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Grafana Oss

Organization
grafana
grafana-oss

Configure Grafana OSS — provisions dashboards from YAML, sets up data sources (Prometheus / Loki / Tempo / Pyroscope), writes dashboard JSON with template variables, builds panel queries, assigns built-in roles (Viewer / Editor / Admin / GrafanaAdmin), mints service-account tokens, edits grafana.ini server config, creates annotations, installs plugins via provisioning, and validates each step with a health-check curl. Use when building dashboards, configuring data sources, setting up provisioning YAML, picking a panel type, writing template variables, managing users and roles, configuring SMTP/OAuth in grafana.ini, creating annotations via API, troubleshooting why a provisioned dashboard isn't showing up, or running Grafana OSS locally — even when the user says "set up a Prometheus data source", "provision dashboards from git", "make a service account", or "configure SSO in OSS" without saying "Grafana OSS".

Overview

Publishergrafana
Repositoryskills
Skill namegrafana-oss
Stars
289
Forks
27
Bundled files
8
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 8 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by grafana on GitHub. Read the source before you install it.

Installation

Install the Grafana Oss AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/grafana/skills/tree/main/skills/grafana-core/grafana-oss
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/grafana/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/skills/grafana-core/grafana-oss .claude/skills/grafana-oss
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Grafana Oss in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Grafana Oss on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Grafana Oss is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Grafana OSS

Docs: https://grafana.com/docs/grafana/latest.md

Common Workflows

Provisioning dashboards from disk

  1. Drop dashboard JSON file(s) under /var/lib/grafana/dashboards/
  2. Add a provider in provisioning/dashboards/default.yaml (see § Dashboard provisioning below)
  3. Restart Grafana so the provider config is loaded
  4. Verify the dashboard landed:
    bash
    curl https://grafana.example.com/api/dashboards/uid/<uid> \
      -H "Authorization: Bearer <token>" | jq '.dashboard.title'
    Returns the title → success. 404 → provisioning didn't pick it up; check Grafana server logs (journalctl -u grafana-server | grep -i provisioning) for parse errors.

Provisioning data sources

  1. Write provisioning/datasources/datasources.yaml (see § Data source provisioning below)
  2. Restart Grafana
  3. Health-check the data source via API:
    bash
    curl https://grafana.example.com/api/datasources/uid/<uid>/health \
      -H "Authorization: Bearer <token>"
    # { "status": "OK", "message": "..." } → working
    # { "status": "ERROR", ... } → URL unreachable or auth misconfigured

Creating a service account + token

  1. Provision via YAML or POST /api/serviceaccounts (full API in references/api.md § Users + service accounts)
  2. Mint a token via POST /api/serviceaccounts/{id}/tokens
  3. Verify the token works:
    bash
    curl https://grafana.example.com/api/org \
      -H "Authorization: Bearer <new-token>"
    # 200 + org JSON → token + role assignment work
    # 401 → token wrong; 403 → role wrong

Dashboard provisioning

yaml
# provisioning/dashboards/default.yaml
apiVersion: 1
providers:
  - name: default
    folder: MyFolder
    type: file
    disableDeletion: false
    updateIntervalSeconds: 30
    options:
      path: /var/lib/grafana/dashboards
      foldersFromFilesStructure: true

For the dashboard JSON shape itself (panels, queries, template variables), see references/dashboard-json.md.

Data source provisioning

yaml
# provisioning/datasources/datasources.yaml
apiVersion: 1
datasources:
  - name: Prometheus
    type: prometheus
    access: proxy
    url: http://prometheus:9090
    isDefault: true
    jsonData:
      timeInterval: 15s
      httpMethod: POST

  - name: Loki
    type: loki
    access: proxy
    url: http://loki:3100

  - name: Tempo
    type: tempo
    access: proxy
    url: http://tempo:3200
    jsonData:
      tracesToLogsV2:
        datasourceUid: loki_uid
        tags: [{ key: "service.name", value: "app" }]
      serviceMap:
        datasourceUid: prometheus_uid
      nodeGraph:
        enabled: true

  - name: Pyroscope
    type: grafana-pyroscope-datasource
    url: http://pyroscope:4040

RBAC (built-in roles)

RolePermissions
ViewerRead dashboards, alerts
EditorCreate/edit dashboards, alerts
AdminManage data sources, users, plugins
GrafanaAdminServer-wide admin (superuser)

Service-account provisioning:

yaml
# provisioning/access-control/service_accounts.yaml
apiVersion: 1
serviceAccounts:
  - name: ci-reader
    orgId: 1
    role: Viewer
    tokens:
      - name: ci-token
        # expires: optional ISO 8601 timestamp; omit for no-expiry tokens

(Custom RBAC roles with fine-grained permissions are Enterprise / Cloud only — see the grafana-cloud/admin skill if you need those.)

Plugin provisioning

yaml
# provisioning/plugins/plugins.yaml
apiVersion: 1
apps:
  - type: grafana-pyroscope-app
    disabled: false
    jsonData:
      backendUrl: http://pyroscope:4040

After restart, verify via GET /api/plugins/<plugin-id>/health.

References

  • references/dashboard-json.md — full dashboard JSON model + template variables + common problems (uid uniqueness, gridPos arithmetic, datasource uid matching)
  • references/dashboards.md — dashboard workflows, settings, variables, annotations, sharing, versions, playlists, and provisioning-as-code
  • references/datasources.md — data source setup and query examples for Prometheus, Loki, Tempo, SQL, CloudWatch, and plugins
  • references/panel-types.md — panel-type table + decision guide for picking the right one
  • references/panels.md — panel editor, visualization options, field config, transformations, query options, inspection, and performance tips
  • references/alerting.md — alerting concepts, contact points, notification policies, templates, silences, and common rule examples
  • references/api.md — full Grafana OSS API reference (dashboards, data sources, users, service accounts, annotations) with verification curls and common failure modes
  • references/config.md — grafana.ini server / database / SMTP / auth / security / feature-toggle config + restart-required issues

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Grafana Oss AI skill do?

Configure Grafana OSS — provisions dashboards from YAML, sets up data sources (Prometheus / Loki / Tempo / Pyroscope), writes dashboard JSON with template variables, builds panel queries, assigns built-in roles (Viewer / Editor / Admin / GrafanaAdmin), mints service-account tokens, edits grafana.ini server config, creates annotations, installs plugins via provisioning, and validates each step with a health-check curl. Use when building dashboards, configuring data sources, setting up provisioning YAML, picking a panel type, writing template variables, managing users and roles, configuring S...

Why use Grafana Oss on TypingMind?

Because you install it once and use it with any model. Grafana Oss is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Grafana Oss in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/grafana/skills/tree/main/skills/grafana-core/grafana-oss. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Grafana Oss?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Grafana Oss?

As many as you like. As long as a model supports skills, you can use Grafana Oss with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Grafana Oss AI skill free?

Yes. It is published on GitHub by grafana under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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