Full-stack-skills elasticsearch

Guides Elasticsearch usage including index mapping design, query DSL (match, term, bool, aggregations), bulk indexing, cluster management, and performance tuning. Use when the user needs to implement full-text search, design index mappings, write complex search queries, or manage Elasticsearch clusters.

install

source · Clone the upstream repo

git clone https://github.com/partme-ai/full-stack-skills

Claude Code · Install into ~/.claude/skills/

T=$(mktemp -d) && git clone --depth=1 https://github.com/partme-ai/full-stack-skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/database-skills/elasticsearch" ~/.claude/skills/partme-ai-full-stack-skills-elasticsearch && rm -rf "$T"

manifest: skills/database-skills/elasticsearch/SKILL.md

When to use this skill

Use this skill whenever the user wants to:

Design index mappings with analyzers and field types
Write search queries (match, term, bool, multi_match, nested, aggregations)
Index, update, or bulk-load documents via the REST API
Manage clusters (shards, replicas, snapshots, upgrades)
Integrate Elasticsearch with Kibana or Logstash (ELK stack)

How to use this skill

Workflow

Design the mapping - Define field types, analyzers, and index settings
Index documents - Use PUT/POST or bulk API
Write queries - Use Query DSL with filters for caching
Monitor and tune - Check cluster health, slow logs, and shard balance

Quick-Start Example: Create Index and Search

// Create index with mapping
PUT /products
{
  "mappings": {
    "properties": {
      "name":        { "type": "text", "analyzer": "standard" },
      "description": { "type": "text" },
      "price":       { "type": "float" },
      "category":    { "type": "keyword" },
      "created_at":  { "type": "date" }
    }
  }
}

// Index a document
POST /products/_doc
{
  "name": "Wireless Mouse",
  "description": "Ergonomic wireless mouse with USB-C receiver",
  "price": 29.99,
  "category": "electronics",
  "created_at": "2025-01-15"
}

// Search with bool query and aggregation
GET /products/_search
{
  "query": {
    "bool": {
      "must": [{ "match": { "description": "wireless" } }],
      "filter": [{ "range": { "price": { "lte": 50 } } }]
    }
  },
  "aggs": {
    "by_category": { "terms": { "field": "category" } }
  }
}

Best Practices

Define explicit mappings - Avoid dynamic mapping in production; set
```
dynamic: strict
```
to catch errors
Use filters for exact matches - Filters are cached and faster than queries for keyword/range conditions
Paginate with search_after - Avoid deep
```
from
```
/
```
size
```
pagination; use
```
search_after
```
for large result sets
Plan shards carefully - Target 20-40 GB per shard; avoid too many small shards
Snapshot regularly - Use snapshot/restore for backups; test restore procedures

Keywords

elasticsearch, search, index, mapping, query DSL, aggregation, 搜索引擎, 全文检索, 聚合, ELK, Kibana, bulk API, cluster