jobe-skills/prometheus-oidc-query
Run PromQL queries, inspect alert state, and troubleshoot OAuth2 or OIDC client-credentials access to Prometheus-compatible APIs.
94
94%
Does it follow best practices?
Impact
Pending
No eval scenarios have been run
Passed
No known issues
Quality
Discovery
100%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 strong skill description that clearly defines both what the skill does and when to use it. It includes specific concrete actions, natural trigger terms covering Prometheus/Grafana/PromQL/monitoring vocabulary, and an explicit 'Use when' clause. The combination of monitoring queries with OAuth2/OIDC authentication creates a highly distinctive niche.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions: run instant queries via `prom_query.py`, inspect `ALERTS` states, refresh/check OAuth2 tokens, and validate query/config prerequisites before making network calls. | 3 / 3 |
Completeness | Clearly answers both 'what' (run instant queries, inspect ALERTS, refresh tokens, validate prerequisites) and 'when' (explicit 'Use when' clause specifying Prometheus metrics, monitoring data, Grafana/PromQL query support on OAuth2/OIDC-protected endpoints). | 3 / 3 |
Trigger Term Quality | Includes strong natural keywords users would say: 'Prometheus metrics', 'monitoring data', 'Grafana', 'PromQL', 'OAuth2', 'OIDC', 'ALERTS', 'tokens'. These cover common variations of how users would describe this need. | 3 / 3 |
Distinctiveness Conflict Risk | Highly distinctive niche combining Prometheus/PromQL querying with OAuth2/OIDC authentication. The specific tool name `prom_query.py` and the combination of monitoring + auth concerns make it very unlikely to conflict with other skills. | 3 / 3 |
Total | 12 / 12 Passed |
Implementation
85%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This is a well-structured skill with clear, actionable workflows, explicit validation checkpoints, and appropriate progressive disclosure. Its main weakness is mild redundancy in the safety/trust sections, where the 'treat responses as untrusted' guidance is stated multiple times across sections. Overall it is a strong skill that effectively guides Claude through a specific operational task.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill is mostly efficient and avoids explaining concepts Claude already knows, but the 'Safety and result handling' section is somewhat verbose with repeated emphasis on treating responses as untrusted data (stated in both 'Trust boundary' and 'Safety' sections). Some bullet points could be consolidated. | 2 / 3 |
Actionability | Provides specific, executable commands for each step (e.g., `python3 scripts/prom_query.py query --expr '<promql>'`, `python3 scripts/check_config.py`), lists exact environment variable names, and gives concrete decision criteria for which command to run. Copy-paste ready. | 3 / 3 |
Workflow Clarity | The workflow is clearly sequenced with an explicit validation-first step (check_config), a stop condition on invalid config, a decision tree for choosing the right command, and clear error handling guidance (report error and stop). The feedback loop of 'validate config → stop if invalid → proceed only if valid' is well-defined. | 3 / 3 |
Progressive Disclosure | The SKILL.md serves as a clear overview with well-organized sections, and appropriately defers detailed command syntax, output structures, and error codes to a single one-level-deep reference file (`references/scripts.md`). Navigation is clearly signaled. | 3 / 3 |
Total | 11 / 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
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