
Elasticsearch Index Design
by elasticbaa511126ba2No license592 starsListed Oct 8, 2026Updated Oct 8, 2026Repository updated yesterday
Design and review Elasticsearch index mappings for stated access patterns: correct field types, text+keyword multi-fields, doc_values tuning, mapping-explosion avoidance, and explicit shard settings. Use when creating a new index, reviewing a mapping for storage or query performance, fixing wrong field types, or when the user asks which type to use for search, filter, sort, or aggregation on a field.
Only the file list is public. File contents are available once the skill is installed in a workspace.
| Path | Size | Type |
|---|---|---|
| references/field-type-decisions.md | 5.7 KB | text/markdown |
| references/mapping-explosion.md | 3.9 KB | text/markdown |
| references/multi-field-patterns.md | 3.1 KB | text/markdown |
| SKILL.md | 12.2 KB | text/markdown |
Source and attribution
Source:elastic/agent-skillsinskills/elasticsearch/elasticsearch-index-designat commitbaa5111
License: No license
Content belongs to its original authors. SourceWeft indexes it from a public repository.
More from elastic/agent-skills

Elasticsearch Search Relevance
elastic
Improve Elasticsearch search relevance for content and catalog indices: pin or promote results with query rules (correct rule type, criteria, and rule-query wiring) and tune organic ranking with multi_match, field boosts, and analysis grounded in the index mapping. Use when search results rank poorly, a specific document must appear first for a query, or the user asks to tune full-text matching — not for ES|QL analytics, index ingest, or cluster health.

Elasticsearch Query Optimization
elastic
Diagnose slow Elasticsearch Query DSL searches and propose measured fixes. Use when a search is slow, profile output shows an expensive clause, exact-match filters sit in scoring context, or leading wildcards dominate latency. Ground every recommendation in search profiling — move non-scoring clauses to filter context, eliminate leading wildcards, and re-profile to confirm improvement.

Elasticsearch Ingest
elastic
Load CSV and JSON files into Elasticsearch indices using the bulk API and explicit mappings when field types matter. Use when batch-importing local files, converting CSV rows or JSON arrays to NDJSON bulk format, or verifying document counts and mappings after ingest — not for Logstash pipelines, Beats, custom scripts, or index-to-index reindex.

Kibana Dashboards
elastic
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.

Kibana Anomaly Detection
elastic
Investigates, explains, troubleshoots and configures Elastic ML anomaly detection jobs in Kibana/Elasticsearch.

Elasticsearch Cluster Health
elastic
Read-only triage of a non-green Elasticsearch cluster to name the likely cause and remediation.
More in Data & Analytics

Content Strategy
anthropics
Turns PayPal, QuickBooks or Square sales data into a prioritized 30-day content brief for small businesses.

Cash Flow Snapshot
anthropics
Builds a 30/60/90-day cash flow forecast with confidence bands and named risk flags from ledger, payment or CSV data.

Pipeline Review
anthropics
Reviews CRM sales pipeline health by stage, flagging aging, stale and at-risk deals and checking coverage.

Metrics Review
anthropics
Reviews product metrics, analyzes trends against targets, and produces a scorecard with recommended actions.

Performance Report
anthropics
Builds marketing performance reports with key metrics, trend analysis, wins and misses, and prioritized optimization recommendations.

People Report
anthropics
Generates HR people-analytics reports on headcount, attrition, diversity, and org health from workforce data.