elasticsearch — Elasticsearch setup elasticsearch, ecomsite, community, Elasticsearch setup, ide skills, Elasticsearch Client, audit logging, full-text search, analytics queries, PostgreSQL TSVECTOR

v1.0.0

About this Skill

Perfect for Data Analysis Agents needing advanced full-text search and analytics query capabilities with Elasticsearch Elasticsearch is a search and analytics engine that enables efficient data retrieval and analysis for various use cases, including audit logging and full-text search.

Features

Configures Elasticsearch for audit logging and analytics queries
Uses Elasticsearch Client for API key access and admin actions
Extends product search beyond PostgreSQL's TSVECTOR
Supports Elasticsearch Client setup via @elastic/elasticsearch
Enables full-text search and analytics queries

# Core Topics

kaxuna1 kaxuna1
[0]
[0]
Updated: 1/25/2026

Killer-Skills Review

Decision support comes first. Repository text comes second.

Reference-Only Page Review Score: 8/11

This page remains useful for operators, but Killer-Skills treats it as reference material instead of a primary organic landing page.

Original recommendation layer Concrete use-case guidance Explicit limitations and caution Locale and body language aligned
Review Score
8/11
Quality Score
36
Canonical Locale
en
Detected Body Locale
en

Perfect for Data Analysis Agents needing advanced full-text search and analytics query capabilities with Elasticsearch Elasticsearch is a search and analytics engine that enables efficient data retrieval and analysis for various use cases, including audit logging and full-text search.

Core Value

Empowers agents to perform audit logging, full-text search, and analytics queries using Elasticsearch, extending beyond PostgreSQL's TSVECTOR capabilities with the @elastic/elasticsearch client library

Ideal Agent Persona

Perfect for Data Analysis Agents needing advanced full-text search and analytics query capabilities with Elasticsearch

Capabilities Granted for elasticsearch

Configuring Elasticsearch for audit trails and API key access
Implementing full-text search for product queries
Generating analytics reports with Elasticsearch queries

! Prerequisites & Limits

  • Requires Elasticsearch node setup
  • Dependent on environment variable ELASTICSEARCH_URL

Why this page is reference-only

  • - The underlying skill quality score is below the review floor.

Source Boundary

The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.

After The Review

Decide The Next Action Before You Keep Reading Repository Material

Killer-Skills should not stop at opening repository instructions. It should help you decide whether to install this skill, when to cross-check against trusted collections, and when to move into workflow rollout.

Labs Demo

Browser Sandbox Environment

⚡️ Ready to unleash?

Experience this Agent in a zero-setup browser environment powered by WebContainers. No installation required.

Boot Container Sandbox

FAQ & Installation Steps

These questions and steps mirror the structured data on this page for better search understanding.

? Frequently Asked Questions

What is elasticsearch?

Perfect for Data Analysis Agents needing advanced full-text search and analytics query capabilities with Elasticsearch Elasticsearch is a search and analytics engine that enables efficient data retrieval and analysis for various use cases, including audit logging and full-text search.

How do I install elasticsearch?

Run the command: npx killer-skills add kaxuna1/ecomsite/elasticsearch. It works with Cursor, Windsurf, VS Code, Claude Code, and 19+ other IDEs.

What are the use cases for elasticsearch?

Key use cases include: Configuring Elasticsearch for audit trails and API key access, Implementing full-text search for product queries, Generating analytics reports with Elasticsearch queries.

Which IDEs are compatible with elasticsearch?

This skill is compatible with Cursor, Windsurf, VS Code, Trae, Claude Code, OpenClaw, Aider, Codex, OpenCode, Goose, Cline, Roo Code, Kiro, Augment Code, Continue, GitHub Copilot, Sourcegraph Cody, and Amazon Q Developer. Use the Killer-Skills CLI for universal one-command installation.

Are there any limitations for elasticsearch?

Requires Elasticsearch node setup. Dependent on environment variable ELASTICSEARCH_URL.

How To Install

  1. 1. Open your terminal

    Open the terminal or command line in your project directory.

  2. 2. Run the install command

    Run: npx killer-skills add kaxuna1/ecomsite/elasticsearch. The CLI will automatically detect your IDE or AI agent and configure the skill.

  3. 3. Start using the skill

    The skill is now active. Your AI agent can use elasticsearch immediately in the current project.

