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.
73
58%
Does it follow best practices?
Impact
100%
1.33xAverage score across 3 eval scenarios
Advisory
Suggest reviewing before use
Optimize this skill with Tessl
npx tessl skill review --optimize ./plugins/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 and misses common trigger term variations that would help Claude distinguish this skill from other monitoring-related skills. Adding more specific capabilities and related keywords would strengthen it.
Suggestions
Add more specific concrete actions such as 'configure scrape targets, write PromQL queries, set up Alertmanager rules, define recording rules, configure exporters'.
Expand trigger terms to include natural variations users might say: 'PromQL', 'scrape config', 'node_exporter', 'time series database', 'Alertmanager', '.yml prometheus config'.
| 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 highly actionable, production-ready Prometheus configurations with concrete examples, which is its main strength. However, it is far too verbose — inlining hundreds of lines of YAML that should live in referenced files, explaining architecture Claude already understands, and including generic best practices. The workflow could be improved by integrating validation steps into a clear sequential process with feedback loops.
Suggestions
Move the large YAML blocks (full prometheus.yml, recording rules, alert rules, scrape configs) into the referenced files and keep only minimal examples inline in SKILL.md
Remove the architecture diagram, 'Purpose' section, and 'When to Use' list — these duplicate the frontmatter description and explain concepts Claude already knows
Add a clear numbered workflow: install → configure → validate (with promtool) → fix errors → re-validate → deploy, integrating the validation commands into the sequence rather than as a separate section
Trim the 'Best Practices' to 3-4 non-obvious, project-specific items rather than 10 generic recommendations
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill is extremely verbose at ~300+ lines. It explains Prometheus architecture (which Claude already knows), includes a full ASCII diagram, lists 10 best practices that are generic knowledge, and provides exhaustive YAML configs that could be referenced externally. The 'When to Use' and 'Purpose' sections are redundant with each other and with the frontmatter description. | 1 / 3 |
Actionability | The content 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 examples are concrete and specific. | 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 | There are references to external files (assets/prometheus.yml.template, references/scrape-configs.md, references/recording-rules.md, scripts/validate-prometheus.sh), which is good. However, the SKILL.md itself is monolithic — it inlines massive YAML blocks for scrape configs, recording rules, and alert rules that should be in those referenced files instead. The overview doesn't stay concise enough to serve as a navigation hub. | 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
- wshobson/agents
- Commit
27a7ed9
- Reviewed
Table of Contents
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