provisioning
Grafana provisioning across all delivery methods: file provisioning YAML (datasources, dashboards, alerting), Kubernetes-style HTTP API, gcx CLI (replacing grafanactl), Terraform provider, Foundation SDK, Git Sync. Invoke whenever task involves any interaction with Grafana provisioning or observability-as-code — configuring datasources, managing dashboards or alerting resources as code, automating Grafana setup, choosing between IaC tools, migrating between approaches, or using the Grafana HTTP API.
What this skill does
# Grafana Provisioning
Make Grafana resources reproducible. Pick the right tool for each resource type and team workflow, then keep the runtime
configuration in sync with version control. Wrong tool choices don't cause errors immediately — they show up months
later as drift, brittle CI, or notification policies overwritten by a partial config push.
## References
- **File provisioning** — [`${CLAUDE_SKILL_DIR}/references/file-provisioning.md`] Directory layout, env var
interpolation, full datasource / dashboard / plugin / alerting YAML schemas, reload behavior, UI edit semantics
- **HTTP API** — [`${CLAUDE_SKILL_DIR}/references/http-api.md`] New `/apis/` Kubernetes-style surface vs. legacy
`/api/`, dashboard / folder / datasource CRUD, alerting provisioning endpoints, annotation API, pagination,
authentication
- **Terraform** — [`${CLAUDE_SKILL_DIR}/references/terraform.md`] Provider setup, full resource catalog, dashboards /
datasources / alerting examples, provenance and UI-edit toggle, GitHub Actions workflow, import workflow
- **gcx** — [`${CLAUDE_SKILL_DIR}/references/gcx.md`] Grafana CLI install, contexts, resource pull/push/serve, telemetry
queries, agentic features and skills, CI integration, migration from `grafanactl`
- **Observability as code** — [`${CLAUDE_SKILL_DIR}/references/observability-as-code.md`] Tool comparison, decision
matrix, how to compose tools, migration paths (Grizzly → gcx, legacy API → new API, file → Terraform)
## Tool selection
Pick the primary tool based on resource type and team workflow. The references above contain a full decision matrix —
quick selection rules:
- **Self-managed Grafana, simple setup** → file provisioning
- **Dev → staging → prod resource migration** → `gcx` (Grafana ≥ v12)
- **Dashboards generated programmatically** → Foundation SDK + `gcx`
- **Agentic coding tools driving Grafana from the terminal** → `gcx`
- **Git as source of truth, edits via Grafana UI** → Git Sync
- **Already running Terraform** → Grafana Terraform provider
- **Kubernetes-native GitOps shop** → Grafana Operator or Crossplane
- **One-off scripts and custom integrations** → HTTP API directly
- **Grafana Cloud only with existing Ansible** → Grafana Ansible Collection
- **Existing grafanactl deployment, Grafana < v12** → continue with `grafanactl` until upgrading; the binary keeps
working through the 2026-06-01 archive date
Compose tools where natural: Foundation SDK generates, `gcx` pushes; Terraform owns alerting + data sources, file
provisioning ships fixed dashboards.
### Tool status notes
- **`gcx`** is the current Grafana CLI. Requires Grafana ≥ v12. Public preview as of 2026. Inherits `grafanactl`'s
design and adds telemetry queries, agentic-driver auto-detection, and broader Grafana Cloud product coverage.
- **`grafanactl`** is superseded by `gcx`. GitHub repo archives 2026-06-01. Migration is a binary rename plus one
command rename (`grafanactl resources serve` → `gcx dev serve`). Don't adopt for new work unless on Grafana < v12.
- **Grizzly** is deprecated; mentioned only because some existing deployments still use it. Successor was `grafanactl`,
now `gcx`. Don't adopt for new work.
- **Grafonnet** is deprecated for new work; use the Foundation SDK.
- **API keys** are deprecated; use service account tokens.
- **`/api/dashboards/db`** is legacy; use `/apis/dashboard.grafana.app/v1/...` where the new API supports the case
(especially dashboards v2 / dynamic dashboards).
## File provisioning
YAML files in `provisioning/` directories read by Grafana at startup. Not available in Grafana Cloud.
