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kopai/create-dashboard

Create observability dashboards from OTEL metrics, logs, and traces using Kopai. Use when building metric visualizations, monitoring views, KPI panels, or when the user wants to see their telemetry data in a dashboard — even if they don't say "dashboard" explicitly. Also use when other skills or workflows need to present telemetry data visually (e.g. after root cause analysis).

77

Quality

97%

Does it follow best practices?

Impact

No eval scenarios have been run

SecuritybySnyk

Passed

No known issues

Overview
Quality
Evals
Security
Files

Quality

Content

92%

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 concrete, executable guidance for creating dashboards with Kopai. The dynamic schema/metrics discovery via shell commands is an excellent pattern that keeps the skill current. The main weakness is the vague reference to rules files without listing specific filenames, which slightly undermines navigation.

Suggestions

List the actual rule file names explicitly (e.g., 'See [rules/workflow.md](rules/workflow.md) for detailed tree structure and error handling rules') instead of the generic 'rules/<rule-name>.md' pattern.

DimensionReasoningScore

Conciseness

The content is lean and efficient. It doesn't explain what OTEL, dashboards, or metrics are. Every section serves a purpose — schema discovery, workflow, example, component table, and rules reference. The dynamic shell commands for schema/metrics are a smart use of tokens.

3 / 3

Actionability

Provides fully executable CLI commands at every step, a complete copy-paste-ready bash example with real JSON structure, and a concrete component compatibility table. Claude can immediately execute these commands without guessing.

3 / 3

Workflow Clarity

The 4-step workflow is clearly sequenced with an explicit validation checkpoint in step 4 that includes a feedback loop: on error, re-run metrics discover, fix the tree, and retry. This covers the validate -> fix -> retry pattern appropriately.

3 / 3

Progressive Disclosure

References `rules/<rule-name>.md` for detailed rules which is good progressive disclosure, but the reference is vaguely signaled — 'Read rules/<rule-name>.md for details' without listing the actual rule file names. The dynamic shell commands for schema and metrics are clever but no bundle files were provided to verify the referenced paths exist.

2 / 3

Total

11

/

12

Passed

Description

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 an excellent skill description that clearly defines what the skill does (create observability dashboards from OTEL telemetry data using Kopai), when to use it (with explicit trigger scenarios including implicit and cross-skill cases), and occupies a distinct niche. It uses proper third-person voice, includes rich natural trigger terms, and even anticipates edge cases where the skill should be selected without the user explicitly requesting a dashboard.

DimensionReasoningScore

Specificity

Lists multiple concrete actions: 'Create observability dashboards from OTEL metrics, logs, and traces using Kopai' and specifies sub-tasks like 'metric visualizations, monitoring views, KPI panels'. The tool name (Kopai) and data types (OTEL metrics, logs, traces) are explicitly named.

3 / 3

Completeness

Clearly answers both 'what' (create observability dashboards from OTEL metrics/logs/traces using Kopai) and 'when' (explicit 'Use when...' clause covering multiple scenarios including implicit triggers and cross-skill handoffs).

3 / 3

Trigger Term Quality

Excellent coverage of natural trigger terms: 'observability dashboards', 'OTEL metrics', 'logs', 'traces', 'metric visualizations', 'monitoring views', 'KPI panels', 'telemetry data', 'dashboard'. Also anticipates implicit triggers ('even if they don't say dashboard explicitly') and cross-skill triggers ('after root cause analysis').

3 / 3

Distinctiveness Conflict Risk

Highly distinctive with a clear niche: OTEL-based observability dashboards via Kopai. The specific tool name, data types (OTEL metrics, logs, traces), and use cases (KPI panels, monitoring views) make it very unlikely to conflict with other skills.

3 / 3

Total

12

/

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.

Validation11 / 11 Passed

Validation for skill structure

No warnings or errors.

Reviewed

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