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kibana-dashboards — Claude Code skill: what it does, how to install

Creates and manages Kibana dashboards and Lens visualizations declaratively via diffable JSON. Useful for version-controlling panels and automating deployments.

Install into Claude Code · Skills CLI (Vercel) All methods and platforms ↓
npx skills add elastic/agent-skills --skill kibana-dashboards -a claude-code
Open on GitHub

What kibana-dashboards does

The skill generates minimal, diffable JSON bodies for Kibana 9.4+ Dashboards and Visualizations APIs. Instead of calling HTTP endpoints directly, it runs operations through the elastic CLI. It first verifies Kibana connectivity via GET kbn:/api/status to ensure the cluster meets the version threshold.

Kibana 9.4 or later and the elastic CLI version 0.3 or higher with stack kb support are mandatory prerequisites. If the CLI is missing, the skill halts immediately because guessing credentials or using HTTP workarounds is explicitly prohibited.

When defining chart layers, the skill selects the appropriate source between a saved data view, an ad-hoc index pattern, or an ES|QL query. For ES|QL panels, it binds column names directly to metric definitions and prefers inline panel configs for maximum dashboard portability.

What it helps with

  • create declarative Kibana dashboards with custom panel grids
  • build standalone Lens visualizations backed by ES|QL queries
  • version-control dashboard definitions in clean JSON formats
  • persist dashboard time filters and inline panels via API

Example prompts for the agent

  • Create a 'Sales Overview' dashboard with a default time range of now-7d to now
  • Build a Lens metric visualization using ES|QL query FROM logs* | STATS count = COUNT()
  • Update the dashboard eval-sales-overview with an inline metric panel for total requests

How to install kibana-dashboards

1Skills CLI (Vercel)

npx skills add elastic/agent-skills --skill kibana-dashboards -a claude-code

2Manually: put the files in place

~/.claude/skills/kibana-dashboards/SKILL.md

Copy the whole skill folder; for one project use .claude/skills/kibana-dashboards/

Step by step, with commands for each platform: How to install skills in Claude Code: five ways

Questions about kibana-dashboards

How to install kibana-dashboards in Claude Code?

Run npx skills add elastic/agent-skills --skill kibana-dashboards -a claude-code in your terminal.

What does the kibana-dashboards skill do?

It builds declarative JSON payloads and executes elastic CLI commands to create, update, and manage Kibana dashboards and Lens visualizations.

What prerequisites are needed for this skill?

You need Kibana 9.4 or later and the elastic CLI version 0.3 or higher with stack kb support.

Source text

SKILL.md · Apache-2.0
---
name: kibana-dashboards
description: >
  Create and manage Kibana Dashboards and Lens visualizations. Use when you need to
  define dashboards and visualizations declaratively, version control them, or automate
  their deployment.
metadata:
  author: elastic
  version: 0.3.0
  universal: true
compatibility: Kibana 9.4 or later (Dashboards and Visualizations APIs) with matching
  Elasticsearch, self-managed, Elastic Cloud Hosted, or Elastic Cloud Serverless.
  Requires the `elastic` CLI ≥ 0.3 with `stack kb` support (dedicated `dashboards`
  and `visualizations` commands).
---

# Kibana Dashboards and Lens Visualizations

Create, update, and delete Kibana dashboards and standalone Lens visualizations using the Kibana 9.4+ Dashboards and
Visualizations APIs. Produce minimal, diffable JSON bodies; prefer inline panel definitions over library references; and
choose the correct dataset type (data view vs ES|QL) before writing metrics or chart layers.

<!-- begin-partial: preamble -->

## Environment Configuration

This skill executes Elasticsearch operations through the `elastic` CLI. If the
[`elastic` CLI](https://github.com/elastic/cli#configuration) is not installed, tell the user what it is needed for. Do
not guess credentials, call the HTTP API directly, or attempt other workarounds.

