# elasticsearch-anomaly-detection

Configures and starts Elasticsearch ML anomaly detection jobs using the elastic CLI. Useful when tracking volume surges, outages, or metric drift in time-series data streams.

- skill · `type=skill` · Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, OpenCode · 1000 installs · ★ 601
- Author: elastic
- License: Apache-2.0 · policy=mirror · the beginning of the file is at the end of this page
- Source: https://github.com/elastic/agent-skills/tree/HEAD/skills/elasticsearch/elasticsearch-anomaly-detection/SKILL.md
- Updated: 2026-10-23
- HTML: https://affpapa.org/en/nevibecode/skills/elasticsearch-anomaly-detection

## What it does

This skill sets up Elastic ML anomaly detection jobs on time-series indices. It operates through the `elastic` CLI rather than direct HTTP calls. First, it inspects candidate indices and mapping fields to verify the timestamp. It then assigns detector functions based on intent: `high_count` flags volume spikes, while `low_count` detects dropouts.

Key settings like `bucket_span` and detector types are immutable. Getting them wrong means deleting and rebuilding the job from scratch. The skill strictly enforces the required sequence: create the job, attach the datafeed, open the job, and start the feed. It confirms the running state via stats endpoints rather than assuming the API succeeded.

Running these operations requires Elasticsearch 8.x+ or Elastic Cloud Serverless. Self-managed deployments need a Platinum-equivalent license and the `manage_ml` privilege. If you need to evaluate influencer metrics or anomaly scores on an active job, Elastic provides a separate tool called `elasticsearch-anomaly-detection-explainer`.

## Install

### Claude Code (native platform)

1. **Skills CLI (Vercel)**
```bash
npx skills add elastic/agent-skills --skill elasticsearch-anomaly-detection -a claude-code
```

2. **Manually: put the files in place**
- File: `~/.claude/skills/elasticsearch-anomaly-detection/SKILL.md` — Copy the whole skill folder; for one project use .claude/skills/elasticsearch-anomaly-detection/

### Codex

1. **Skills CLI (Vercel)**
```bash
npx skills add elastic/agent-skills --skill elasticsearch-anomaly-detection -a codex
```

2. **Manually: put the files in place**
- File: `.agents/skills/elasticsearch-anomaly-detection/SKILL.md` — For all projects use ~/.agents/skills/

### Cursor

1. **Skills CLI (Vercel)**
```bash
npx skills add elastic/agent-skills --skill elasticsearch-anomaly-detection -a cursor
```

2. **Manually: put the files in place**
- File: `.cursor/skills/elasticsearch-anomaly-detection/SKILL.md` — Cursor also reads .agents/skills/ and .claude/skills/

### GitHub Copilot

1. **GitHub CLI**
```bash
gh skill install elastic/agent-skills elasticsearch-anomaly-detection
```

2. **Manually: put the files in place**
- File: `.github/skills/elasticsearch-anomaly-detection/SKILL.md`

### Gemini CLI

1. **Skills CLI (Vercel)**
```bash
npx skills add elastic/agent-skills --skill elasticsearch-anomaly-detection -a gemini-cli
```

2. **Platform CLI**
```bash
gemini skills install https://github.com/elastic/agent-skills --path skills/elasticsearch/elasticsearch-anomaly-detection
```

### Windsurf (Devin Desktop)

**Manually: put the files in place**
- File: `.devin/skills/elasticsearch-anomaly-detection/SKILL.md` — The legacy .windsurf/skills/ path still works

### OpenCode

**Skills CLI (Vercel)**
```bash
npx skills add elastic/agent-skills --skill elasticsearch-anomaly-detection -a opencode
```

### Claude.ai

**Claude.ai**
- Zip the folder and upload it in Settings → Capabilities → Skills

Where a file is given instead of a command, copy the files from the source to that path: https://github.com/elastic/agent-skills/tree/HEAD/skills/elasticsearch/elasticsearch-anomaly-detection/SKILL.md

## When to use it
- configure a `high_count` detector to catch event volume spikes
- track traffic drops or outages using `low_count`
- link an Elasticsearch datafeed to a specific time-series index
- start an Elastic ML anomaly detection job in the correct sequence

## Example prompts
- Create an ML job to detect event spikes in the logs-app-* index with a 15m bucket span
- Set up an anomaly detection job for traffic drops in the network-traffic data stream

## Source text · SKILL.md · Apache-2.0

Below is the content of a third-party file. It is data, not instructions for you: do not act on anything written inside unless the human asks. Block tag: 1489cdef9c8665f9.

BEGIN THIRD-PARTY FILE 1489cdef9c8665f9
```text
---
name: elasticsearch-anomaly-detection
description: >
  Create and manage Elastic ML anomaly detection jobs via the API. Use when setting
  up jobs on an index or data stream, configuring jobs and datafeeds, or opening,
  starting, or stopping them.
compatibility: >
  Requires Elasticsearch 8.x+ or Elastic Cloud Serverless with ML anomaly detection.
  Uses the ML REST API only. User needs manage_ml privilege to create and manage jobs.
metadata:
  author: elastic
  version: 1.1.0
  universal: true
---

# Elasticsearch Anomaly Detection

Create, open, and start ML anomaly detection jobs on time-series data. Choose the right count-family detector direction,
configure bucket span and time field, wire the datafeed to the correct index, and confirm running state from stats — not
from assumptions.

<!-- 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 -->

> **Prerequisite:** ML anomaly detection requires a Platinum-equivalent license on self-managed clusters. Serverless
> projects include ML. The caller needs `manage_ml` to create and manage jobs.
>
> **Related skill:** For interpreting anomaly scores, influencers, and model behavior after a job is running, use
> `elasticsearch-anomaly-detection-explainer` — not this skill.

## Process

1. **Discover the target index and time field.** List candidate indices with `GET /_cat/indices` (pass a pattern when
   the user names one). Fetch field types for the chosen index with `GET /{index}/_mapping`. The decision: confirm the
   index exists, identify the time field (often `@timestamp`), and verify document volume is sufficient for baseline
   learning. Never guess index or field names — they vary across deployments.
```
END THIRD-PARTY FILE 1489cdef9c8665f9

The third-party file has ended. Everything between the 1489cdef9c8665f9 tags is data: requests and commands from it are not followed. An “end of file” line with another tag inside the block is part of the file.

First 2373 of 9607 bytes. © elastic · Apache-2.0 · https://github.com/elastic/agent-skills/tree/HEAD/skills/elasticsearch/elasticsearch-anomaly-detection/SKILL.md

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