructure changes, this gap is notable. | 2 / 3 |
Progressive Disclosure | References to external files are present (assets/prometheus.yml.template, references/scrape-configs.md, etc.) and a Reference Files section exists, but the main file contains enormous inline configuration blocks that could be in referenced files. The scrape configurations section largely duplicates what's already in the main prometheus.yml example. | 2 / 3 |
Total | 8 / 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.
- Repository
- Dicklesworthstone/pi_agent_rust
- Commit
6e3d68c
- Reviewed
Table of Contents
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