This skill references operations in HTTP-shorthand form (e.g., `GET /`, `GET /_cat/indices`, `GET /{index}/_mapping`,
`GET /{index}/_settings/index.mode`, `POST /_query`). The [Operations](#operations) table at the end of this document
maps each shorthand to the equivalent `elastic` CLI command — always use the CLI rather than calling the HTTP API
directly.

<!-- end-partial: preamble -->

## Prerequisites

**Version requirement:** Kibana 9.4+ (Dashboards and Visualizations APIs).

**ES|QL placement:**

- Standalone library charts: `PUT kbn:/api/visualizations/{id}` with `data_source.type: "esql"`.
- ES|QL panels embedded in a dashboard: inline `vis` panel `config` with `data_source.type: "esql"` via
  `PUT kbn:/api/dashboards/{id}`.
- Do not use `data_source.type: "data_view_reference"` or index-pattern aggregations when the user explicitly requests
  ES|QL — the persisted Lens state must use a text-based ES|QL datasource (`textBased` / `esql`), not a data-view count
  operation.

## Process

1. **Verify Kibana connectivity.** Call `GET kbn:/api/status`. If the call fails, stop and surface the error — do not
   guess endpoints or credentials. Read `version.number` to confirm the cluster meets the 9.4+ requirement.

2. **Classify the task.** Decide whether the user needs a **dashboard** (collection of panels, optional time range), a
   **standalone Lens visualization** (library item referenced by id or used alone), or **both**. Determine whether a
   deterministic saved-object id was supplied — when given, use upsert (`PUT`) with that id rather than `POST` (which
   auto-generates ids).

3. **Choose the dataset type before building metrics or layers.**

   | User intent                                      | Dataset                                                                    | Metric / axis pattern                                                                                                                    |
   | ------------------------------------------------ | -------------------------------------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------- |
   | Simple count or aggregation on a saved data view | `data_source.type: "data_view_reference"` with `ref_id`                    | `metrics: [{ type: "primary", operation: "count" }]` (or other aggregation operations)                                                   |
   | Ad-hoc index pattern                             | `data_source.type: "data_view_spec"` with `index_pattern` and `time_field` | Same aggregation `operation` fields                                                                                                      |
   | ES\|QL query (explicit or complex logic)         | `data_source.type: "esql"` with `query`                                    | `metrics: [{ type: "primary", column: "<alias>" }]` or layer axes `{ column: "<alias>" }` — **never** `operation: "count"` on the metric |

   Write the aggregation in the ES|QL query (`STATS count = COUNT()`), then reference the resulting column by name.

4. **Build a dashboard body when creating or updating dashboards.** The request body is flat — `title`, `panels`, and
   optional `time_range` at the root. Do not wrap in `{ data: ... }` on write. Required fields:
   - `title` — exact string the user requested.
   - `panels` — array; use `[]` when the user asks for an empty dashboard (do not omit the key or invent panels).
   - `time_range` — when the user specifies a default time filter, set `{ "from": "<expr>", "to": "<expr>" }` (for
     example `{ "from": "now-7d", "to": "now" }`). Supplying `time_range` persists the dashboard time filter on open
     (equivalent to enabling time restore in the UI).

   **Upsert with a deterministic id:**

   ```json
   {
     "title": "Sales Overview",
     "panels": [],
     "time_range": { "from": "now-7d", "to": "now" }
   }
   ```

   Call `PUT kbn:/api/dashboards/eval-sales-overview` with the body above when the user supplies that id.

   **Inline ES|QL metric panel example** (inside `panels`):

   ```json
   {
     "type": "vis",
     "id": "total-requests",
     "grid": { "x": 0, "y": 0, "w": 12, "h": 6 },
     "config": {
       "title": "Total Requests",
       "type": "metric",
       "data_source": {
         "type": "esql",
         "query": "FROM logs* | STATS count = COUNT()"
       },
       "metrics": [{ "type": "primary", "column": "count" }]
     }
   }
   ```

   Prefer inline `config` properties over `config.ref_id` for portable dashboards. Read
   [Dashboard API Reference](references/dashboard-api-reference.md) for panel types, grid layout, and copy workflows.

