groq-observability
Set up observability for Groq integrations: latency histograms, token throughput, rate limit gauges, cost tracking, and Prometheus alerts. Trigger with phrases like "groq monitoring", "groq metrics", "groq observability", "monitor groq", "groq alerts", "groq dashboard".
67
82%
Does it follow best practices?
Impact
—
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 specific capabilities (latency histograms, token throughput, rate limit gauges, cost tracking, Prometheus alerts) within a well-scoped domain (Groq observability). It includes explicit trigger phrases covering natural user language variations, and the narrow focus on Groq monitoring makes it highly distinctive and unlikely to conflict with other skills.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions: latency histograms, token throughput, rate limit gauges, cost tracking, and Prometheus alerts. These are clearly defined, actionable capabilities. | 3 / 3 |
Completeness | Clearly answers both 'what' (set up observability with specific metrics and alerts) and 'when' (explicit trigger phrases provided). The 'Trigger with phrases like...' clause serves as an explicit 'Use when' equivalent. | 3 / 3 |
Trigger Term Quality | Includes natural trigger phrases users would say: 'groq monitoring', 'groq metrics', 'groq observability', 'monitor groq', 'groq alerts', 'groq dashboard'. Good coverage of natural variations combining the domain (Groq) with common monitoring-related terms. | 3 / 3 |
Distinctiveness Conflict Risk | Highly distinctive due to the specific combination of Groq + observability/monitoring. The Groq-specific focus and Prometheus tooling make it unlikely to conflict with generic monitoring or other LLM provider skills. | 3 / 3 |
Total | 12 / 12 Passed |
Implementation
64%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This is a solid, actionable skill with executable code examples covering the full observability stack from instrumentation to alerting. Its main weaknesses are the lack of validation/verification steps in the workflow (e.g., how to confirm metrics are flowing correctly) and the monolithic structure that could benefit from splitting detailed configurations into separate files. The content is mostly concise but has some unnecessary explanatory commentary.
Suggestions
Add a validation step after Step 2 (e.g., 'Verify metrics are emitting: curl localhost:9090/metrics | grep groq_') and after Step 4 (e.g., 'Test alert rules: promtool check rules groq-alerts.yml').
Split the Prometheus alert rules (Step 4) and dashboard panel specs (Step 6) into separate bundle files (e.g., groq-alerts.yml and DASHBOARD.md) and reference them from the main skill.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The content is mostly efficient with good use of tables and code, but includes some unnecessary context (e.g., explaining Groq's speed advantage, 'Groq's main value prop' comments, the overview paragraph). The pricing table and metric definitions are useful but the dashboard panel descriptions could be more compact. | 2 / 3 |
Actionability | Provides fully executable TypeScript code for the instrumented client, Prometheus metric definitions, rate limit tracking, and complete YAML alert rules. Code is copy-paste ready with proper imports, types, and realistic configurations. | 3 / 3 |
Workflow Clarity | Steps are clearly numbered and sequenced (1-6), but there are no validation checkpoints or feedback loops. There's no guidance on verifying that metrics are actually being emitted correctly, no testing step to confirm Prometheus scraping works, and no verification that alert rules fire as expected. | 2 / 3 |
Progressive Disclosure | The content is well-structured with clear sections and a logical flow, but it's quite long (~200 lines of code) with everything inline. The Prometheus alert rules and dashboard panel specs could reasonably be split into separate reference files. The reference to 'groq-incident-runbook' is good but there are no bundle files to support it. | 2 / 3 |
Total | 9 / 12 Passed |
Validation
81%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 9 / 11 Passed
Validation for skill structure
| Criteria | Description | Result |
|---|---|---|
allowed_tools_field | 'allowed-tools' contains unusual tool name(s) | Warning |
frontmatter_unknown_keys | Unknown frontmatter key(s) found; consider removing or moving to metadata | Warning |
Total | 9 / 11 Passed | |
- Commit
a04d1a2
- Reviewed
Table of Contents
Is this your skill?
If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.