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Found 56 Skills
Analyzes and optimizes SQL/NoSQL queries for performance. Use when reviewing query performance, optimizing slow queries, analyzing EXPLAIN output, suggesting indexes, identifying N+1 problems, recommending query rewrites, or improving database access patterns. Supports PostgreSQL, MySQL, SQLite, MongoDB, Redis, DynamoDB, and Elasticsearch.
Ultimate 25+ years expert-level backend skill covering FastAPI, Express, Node.js, Next.js with TypeScript. Includes ALL databases (PostgreSQL, MongoDB, Redis, Elasticsearch), ALL features (REST, GraphQL, WebSockets, gRPC, Message Queues), comprehensive security hardening (XSS, CSRF, SQL injection, authentication, authorization, rate limiting), complete performance optimization (caching, database tuning, load balancing), ALL deployment strategies (Docker, Kubernetes, CI/CD), advanced patterns (microservices, event-driven, saga, CQRS), ALL use cases (e-commerce, SaaS, real-time, high-traffic), complete testing (unit, integration, E2E, load, security). Route protection, middleware, authentication implementation in PERFECTION. Use for ANY backend system requiring enterprise-grade security, performance, scalability, and architectural excellence.
Amazon OpenSearch Service and Serverless across five capabilities — migration (Solr/ES/self-managed OpenSearch into AOS/AOSS, schema/query translation, sizing, cutover); provisioning (domain + AOSS lifecycle, upgrades, storage tiers, FGAC, monitoring); search (vector / semantic / hybrid / RAG with Bedrock connectors); log-analytics (PPL, OSI ingestion, anomaly detection, OpenSearch Dashboards, Splunk/Datadog alternatives); trace-analytics (OTel spans, service maps, Data Prepper). Triggers on OpenSearch, AOS, AOSS, Elasticsearch, ELK, Solr, Lucene, vector / k-NN / semantic / hybrid / neural search, RAG, ELSER, log analytics, observability, Kibana, OSI, OCU, PPL, trace analytics, BM25, eDisMax, schema.xml, ILM, ISM, FAISS, HNSW, Migration Assistant for Amazon OpenSearch Service, Historical Data Migration, Live Traffic Migration, UltraWarm, OR1, Splunk/Datadog alternative, moving off Solr. Picks ONE capability per ask, names instance class + count + shard math, ships query DSL examples.
Eino component selection, configuration, and usage. Use when a user needs to choose or configure a ChatModel, Embedding, Retriever, Indexer, Tool, Document loader/parser/transformer, Prompt template, or Callback handler. Covers all component interfaces and their implementations in eino-ext including OpenAI, Claude, Gemini, Ollama, Milvus, Elasticsearch, Redis, MCP tools, and more.
Workload-aware architecture design for Apache Doris. MUST USE when designing data architectures, choosing between data models, planning ingestion strategies, sizing clusters, or translating business requirements into Apache Doris system designs. Complements doris-best-practices with decision frameworks and sizing-first workflow. Use when user describes a workload involving: IoT, sensor data, telemetry, real-time analytics, dashboard, log analysis, log search, CDC sync, time-series, device monitoring, point query service, ad-hoc analytics, lakehouse federation, ETL/ELT pipeline, report analytics, clickstream, user behavior, observability, metrics, fleet tracking, or any OLAP workload requiring table design from scratch. Also triggers on prompts like: "design a table for...", "how should I store...", "build an architecture for...", "we have X devices sending data every Y seconds", "recommend a cluster size for...", "what data model should I use for...", "we need to ingest X GB/day", "migrate from MySQL/PostgreSQL to Apache Doris". Also use for legacy analytics/search/serving stack consolidation prompts even when Apache Doris is not named explicitly, including replacing or migrating from Impala, Kudu, Elasticsearch/ES, Greenplum, Presto, HBase, Hive, Hadoop, Redis, or Lambda-style multi-engine data platforms.
Alibaba Cloud Elasticsearch Instance Network Management Skill. Use for managing ES instance network configurations including triggering network, Kibana PVL network, white IP list, HTTPS settings, and Kibana SSO authentication. Triggers: "elasticsearch network", "ES network", "kibana pvl", "white ip", "https", "trigger network", "modify white ips", "kibana sso", "kibana authentication".
VeloDB/Apache Doris table design and cluster sizing best practices. MUST USE when writing, reviewing, or optimizing Doris CREATE TABLE statements, partition/bucket strategies, data models, or cluster configurations. ALSO MUST USE whenever the velodb-architecture-advisor skill produces DDL — apply the Pre-Flight Checklist to every CREATE TABLE before output. Also triggers on any workload design involving: IoT, analytics, dashboard, CDC, time-series, log analysis, real-time warehouse, point query, data platform, or any scenario where table design decisions are being made. Also triggers on replacing or migrating from legacy analytics/search/serving stacks such as Impala, Kudu, Elasticsearch/ES, Greenplum, Presto, HBase, Hive, Hadoop, Redis, or Lambda-style multi-engine data platforms, even when VeloDB/Doris is not named explicitly. Also use when user provides a VeloDB connection string or asks to get started. Also triggers on slow query investigation, query profiling, runtime performance diagnosis, tablet skew analysis, and table health checks — any scenario where runtime evidence (profile output, tablet distribution) informs optimization. For Cloud operations (auth, cluster lifecycle, billing, networking), defer to the velocli-cloud skill.
Answer questions using the Tenzir documentation. Use whenever the user asks about TQL syntax, pipeline operators, functions, data parsing or transformation, normalization, OCSF mapping, enrichment, lookup tables, contexts, packages, nodes, platform setup, deployment, configuration, integrations with tools like Splunk, Kafka, S3, Elasticsearch, or any other Tenzir feature. Also use when the user asks how to collect, route, filter, aggregate, or export security data with Tenzir, or needs help writing or debugging TQL pipelines, even if they don't mention 'Tenzir' explicitly but are clearly working in a Tenzir context.
Activate when the user asks Claude to talk like a caveman, use caveman mode, say "less tokens please", or invoke "/elastic-caveman". Also activate when the user wants faster, terser responses while still working with Elasticsearch, Kibana, Elastic Security, Elastic Observability, or any part of the Elastic stack. In caveman mode all Elasticsearch-specific technical terms, API names, field names, index patterns, query DSL structures, ESQL syntax, and error messages are preserved verbatim — only filler words and pleasantries are removed. Stop caveman mode when the user says "stop caveman" or "normal mode".
Implements search and filter interfaces for both frontend (React/TypeScript) and backend (Python) with debouncing, query management, and database integration. Use when adding search functionality, building filter UIs, implementing faceted search, or optimizing search performance.
Enable and configure Kibana audit logging for saved object access, logins, and space operations. Use when setting up Kibana audit, filtering events, or correlating Kibana and ES audit logs.
Kibana integration. Manage data, records, and automate workflows. Use when the user wants to interact with Kibana data.