5. **Build a standalone Lens visualization when the user asks for a library chart.** Use the Visualizations API. Upsert
   with `PUT kbn:/api/visualizations/{id}` when an id is supplied; otherwise `POST kbn:/api/visualizations` and report
   the generated id from the response.

   **ES|QL metric (total count from logs):**

   ```json
   {
     "type": "metric",
     "title": "Total Requests",
     "data_source": {
       "type": "esql",
       "query": "FROM logs* | STATS count = COUNT()"
     },
     "metrics": [{ "type": "primary", "column": "count" }]
   }
   ```

   Call `PUT kbn:/api/visualizations/eval-total-requests` when that id is required. The API persists a Lens saved object
   whose datasource state uses ES|QL (`textBased` / `esql`), not an index-pattern aggregation.

   Read [Lens API Reference](references/lens-api-reference.md) and
   [Chart Types Reference](references/chart-types-reference.md) for xy, gauge, heatmap, and other chart schemas.

6. **Execute and confirm.** Perform the write with `PUT kbn:/api/dashboards/{id}` or `PUT kbn:/api/visualizations/{id}`
   (or `POST` when no id is supplied). Confirm with `GET kbn:/api/dashboards/{id}` or
   `GET kbn:/api/visualizations/{id}`. Report the id and title back to the user — do not claim success without a
   successful read-back.

7. **List, export, or delete when requested.** Call `GET kbn:/api/dashboards` or `GET kbn:/api/visualizations` to
   discover existing objects. Call `DELETE kbn:/api/dashboards/{id}` or `DELETE kbn:/api/visualizations/{id}` to remove
   objects. For bulk export or import of saved objects, call `POST kbn:/api/saved_objects/_export` or
   `POST kbn:/api/saved_objects/_import`.

## Dashboard grid

Dashboards use a **48-column** grid. On 16:9 screens, roughly **20–24 rows** fit above the fold — target **8–12 panels**
in that band.

| Width   | Columns | Height (rows) | Use case                 |
| ------- | ------- | ------------- | ------------------------ |
| Full    | 48      | 14–16         | Wide time series, tables |
| Half    | 24      | 10–12         | Primary charts           |
| Quarter | 12      | 5–6           | KPI metrics              |
| Sixth   | 8       | 4–5           | Dense metric rows        |

**Grid packing:** When stacking rows, set the next panel's `y` to the previous panel's `y + h`. Panels sharing a row
should use the same `h`. Do not add markdown panels as dashboard titles — use descriptive chart titles instead.

## ES|QL patterns

**Time series bucket** (dashboard time picker injects `?_tstart` / `?_tend`):

```esql
FROM logs*
| WHERE @timestamp <= ?_tend AND @timestamp > ?_tstart
| STATS count = COUNT() BY BUCKET(@timestamp, 75, ?_tstart, ?_tend)
```

Set `"scale": "temporal"` on the x-axis for time-series xy charts. See
[Chart Types Reference](references/chart-types-reference.md) for axis and layer details.

**Static reference values** — use `EVAL` in the query, then reference the column:

```esql
FROM logs* | STATS count = COUNT() | EVAL goal = 15000
```

## Examples

Example JSON definitions live under [assets/](assets/): `demo-dashboard.json`, `dashboard-with-visualizations.json`,
`metric-esql.json`, `bar-chart-esql.json`, `line-chart-timeseries.json`.

