grafana
Investigate production issues, query logs and metrics, and explore dashboards on the Mattermost Grafana instance at grafana.internal.mattermost.com.
69
85%
Does it follow best practices?
Impact
—
No eval scenarios have been run
Passed
No known issues
Quality
Discovery
82%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 description with specific actions, good natural trigger terms, and excellent distinctiveness due to the named internal system. Its main weakness is the absence of an explicit 'Use when...' clause, which would help Claude know precisely when to select this skill over others.
Suggestions
Add an explicit 'Use when...' clause, e.g., 'Use when the user asks about production incidents, wants to check Grafana dashboards, or needs to query logs and metrics from grafana.internal.mattermost.com.'
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions: 'investigate production issues', 'query logs and metrics', and 'explore dashboards'. Also specifies the exact target system (Mattermost Grafana instance at grafana.internal.mattermost.com). | 3 / 3 |
Completeness | Clearly answers 'what does this do' (investigate production issues, query logs/metrics, explore dashboards on Grafana), but lacks an explicit 'Use when...' clause or equivalent trigger guidance, which caps this at 2 per the rubric. | 2 / 3 |
Trigger Term Quality | Includes strong natural keywords users would say: 'production issues', 'logs', 'metrics', 'dashboards', 'Grafana', and the specific internal URL. These are terms engineers naturally use when debugging production problems. | 3 / 3 |
Distinctiveness Conflict Risk | Highly distinctive due to the specific internal Grafana instance URL and the combination of production investigation with Mattermost's specific infrastructure. Very unlikely to conflict with other skills. | 3 / 3 |
Total | 11 / 12 Passed |
Implementation
87%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This is a strong, well-structured skill that provides Claude with all the concrete details needed to investigate production issues on Grafana. The pre-cached UIDs, specific tool names with parameters, and namespace mapping tables are excellent. The main weakness is the workflow section, which could benefit from explicit validation/error-handling steps (e.g., what to do when a query returns no results or a UID is rejected).
Suggestions
Add error recovery guidance to the workflow, e.g., 'If a query returns no results, widen the time range or check label values with list_loki_label_values' and 'If a UID fails, fall back to list_datasources'.
Add a validation step in the workflow such as 'Verify findings by cross-referencing log patterns with metric trends before synthesizing conclusions'.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The content is lean and efficient. It provides only what Claude needs: specific UIDs, tool names, query patterns, and workflow steps. No unnecessary explanations of what Grafana, Loki, or Prometheus are. Every section earns its place. | 3 / 3 |
Actionability | Provides specific tool names (query_loki_logs, query_prometheus, search_dashboards, etc.), exact parameter names and values (datasourceUid, query, timeRange), concrete query examples, and pre-cached UIDs. Claude can immediately execute these instructions. | 3 / 3 |
Workflow Clarity | The 6-step workflow is clearly sequenced and logical, but lacks explicit validation checkpoints or error recovery steps. For production investigation (a potentially high-stakes operation), there's no guidance on what to do if queries return unexpected results, if UIDs fail, or how to verify findings before sharing conclusions. | 2 / 3 |
Progressive Disclosure | For a skill with no bundle files, the content is well-organized with clear sections (Environment, Namespace identifiers, Data source UIDs, Querying logs, Querying metrics, Finding dashboards, Generating links, Workflow). The content is appropriately sized for a single file and uses tables effectively for reference data. | 3 / 3 |
Total | 11 / 12 Passed |
Validation
90%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 10 / 11 Passed
Validation for skill structure
| Criteria | Description | Result |
|---|---|---|
allowed_tools_field | 'allowed-tools' contains unusual tool name(s) | Warning |
Total | 10 / 11 Passed | |
- Repository
- mattermost/mattermost-ai-marketplace
- Commit
349d5ed
- Reviewed
Table of Contents
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