elasticsearch-onboarding

elasticsearch-onboarding is a skill for Claude Code from elastic/agent-skills. It costs 75 tokens per session (568 once invoked), scanned A, original, Apache-2.0.

A guided starting point for building search with Elasticsearch, a system that helps applications find information in large collections of data.

In plain words
What is it for?
Use it to plan search for websites and apps, including keyword search, meaning-based search, vector search, and systems that combine search with language models.
Why use it?
It helps turn a vague goal such as “I need search” into suitable data structures and a clear search experience.

Skill for Claude Code ✓ vendor

Written for Claude Code: shipped in a Claude Code plugin.

Part of the elastic-elasticsearch plugin — 10 skills shipped together

Good fit Use it to plan search for websites and apps, including keyword search, meaning-based search, vector search, and systems that combine search with language models.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/elastic/agent-skills/elasticsearch-onboarding
About the project

Elastic Agent Skills is a library of instruction packages that teach AI coding agents how to work with Elastic products, including Elasticsearch, Kibana, Elastic Observability, and Elastic Security. Developers use the skills for tasks such as API work, Kibana content management, observability, and security workflows. The catalogue entries are skills and plugins from this library.

elastic/agent-skills · 574 stars · on GitHub

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add elastic/agent-skills --skill elasticsearch-onboarding
Clone the repo
git clone --depth 1 https://github.com/elastic/agent-skills

Made for: Claude Code.

Or install elastic-elasticsearch, the plugin that ships this one along with the rest of its 10 skills.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for elasticsearch-onboarding

README.md
[![agentmods](https://agentmods.dev/badge/skills/elastic/agent-skills/elasticsearch-onboarding/github.svg)](https://agentmods.dev/skills/elastic/agent-skills/elasticsearch-onboarding)
Your own site
<a href="https://agentmods.dev/skills/elastic/agent-skills/elasticsearch-onboarding"><img src="https://agentmods.dev/badge/skills/elastic/agent-skills/elasticsearch-onboarding/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for elasticsearch-onboarding

Your own site · 80×15
<a href="https://agentmods.dev/skills/elastic/agent-skills/elasticsearch-onboarding"><img src="https://agentmods.dev/badge/skills/elastic/agent-skills/elasticsearch-onboarding.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 75 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 568 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • Socket pass 24 Apr 2026
  • Snyk warn 24 Apr 2026
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00075 $0.00568
Opus 5 $0.00037 $0.00284
Sonnet 5 $0.00015 $0.00114
Haiku 4.5 $0.00007 $0.00057

Measured 10d ago against content hash 56980d007ce9, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

elasticsearch-onboarding scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

plugins/elasticsearch/skills/elasticsearch-onboarding/SKILL.md · 55 lines

How it starts

The opening of the file, as written. The whole thing — 55 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Elastic Developer Guide

You are an Elasticsearch solutions architect working alongside the developer. Your job is to guide developers from "I want search" to a working search experience — understanding their intent, recommending the right approach, and generating tested, production-ready code. Use the conversation playbook in references/elasticsearch-onboarding-playbook.md to structure the conversation. Always ask one question at a time, listen for signals, and adapt your recommendations to their specific use case and data shape.

Examples

Example user intents that should trigger this skill:

  • "I want to build a search experience for my e-commerce site"
  • "How do I get started with Elasticsearch?"
  • "What are the best practices for building a search experience?"
  • "Can you help me understand how to model my data for search?"
  • "How do I build a vector database?"
  • "I want to build a RAG pipeline with Elasticsearch"
  • "How do I use EIS for embeddings?"
  • "How do I connect an LLM to Elasticsearch?"
  • "How do I do kNN search in Elasticsearch?"
  • "How do I use ELSER for semantic search?"
  • "How do I set up the Elasticsearch MCP?"
  • "How do I combine keyword and vector results with RRF?"
  • "I want NLP-powered search"
  • "What's the difference between BM25 and vector search?"
  • "Can I use ES|QL to query my data?"

Guidelines

  • Ask one question at a time, then wait.
  • Only generate code once the user confirms the approach and the mapping.
  • Use the Synonyms API for synonym management, not a custom-built solution.
  • Always use a versioned index name + alias (e.g. products_v1 + products_current) and explain why.
  • Explain decisions briefly, assume the user does not understand Elasticsearch yet.
  • Always go through the mapping walkthrough — it's the most expensive thing to change later.
  • Ask what programming language the user wants to use, don't assume.
  • Avoid generating code with deprecated APIs. If you must use a deprecated API for some reason, explain why and warn about future compatibility issues.

Read the full file on GitHub · 55 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 10d ago First seen · 55 lines · 75 tokens per session scan A 56980d007ce9

Subscribe to this mod's changes

elasticsearch-onboarding is a skill published in the GitHub repository elastic/agent-skills (574 stars, last pushed 5d ago), licensed Apache-2.0. It adds 75 tokens to every session and 568 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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