grafana-plugin-scaffolding
Scaffold and automate Grafana plugin projects using @grafana/create-plugin. Use when creating panel plugins, data source plugins, app plugins, or backend plugins. Handles project scaffolding, Docker dev environment setup, and plugin configuration.
What this skill does
# Grafana Plugin Scaffolding Skill Automate Grafana plugin project creation using the official `@grafana/create-plugin` scaffolder. This skill handles project scaffolding, development environment setup, and initial configuration for all plugin types. **Supported Grafana Version:** v12.x+ only ## Instructions ### Step 1: Verify Prerequisites Before scaffolding, verify these tools are installed: ```bash # Check Node.js (v18+ required) node --version # Check npm npm --version # Check Docker (optional, for local development) docker --version ``` If prerequisites are missing, guide the user to install them: - Node.js: https://nodejs.org/ - Docker Desktop: https://www.docker.com/products/docker-desktop/ ### Step 2: Scaffold the Plugin Use the official `@grafana/create-plugin` tool: ```bash # Interactive scaffolding (recommended) npx @grafana/create-plugin@latest # The tool will prompt for: # - Plugin type (panel, datasource, app, scenesapp) # - Organization name (e.g., "myorg") # - Plugin name (e.g., "my-panel") # - Include backend? (y/n) ``` ### Step 3: Navigate and Install Dependencies ```bash # Navigate to the new plugin directory cd <orgName>-<pluginName>-<pluginType> # Install frontend dependencies npm install # Install backend dependencies (if backend plugin) go mod tidy ``` ### Step 4: Start Development Environment **Option A: Docker with Hot-Reload (Recommended)** The scaffolder generates a `docker-compose.yaml`. For enhanced development with file watching, use the template from `templates/docker-compose.yaml` which includes Docker Compose `develop` features. ```bash # Start Grafana with file watching (Docker Compose v2.22.0+) docker compose watch # Or standard start without watching docker compose up -d # Access Grafana at http://localhost:3000 # Login: admin / admin ``` With `docker compose watch`: - Frontend changes in `dist/` sync automatically (no restart) - Backend binary changes (`gpx_*`) trigger container restart - No manual rebuild-restart cycle needed **Option B: Manual** ```bash # Build and watch frontend npm run dev # Build backend (if applicable) mage -v # Configure Grafana to load unsigned plugins # Add to grafana.ini: plugins.allow_loading_unsigned_plugins = <plugin-id> ``` ### Step 5: Verify Plugin Installation 1. Open http://localhost:3000 2. Navigate to Administration > Plugins 3. Search for your plugin name 4. Verify it appears and can be added to dashboards ## Plugin Type Workflows ### Panel Plugin ```bash npx @grafana/create-plugin@latest # Select: panel # Enter: organization name # Enter: plugin name # Backend: No (panels don't need backend) ``` Post-scaffolding: 1. Edit `src/components/SimplePanel.tsx` for visualization logic 2. Edit `src/types.ts` for panel options interface 3. Edit `src/module.ts` for option configuration ### Data Source Plugin (Frontend Only) ```bash npx @grafana/create-plugin@latest # Select: datasource # Enter: organization name # Enter: plugin name # Backend: No ``` Post-scaffolding: 1. Edit `src/datasource.ts` for query logic 2. Edit `src/ConfigEditor.tsx` for connection settings 3. Edit `src/QueryEditor.tsx` for query builder UI ### Data Source Plugin (With Backend) ```bash npx @grafana/create-plugin@latest # Select: datasource # Enter: organization name # Enter: plugin name # Backend: Yes ``` Post-scaffolding: 1. Edit `pkg/plugin/datasource.go` for Go query logic 2. Implement `QueryData` and `CheckHealth` methods 3. Build backend: `mage -v` ### App Plugin ```bash npx @grafana/create-plugin@latest # Select: app # Enter: organization name # Enter: plugin name # Backend: Optional ``` Post-scaffolding: 1. Edit `src/pages/` for app pages 2. Update `plugin.json` includes for navigation 3. Add new pages as React components ## Development Commands ```bash # Frontend development (watch mode) npm run dev # Frontend production build npm run build # Backend build (Go plugins) mage -v # Run unit tests npm test # Run E2E tests (requires Grafana running) npx playwright test # Lint code npm run lint # Type check npm run typecheck ``` ## E2E Testing The `@grafana/create-plugin` scaffolder includes E2E testing setup with `@grafana/plugin-e2e` and Playwright. ```bash # Install Playwright browsers npx playwright install --with-deps chromium # Start Grafana docker compose up -d # Run E2E tests npx playwright test # Run with UI mode (debugging) npx playwright test --ui ``` See `references/e2e-testing.md` for comprehensive testing patterns, fixtures, and CI/CD setup. ## Best Practices 1. **Start Simple**: Begin with minimal functionality, then iterate 2. **Use Docker**: Consistent environment across team members 3. **Test Early**: Run tests frequently during development 4. **Type Safety**: Leverage TypeScript for all frontend code 5. **SDK Updates**: Keep `@grafana/data`, `@grafana/ui`, `@grafana/runtime` versions aligned ## Common Issues ### Plugin Not Appearing - Check `plugin.json` has correct `id` field - Verify Docker volume mounts correctly - Ensure `npm run dev` completed without errors ### Backend Plugin Errors - Run `mage -v` to rebuild Go code - Check `plugin_start_linux_*` or `gpx_*` binaries exist in `dist/` - Verify `plugin.json` has `"backend": true` ### Development Server Issues - Clear browser cache - Restart Docker: `docker compose down && docker compose up -d` - Check Grafana logs: `docker compose logs grafana` ## Delegation For complex architectural decisions, plugin design patterns, or troubleshooting, delegate to the `grafana-plugin-expert` agent which has access to current SDK documentation via Context7.
