grafana-tst - SKILL.md Agent Skill

name: grafana-tst description: "Tools for interaction with grafana testing environment"

Grafana Test Environment Skill

Metadata

Skill Name: grafana-tst
Trigger Tag: #grafana-tst
MCP Server: Grafana MCP Server (Test)
Category: Monitoring (Test Environment)

Description

Access Grafana test/staging environment for observability data. Covers metrics (Prometheus), logs (Loki), traces (Tempo), profiling (Pyroscope), incident management, OnCall schedules, Sift investigations, alerting, and dashboard management. Use for development, testing, and staging workflows.

Capabilities

Metrics (Prometheus)

Query PromQL against test Prometheus datasources
List metric names, label names, label values, and metadata
Query histograms and percentiles

Logs (Loki)

Execute LogQL queries for test log retrieval
List log label names and values
Query log patterns and statistics
Stream log data with filtering and parsing

Traces (Tempo)

Find slow requests in test environment
Analyze distributed traces

Profiling (Pyroscope)

Fetch CPU, memory, goroutine profiles for test services
List profile types and label values per service

Incidents & OnCall

Create, list, and get incident details
Add timeline notes to incidents
List OnCall schedules, teams, users
Get current on-call users for a schedule

Sift Investigations

Create and retrieve automated investigations
Find error patterns in logs
Find slow requests across services

Alerting

List, get, create, update, delete alert rules
List contact points and notification policies
List alert groups from OnCall

Dashboards

Search, get, create, update dashboards
Get panel queries and dashboard summaries
Generate deeplinks to dashboards or panels
Render panel/dashboard images (PNG)
Create and manage annotations

Datasources

List, get datasources by name or UID

Activation

Include #grafana-tst tag in your prompt to activate this skill.

Usage Examples

Test Metrics

#grafana-tst Show CPU usage for test-api service in staging

Log Investigation

#grafana-tst Search Loki logs for errors in auth service last 1 hour

Dashboard Editing

#grafana-tst Add a new panel to the staging overview dashboard

Alert Testing

#grafana-tst Create a test alert rule for high memory usage

Trace Analysis

#grafana-tst Find slow requests for checkout service in test environment

Configuration

Do NOT search the filesystem for mcp-config.json or similar files directly. Do NOT read ~/.copilot/mcp-config.json directly — always route through custom agent file. MCP server is configured in the grafana-tst.agent.md custom agent file.

Environment Variables

Use environment variables defined in .copilot/.env.

Connectivity Check

Before taking any action, verify the Grafana Test MCP server is reachable:

Call list_datasources (with limit=1) as a lightweight probe.
If the call fails or returns an error, immediately stop and report: "Grafana test MCP server is unavailable. Cannot proceed."
Only proceed with the user's request after a successful probe response.

Best Practices

Use list_datasources first to find correct datasource UIDs before querying
Use list_prometheus_metric_names before writing PromQL
Use list_loki_label_names / list_loki_label_values before writing LogQL
Use query_loki_stats to check log volume before fetching entries
Use get_dashboard_summary instead of get_dashboard_by_uid for large dashboards
Never mix with #grafana-prd in the same request

Limitations

Test environment only — data does not reflect production
Different data retention policies than production
Write operations (create/update alerts, incidents) require appropriate permissions
Image rendering requires Grafana Image Renderer service

Environment Isolation

CRITICAL: Never use #grafana-tst and #grafana-prd in the same request. Choose one environment per query.

GitHub Copilot & LLM Optimization Context

Environment Indicator: You are operating within the GitHub Copilot CLI context. Always leverage native GitHub Copilot capabilities when interacting with codebases.
Model Optimization: This prompt is optimized specifically for Claude Opus 4.5.
- Leverage Claude Opus 4.5's deep comprehension and superior coding accuracy for complex architectural and logical tasks.
- Ensure responses are direct, code-focused, and minimize conversational filler to optimize for developer workflows.