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 is functional with a clear 'Use when' clause and identifies the core domain (Prometheus monitoring), but it lacks specificity in concrete actions and could benefit from more natural trigger terms that users would actually say. The generic monitoring terminology creates some overlap risk 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, configure exporters'.
Expand trigger terms to include common variations users would say: 'PromQL', 'prometheus.yml', 'exporters', 'node_exporter', 'scrape config', 'observability'.
| 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', 'Grafana', 'scrape config', 'exporters', 'node_exporter', 'prometheus.yml', or 'observability'. | 2 / 3 |
Distinctiveness Conflict Risk | Mentioning 'Prometheus' specifically helps distinguish it, but terms like 'monitoring infrastructure' and 'alerting systems' could overlap with skills for Datadog, Grafana, Nagios, or other monitoring tools. The description doesn't clearly delineate boundaries against other monitoring skills. | 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, executable Prometheus configurations but suffers significantly from verbosity—it reads more like comprehensive documentation than a focused skill for Claude. The inline content is far too long, with redundant examples and generic best practices that Claude already knows. The workflow lacks a clear sequential structure with validation checkpoints tying the pieces together.
Suggestions
Reduce content by 50-60%: remove the architecture diagram, trim best practices to only non-obvious ones, eliminate redundant scrape config examples (static targets appear twice), and move detailed recording/alert rules to referenced files.
Add a clear sequential workflow at the top: 'Install → Configure prometheus.yml → Add scrape targets → Create rules → Validate with promtool → Deploy → Verify targets are up' with explicit validation checkpoints.
Move the detailed alert rules and recording rules content into the referenced files (references/recording-rules.md, references/alert-rules.md) and keep only a minimal example inline.
Provide the referenced bundle files (assets/prometheus.yml.template, scripts/validate-prometheus.sh, etc.) so the progressive disclosure structure actually works.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill is extremely verbose at ~300+ lines. It includes an architecture diagram Claude doesn't need, explains basic concepts like what Prometheus does, lists 10 best practices that are generic knowledge, and provides redundant scrape configuration examples (static targets are shown twice). Much of this content is reference material Claude already knows. | 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 with real values. | 3 / 3 |
Workflow Clarity | While individual sections are clear, there's no overall workflow sequence guiding Claude through a Prometheus setup from start to finish. The validation section exists but is disconnected from the configuration steps—there's no explicit 'configure → validate → deploy → verify' flow with checkpoints or error recovery loops. | 2 / 3 |
Progressive Disclosure | The skill references external files (assets/prometheus.yml.template, references/scrape-configs.md, references/recording-rules.md, scripts/validate-prometheus.sh) which is good structure, but no bundle files are provided, making these references dead links. Additionally, too much detailed content (full scrape configs, full alert rules) is inline rather than in referenced files, creating a monolithic document. | 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
bbc5ade
- Reviewed
Table of Contents
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