Loading...
Loading...
Found 56 Skills
Help developers new to Elasticsearch get from zero to a working search experience. Guide them through understanding their intent, mapping their data, and building a search experience with best practices baked in. Use this when developers are new to Elasticsearch and need help getting started with their search use case.
Alibaba Cloud Elasticsearch instance diagnosis skill. Use for cluster health checks, troubleshooting, and performance analysis on Elasticsearch instances. Triggers (English): Elasticsearch diagnosis, ES instance issues, slow search, write failures, cluster Red/Yellow, unassigned shards, node disconnected, load imbalance, thread pool 429, JVM/OOM/circuit breaker, disk watermark / read-only index, instance activating / change stuck, service avalanche / all shards failed. 触发词（中文）: ES诊断、阿里云ES、Elasticsearch诊断、ES集群/实例故障排查、ES健康检查、集群红灯/变红/黄灯/变黄、集群异常、分片未分配、主分片未分配、节点掉线/离线、负载不均衡、搜索/查询变慢、慢查询、写入失败/变慢/拒绝、线程池打满、HTTP 429、内存过高、OOM、断路器、磁盘满/水位、索引只读、实例激活中/activating、变更卡住/未完成、雪崩、服务不可用、all shards failed。
Expert-level Elasticsearch, search, ELK stack, and full-text search
Alibaba Cloud Elasticsearch Instance Management Skill. Use for creating, querying, listing, and restarting Elasticsearch instances on Alibaba Cloud. Triggers: "elasticsearch", "ES instance", "elasticsearch instance", "create ES", "query ES instance", "restart ES", "ES node", "cluster node"
Use when designing or modifying Elasticsearch ingest pipelines, including single-path parsing, branching logic, sub-pipelines, enrichment processors, and robust on_failure handling.
Spring Data Elasticsearch for full-text search and analytics. Covers ElasticsearchOperations, repositories, aggregations, and index management. USE WHEN: user mentions "spring data elasticsearch", "ElasticsearchRepository", "ElasticsearchOperations", "@Document elasticsearch", "Spring Boot Elasticsearch" DO NOT USE FOR: raw Elasticsearch queries - use `elasticsearch` instead, ELK stack setup - use `elasticsearch` instead
Diagnose a non-green Elasticsearch cluster and surface the single most likely cause with remediation. Use when an operator reports yellow or red status, unassigned shards, allocation failures, or wants read-only triage before deeper investigation. Teaches replica-vs-primary impact, allocation decider classification, and data-loss awareness.
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.
Guide Elasticsearch reindex for performance: local and remote, slicing, throttling, task API. Use when copying or migrating indices, changing mappings, or transforming during reindex.
Explain Elasticsearch ML anomaly detection scores, model behavior, and result interpretation. Use when the user asks why a score is high or low, how the model learns, what the numbers mean, or how to troubleshoot unexpected anomaly scores.
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.
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.