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Run npx skillmds@latest add modra40/elasticsearch-principal-engineer in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

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modra40 (@modra40) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Elasticsearch Principal Engineer by modra40

Name: Elasticsearch Principal Engineer
Author: modra40

Elasticsearch Principal Engineer

Principal/Senior-level Elasticsearch playbook for index design, search relevance, cluster operations, performance tuning, observability, and production reliability. Use when: designing search workloads, reviewing mappings and analyzers, fixing shard/query bottlenecks, or operating Elasticsearch in production.

modra40 f07825e 16 files · 10.0 KB Updated Sep 17, 2026

File contents

Elasticsearch Mastery (Senior → Principal)

Operate

Start with query patterns, relevance requirements, data freshness, and retention.
Treat mapping, analyzer, shard count, and indexing strategy as architectural choices.
Optimize for predictable operations, not demo-search quality only.
Distinguish logging/observability use-cases from user-facing search needs.

Default Standards

Mappings should be explicit on important fields.
Shards are not free; oversharding is an operational tax.
Relevance tuning requires representative queries and evaluation, not intuition.
Observe indexing throughput, search latency, heap pressure, GC, and shard health.

References

Indexing and query design: references/indexing-and-query-design.md
Operations and relevance: references/operations-and-relevance.md
Mappings and analyzers: references/mappings-and-analyzers.md
Query DSL and scoring: references/query-dsl-and-scoring.md
Shards and cluster layout: references/shards-and-cluster-layout.md
Indexing pipelines: references/indexing-pipelines.md
Search relevance: references/search-relevance.md
Aggregations and analytics: references/aggregations-and-analytics.md
ILM and retention: references/ilm-and-retention.md
Capacity planning: references/capacity-planning.md
Security and multi-tenant: references/security-and-multi-tenant.md
Backup, restore, and snapshots: references/backup-restore-and-snapshots.md
Observability: references/observability.md
Logging vs search clusters: references/logging-vs-search-clusters.md
Incident runbooks: references/incident-runbooks.md

---name: elasticsearch-principal-engineerdescription: Principal/Senior-level Elasticsearch playbook for index design, search relevance, cluster operations, performance tuning, observability, and production reliability. Use when: designing search workloads, reviewing mappings and analyzers, fixing shard/query bottlenecks, or operating Elasticsearch in production.---# Elasticsearch Mastery (Senior → Principal)## Operate- Start with query patterns, relevance requirements, data freshness, and retention.- Treat mapping, analyzer, shard count, and indexing strategy as architectural choices.- Optimize for predictable operations, not demo-search quality only.- Distinguish logging/observability use-cases from user-facing search needs.## Default Standards- Mappings should be explicit on important fields.- Shards are not free; oversharding is an operational tax.- Relevance tuning requires representative queries and evaluation, not intuition.- Observe indexing throughput, search latency, heap pressure, GC, and shard health.## References- Indexing and query design: [references/indexing-and-query-design.md](references/indexing-and-query-design.md)- Operations and relevance: [references/operations-and-relevance.md](references/operations-and-relevance.md)- Mappings and analyzers: [references/mappings-and-analyzers.md](references/mappings-and-analyzers.md)- Query DSL and scoring: [references/query-dsl-and-scoring.md](references/query-dsl-and-scoring.md)- Shards and cluster layout: [references/shards-and-cluster-layout.md](references/shards-and-cluster-layout.md)- Indexing pipelines: [references/indexing-pipelines.md](references/indexing-pipelines.md)- Search relevance: [references/search-relevance.md](references/search-relevance.md)- Aggregations and analytics: [references/aggregations-and-analytics.md](references/aggregations-and-analytics.md)- ILM and retention: [references/ilm-and-retention.md](references/ilm-and-retention.md)- Capacity planning: [references/capacity-planning.md](references/capacity-planning.md)- Security and multi-tenant: [references/security-and-multi-tenant.md](references/security-and-multi-tenant.md)- Backup, restore, and snapshots: [references/backup-restore-and-snapshots.md](references/backup-restore-and-snapshots.md)- Observability: [references/observability.md](references/observability.md)- Logging vs search clusters: [references/logging-vs-search-clusters.md](references/logging-vs-search-clusters.md)- Incident runbooks: [references/incident-runbooks.md](references/incident-runbooks.md)

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