jbvc/observability-monitoring-monitor-setup
You are a monitoring and observability expert specializing in implementing comprehensive monitoring solutions. Set up metrics collection, distributed tracing, log aggregation, and create insightful da
42
42%
Does it follow best practices?
Impact
Pending
No eval scenarios have been run
Passed
No known issues
Quality
Discovery
32%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 truncated mid-word, rendering it incomplete and unprofessional. It uses second-person voice ('You are') instead of the required third-person voice, and lacks any 'Use when...' clause to guide skill selection. While it names some relevant monitoring capabilities, the truncation and missing trigger guidance significantly undermine its effectiveness.
Suggestions
Complete the truncated description and add an explicit 'Use when...' clause with trigger terms like 'monitoring setup', 'observability', 'alerting', 'dashboards', 'Prometheus', 'Grafana', 'tracing'.
Rewrite in third person voice (e.g., 'Sets up metrics collection, distributed tracing, and log aggregation') instead of second person ('You are').
Add more specific concrete actions and common tool names to improve trigger term coverage and distinctiveness from general DevOps or infrastructure skills.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Names the domain (monitoring/observability) and lists some actions like 'metrics collection, distributed tracing, log aggregation, and create insightful da[shboards]', but the description appears truncated and uses second-person framing ('You are') which is problematic. The actions listed are somewhat specific but not fully comprehensive. | 2 / 3 |
Completeness | The description addresses 'what' (set up monitoring solutions) but completely lacks a 'Use when...' clause or any explicit trigger guidance. Additionally, the description is truncated mid-word, making it incomplete. Per rubric guidelines, missing 'Use when' caps completeness at 2, and the truncation further reduces it. | 1 / 3 |
Trigger Term Quality | Includes relevant keywords like 'monitoring', 'observability', 'metrics collection', 'distributed tracing', 'log aggregation', but misses common user variations like 'alerts', 'Prometheus', 'Grafana', 'dashboards', 'APM', or 'logging'. The truncation also limits keyword coverage. | 2 / 3 |
Distinctiveness Conflict Risk | The monitoring/observability domain is somewhat specific, but terms like 'metrics collection' and 'log aggregation' could overlap with DevOps, infrastructure, or logging-specific skills. Without clear trigger boundaries, there's moderate conflict risk. | 2 / 3 |
Total | 7 / 12 Passed |
Implementation
22%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This skill is a high-level template with no actionable content. It describes what outputs should look like but provides zero concrete implementation guidance—no code snippets, no specific tool configurations, no example metrics or dashboard JSON. It relies entirely on an external resource file for substance, making the SKILL.md itself nearly useless as a standalone reference.
Suggestions
Add concrete, executable examples for at least one pillar (e.g., a Prometheus scrape config, an OpenTelemetry tracing setup snippet, or a Grafana dashboard JSON template).
Replace the generic instructions ('Clarify goals', 'Apply best practices') with a specific sequenced workflow, e.g.: 1. Deploy Prometheus with provided config → 2. Instrument services with OpenTelemetry → 3. Verify metrics endpoint → 4. Import dashboard templates → 5. Configure alerting rules.
Add validation checkpoints to the workflow, such as 'Verify metrics are being scraped: curl localhost:9090/api/v1/targets' or 'Check trace propagation with a test request'.
Remove the boilerplate 'Use this skill when / Do not use this skill when' sections and the repeated persona description to save tokens for actual technical content.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill includes some unnecessary framing (e.g., 'You are a monitoring and observability expert' repeated from description, 'Use this skill when/Do not use this skill when' sections that are generic boilerplate). The context section restates what's already implied. However, it's not excessively verbose. | 2 / 3 |
Actionability | The skill provides no concrete code, commands, configuration examples, or specific tool instructions. It lists abstract output categories (e.g., 'Complete monitoring stack design', 'Ready-to-use Grafana dashboards') without any actual implementation details, executable snippets, or specific guidance. Instructions like 'Clarify goals' and 'Apply relevant best practices' are vague directives. | 1 / 3 |
Workflow Clarity | There is no clear sequenced workflow with validation checkpoints. The instructions are four generic bullet points ('Clarify goals', 'Apply best practices', 'Provide actionable steps') that don't constitute a real workflow. The output format lists deliverables but not a process to produce them. No validation or feedback loops are present for what could be complex infrastructure operations. | 1 / 3 |
Progressive Disclosure | The skill references `resources/implementation-playbook.md` for detailed patterns, which is a reasonable one-level-deep reference. However, the main content itself is too thin to serve as a useful overview—it's essentially a table of contents with no substantive quick-start content. The reference is mentioned but not clearly signaled with what it contains. | 2 / 3 |
Total | 6 / 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
Table of Contents