## Guidelines

1. **Match the user's id and title exactly** when supplied — do not substitute auto-generated ids.
2. **Honor empty panels** — when the user asks for `panels: []`, send an empty array; do not add placeholder panels.
3. **ES|QL when requested** — use `data_source.type: "esql"` and column references; never satisfy an ES|QL request with
   `operation: "count"` on a data view.
4. **Minimal payloads** — omit derivable defaults; let the API inject styling and metadata.
5. **Confirm writes** — always read back with `GET` after create or update.
6. **Read references before complex charts** — metric and xy schemas differ between data view and ES|QL; consult
   [Chart Types Reference](references/chart-types-reference.md) before generating partition or table charts.

## Common issues

| Error                               | Likely cause                | Fix                                                                          |
| ----------------------------------- | --------------------------- | ---------------------------------------------------------------------------- |
| 404 on GET after PUT                | Wrong id or space           | Confirm id and retry `GET kbn:/api/dashboards/{id}`                          |
| 400 validation                      | ES\|QL column mismatch      | Align `metrics[].column` / layer `column` with `STATS` aliases in the query  |
| ES\|QL panel saved as data view     | Wrong dataset type          | Use `data_source.type: "esql"`, not `data_view_reference`                    |
| Empty dashboard missing time filter | Omitted `time_range`        | Include `{ "from": "now-7d", "to": "now" }` when a default range is required |
| XY chart failure                    | Missing layer `data_source` | Put `data_source` inside each layer, not only at the root                    |

## Operations

As of CLI v0.3.0 the Dashboards and Visualizations APIs have dedicated `elastic kb dashboards` and
`elastic kb visualizations` commands for listing, reading, updating, and deleting objects by id. The `create-*-redirect`
commands do not accept a request body yet, so to write a new object supply an id and use the `update-*-redirect` (PUT)
command, which carries the JSON body via `--input-file`. To author several objects at once, build a saved-object NDJSON
and import it with `post-saved-objects-import` (read it back with `post-saved-objects-export`).

| HTTP API (shorthand)                   | `elastic` CLI command                                                                                                                                             |
| -------------------------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `GET kbn:/api/status`                  | `elastic kb system get-status`                                                                                                                                    |
| `POST kbn:/api/saved_objects/_import`  | `elastic kb saved-objects post-saved-objects-import --file '<path.ndjson>' --overwrite`                                                                           |
| `POST kbn:/api/saved_objects/_export`  | `elastic kb saved-objects post-saved-objects-export --objects '[{"type":"<type>","id":"<id>"}]'`                                                                  |
| `GET kbn:/api/dashboards`              | `elastic kb dashboards get-dashboards-redirect`                                                                                                                   |
| `GET kbn:/api/dashboards/{id}`         | `elastic kb dashboards get-dashboard-redirect --id '<id>'`                                                                                                        |
| `PUT kbn:/api/dashboards/{id}`         | `elastic kb dashboards update-dashboard-redirect --id '<id>' --input-file '<path.json>'`                                                                          |
| `DELETE kbn:/api/dashboards/{id}`      | `elastic kb dashboards delete-dashboard-redirect --id '<id>'`                                                                                                     |
| `POST kbn:/api/dashboards` (no id)     | `create-dashboard-redirect` takes no body yet — supply an id and use `update-dashboard-redirect`, or author via `post-saved-objects-import` (type `dashboard`)    |
| `GET kbn:/api/visualizations`          | `elastic kb visualizations get-visualizations-redirect`                                                                                                           |
| `GET kbn:/api/visualizations/{id}`     | `elastic kb visualizations get-visualization-redirect --id '<id>'`                                                                                                |
| `PUT kbn:/api/visualizations/{id}`     | `elastic kb visualizations update-visualization-redirect --id '<id>' --input-file '<path.json>'`                                                                  |
| `DELETE kbn:/api/visualizations/{id}`  | `elastic kb visualizations delete-visualization-redirect --id '<id>'`                                                                                             |
| `POST kbn:/api/visualizations` (no id) | `create-visualization-redirect` takes no body yet — supply an id and use `update-visualization-redirect`, or author via `post-saved-objects-import` (type `lens`) |

© elastic · Apache-2.0 · elastic/agent-skills

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