### Directory layout
```
provisioning/
├── datasources/ # *.yaml — data source configs
├── dashboards/ # *.yaml — dashboard provider configs (NOT dashboards themselves)
├── plugins/ # *.yaml — plugin app configs
└── alerting/ # *.yaml or *.json — alert resources
```
Dashboard JSON files live elsewhere (e.g., `/var/lib/grafana/dashboards/`) and the dashboard provider YAML points to
them.
### Environment variables
All provisioning YAML supports `$VAR` and `${VAR}` for values (not keys, not dashboard JSON). Order: `${VAR}` first,
then `$VAR`. Escape literal `$` as `$$`. Prefer `$VAR` when the substituted value contains `$`.
### Datasource shape
```yaml
apiVersion: 1
prune: true # auto-delete provisioned datasources removed from this file
datasources:
- name: Prometheus # required, unique per org
type: prometheus # required
access: proxy # proxy = Server, direct = Browser
uid: prom_main
url: http://prometheus:9090
isDefault: true
jsonData:
prometheusType: Mimir
manageAlerts: true
secureJsonData:
httpHeaderValue1: ${TENANT_TOKEN}
editable: false
```
Secrets go in `secureJsonData` (encrypted at rest). For multi-instance Grafana with shared DB, set `version` and bump it
on each change.
### Dashboard shape
Provider YAML configures discovery; dashboard JSON files contain the dashboards:
```yaml
apiVersion: 1
providers:
- name: 'team-platform'
folder: '' # '' = root
type: file
disableDeletion: false
updateIntervalSeconds: 30 # poll if > 10, watch filesystem if ≤ 10
allowUiUpdates: false # let UI edits persist until next reprovision
options:
path: /var/lib/grafana/dashboards
foldersFromFilesStructure: true
```
`foldersFromFilesStructure: true` maps subdirectory names to Grafana folders. Nested folders not supported.
Dashboard JSON must use the Kubernetes-style format for dashboards v2 / dynamic dashboards
(`apiVersion: dashboard.grafana.app/v1`).
### Alerting shape
`provisioning/alerting/*.yaml` can contain any combination of:
- `groups` — alert rule groups (with `name`, `folder`, `interval`, `rules[]`)
- `contactPoints` — contact points with `receivers[]`
- `policies` — the notification policy tree (entire tree is one resource — replaces existing)
- `templates` — notification template groups
- `muteTimes` — mute time intervals
Plus `deleteRules`, `deleteContactPoints`, `deleteTemplates`, `deleteMuteTimes`, `resetPolicies`.
Variable interpolation does **not** apply in: alert rule annotations, `relativeTimeRange`, query `data.model`, mute
timing names/intervals, template names/bodies. Escape `$variable` as `$$variable` where not wanted.
### Reload behavior
Provisioning runs at startup. Reload at runtime via the Admin API (`POST /api/admin/provisioning/{type}/reload`) —
requires admin permissions. Dashboard files have their own poll/watch loop independent of provisioning reload.
## HTTP API
Two surfaces:
- **New `/apis/<group>.grafana.app/<version>/...`** — Kubernetes-style resources. Covers dashboards, folders, library
panels, playlists; expanding over time. Built on these are `gcx`, Foundation SDK, Git Sync.
- **Legacy `/api/...`** — data sources, annotations, admin, alerting provisioning. Won't get new functionality but
remains functional.
### Authentication
Service account tokens (recommended) via `Authorization: Bearer <token>`. API keys still work but are deprecated.
### Dashboard CRUD pattern
```
POST /apis/dashboard.grafana.app/v1/namespaces/<ns>/dashboards
PUT /apis/dashboard.grafana.app/v1/namespaces/<ns>/dashboards/<uid>
GET /apis/dashboard.grafana.app/v1/namespaces/<ns>/dashboards/<uid>
GET /apis/dashboard.grafana.app/v1/namespaces/<ns>/dashboards?limit=100
DELETE /apis/dashboard.grafana.app/v1/namespaces/<ns>/dashboards/<uid>
```
Namespace is `default` for single-org Grafana, `stack-<id>` for Grafana Cloud. Use pagination's `metadata.continue`
token for list endpoints.
### Alerting provisioning API
`/api/v1/provisioning/{alert-rules,contact-points,policies,templates,mute-timings}` — JSON CRUD.
Standard endpoints return JSON **not compatible with file provisioning**. For round-tripping via configuration files,
use `/export` endpoints which retuRelated 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.