Related in Backend & APIs
jfrog
IncludedInteract with the JFrog Platform via the JFrog CLI and REST/GraphQL APIs. Use this skill when the user wants to manage Artifactory repositories, upload or download artifacts, manage builds, configure permissions, manage users and groups, work with access tokens, configure JFrog CLI servers, search artifacts, manage properties, set up replication, manage JFrog Projects, run security audits or scans, look up CVE details, query exposures scan results from JFrog Advanced Security, manage release bundles and lifecycle operations, aggregate or export platform data, or perform any JFrog Platform administration task. Also use when the user mentions jf, jfrog, artifactory, xray, distribution, evidence, apptrust, onemodel, graphql, workers, mission control, curation, advanced security, exposures, or any JFrog product name.
cupynumeric-migration-readiness
IncludedPre-migration readiness assessor for porting NumPy to cuPyNumeric. Use BEFORE substantial porting work begins when the user asks whether code will scale on GPU, whether they should migrate to cuPyNumeric, which NumPy patterns transfer cleanly, what must be refactored before porting, or mentions pre-port assessment, scaling analysis, or refactor planning. Inspect the user's source code, look up NumPy usage, cross-reference the cuPyNumeric API support manifest, and distinguish distributed-scaling-friendly patterns from blockers such as unsupported APIs, scalar synchronization, host round-trips, Python/object-heavy control flow, shape/data-dependent branching, and in-place mutation hazards. Produce a verdict of READY, LIGHT REFACTOR, SIGNIFICANT REFACTOR, or NOT RECOMMENDED, with concrete refactor pointers.
alibabacloud-data-agent-skill
IncludedInvoke Alibaba Cloud Apsara Data Agent for Analytics via CLI to perform natural language-driven data analysis on enterprise databases. Data Agent for Analytics is an intelligent data analysis agent developed by Alibaba Cloud Database team for enterprise users. It automatically completes requirement analysis, data understanding, analysis insights, and report generation based on natural language descriptions. This tool supports: discovering data resources (instances/databases/tables) managed in DMS, initiating query or deep analysis sessions, real-time progress tracking, and retrieving analysis conclusions and generated reports. Use this Skill when users need to query databases, analyze data trends, generate data reports, ask questions in natural language, or mention "Data Agent", "data analysis", "database query", "SQL analysis", "data insights".
token-optimizer
IncludedReduce OpenClaw token usage and API costs through smart model routing, heartbeat optimization, budget tracking, and native 2026.2.15 features (session pruning, bootstrap size limits, cache TTL alignment). Use when token costs are high, API rate limits are being hit, or hosting multiple agents at scale. The 4 executable scripts (context_optimizer, model_router, heartbeat_optimizer, token_tracker) are local-only — no network requests, no subprocess calls, no system modifications. Reference files (PROVIDERS.md, config-patches.json) document optional multi-provider strategies that require external API keys and network access if you choose to use them. See SECURITY.md for full breakdown.
resend-cli
IncludedUse this skill when the task is specifically about operating Resend from an AI agent, terminal session, or CI job via the official resend CLI: installing/authenticating the CLI, sending/listing/updating/cancelling emails, batch sends, domains and DNS, webhooks and local listeners, inbound receiving, contacts, topics, segments, broadcasts, templates, API keys, profiles, or debugging Resend CLI/API failures. Trigger on mentions of Resend CLI, `resend`, `resend doctor`, `resend emails send`, `resend domains`, `resend webhooks listen`, `resend emails receiving`, or agent-friendly terminal automation.
alibabacloud-odps-maxframe-coding
IncludedUse this skill for MaxFrame SDK development and documentation navigation on Alibaba Cloud MaxCompute (ODPS). Helps answer MaxFrame API, concept, official example, and supported pandas API questions; create data processing programs; read/write MaxCompute tables; debug jobs (remote or local); and build custom DPE runtime images. Trigger when users mention MaxFrame, MaxCompute with MaxFrame, ODPS table processing, DPE runtime, MaxFrame docs/examples, DataFrame/Tensor operations, or GPU runtime setup. Works for both English and Chinese queries about Alibaba Cloud data processing with MaxFrame.