! Reference-Only Mode

This page remains useful for installation and reference, but Killer-Skills no longer treats it as a primary indexable landing page. Read the review above before relying on the upstream repository instructions.

Upstream Repository Material

The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.

Upstream Source

elasticsearch

Install elasticsearch, an AI agent skill for AI agent workflows and automation. Review the use cases, limitations, and setup path before rollout.

SKILL.md
Readonly
Upstream Repository Material
The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.
Supporting Evidence

Elasticsearch Skill

Configures Elasticsearch for audit logging, full-text search, and analytics queries. This project uses Elasticsearch for audit trails (API key access, admin actions) and could extend to product search beyond PostgreSQL's TSVECTOR.

Quick Start

Elasticsearch Client Setup

typescript
1// src/services/elasticsearchService.ts 2import { Client } from '@elastic/elasticsearch'; 3 4const client = new Client({ 5 node: process.env.ELASTICSEARCH_URL || 'http://localhost:9200', 6 auth: { 7 apiKey: process.env.ELASTICSEARCH_API_KEY 8 } 9}); 10 11export async function indexAuditEvent(event: AuditEvent): Promise<void> { 12 await client.index({ 13 index: `audit-logs-${new Date().toISOString().slice(0, 7)}`, // Monthly indices 14 document: { 15 ...event, 16 '@timestamp': new Date().toISOString() 17 } 18 }); 19}

Searching Audit Logs

typescript
1export async function searchAuditLogs(params: { 2 keyName?: string; 3 action?: string; 4 adminUserId?: number; 5 from?: string; 6 to?: string; 7 limit?: number; 8}): Promise<AuditEvent[]> { 9 const must: any[] = []; 10 11 if (params.keyName) must.push({ term: { 'key_name.keyword': params.keyName } }); 12 if (params.action) must.push({ term: { action: params.action } }); 13 if (params.adminUserId) must.push({ term: { admin_user_id: params.adminUserId } }); 14 15 if (params.from || params.to) { 16 must.push({ 17 range: { 18 '@timestamp': { 19 ...(params.from && { gte: params.from }), 20 ...(params.to && { lte: params.to }) 21 } 22 } 23 }); 24 } 25 26 const response = await client.search({ 27 index: 'audit-logs-*', 28 query: { bool: { must } }, 29 size: params.limit || 100, 30 sort: [{ '@timestamp': 'desc' }] 31 }); 32 33 return response.hits.hits.map(hit => hit._source as AuditEvent); 34}

Key Concepts

ConceptUsageExample
Index per time periodPrevents unbounded index growthaudit-logs-2025-01
Keyword vs text.keyword for exact match, text for full-textkey_name.keyword
Bool queriesCombine must/should/must_not clauses{ bool: { must: [...] } }
Date rangeFilter by timestamprange: { '@timestamp': { gte, lte } }
AggregationsAnalytics and metricsaggs: { by_action: { terms: { field: 'action' } } }

Common Patterns

Index Template for Audit Logs

typescript
1await client.indices.putIndexTemplate({ 2 name: 'audit-logs-template', 3 index_patterns: ['audit-logs-*'], 4 template: { 5 settings: { 6 number_of_shards: 1, 7 number_of_replicas: 0, // Dev; use 1+ in production 8 'index.lifecycle.name': 'audit-logs-policy' 9 }, 10 mappings: { 11 properties: { 12 '@timestamp': { type: 'date' }, 13 key_name: { type: 'keyword' }, 14 action: { type: 'keyword' }, 15 admin_user_id: { type: 'integer' }, 16 admin_user_email: { type: 'keyword' }, 17 ip_address: { type: 'ip' }, 18 user_agent: { type: 'text' }, 19 metadata: { type: 'object', enabled: false } 20 } 21 } 22 } 23});

Aggregation for Analytics

typescript
1const response = await client.search({ 2 index: 'audit-logs-*', 3 size: 0, 4 aggs: { 5 actions_over_time: { 6 date_histogram: { 7 field: '@timestamp', 8 calendar_interval: 'day' 9 }, 10 aggs: { 11 by_action: { terms: { field: 'action' } } 12 } 13 } 14 } 15});

See Also

  • patterns - Index design, query patterns, bulk operations
  • workflows - Setup, monitoring, troubleshooting
  • See the postgresql skill for hybrid search strategies (Elasticsearch + PostgreSQL)
  • See the docker skill for Elasticsearch container configuration
  • See the node skill for async client patterns

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