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Found 206 Skills
Ingest and transform data files (CSV/JSON/Parquet/Arrow IPC) into Elasticsearch with stream processing, custom transforms, and cross-version reindexing. Use when loading files, batch importing data, or migrating indices across versions — not for general ingest pipeline design or bulk API patterns.
Manage the Grounded Docs MCP Server documentation index. Covers scraping and indexing documentation from URLs or local files, refreshing existing indexes with changed content, and removing libraries from the index. Use when you need to add, update, or delete indexed documentation.
This skill should be used when code search is needed (whether explicitly requested or as part of completing a task), when indexing the codebase after changes, or when the user asks about codeindex, cocoindex-code, or the codebase index. Trigger phrases include 'search the codebase', 'find code related to', 'update the index', 'codeindex', 'cocoindex-code'.
Transform slow database queries into lightning-fast operations through systematic optimization, proper indexing, and query plan analysis.
Comprehensive skill for the `kb` CLI and the Karpathy Knowledge Base pattern. Covers the full KB lifecycle — topic scaffolding, multi-source ingestion (URLs, files, YouTube, bookmarks, codebases), wiki article compilation, cross-article querying with file-back, lint-and-heal passes, QMD indexing, and hybrid search. Also covers codebase-specific analysis via inspect commands for complexity, coupling, blast radius, dead code, circular dependencies, symbol/file lookups, backlinks, and code smells. Use when working with kb CLI commands, knowledge base workflows, code vault generation, code graph analysis, code metrics inspection, wiki compilation, or the ingest-compile-query-lint cycle. Do not use for general code review, linting, formatting, building Go projects, or writing application code.
Design and optimize database schemas for SQL and NoSQL databases. Use when creating new databases, designing tables, defining relationships, indexing strategies, or database migrations. Handles PostgreSQL, MySQL, MongoDB, normalization, and performance optimization.
Design robust, scalable database schemas for SQL and NoSQL databases. Provides normalization guidelines, indexing strategies, migration patterns, constraint design, and performance optimization. Ensures data integrity, query performance, and maintainable data models.
When the user wants to audit, review, or diagnose SEO issues on their site. Uses live web data via the Bright Data CLI for accurate detection of JS-injected schema, hreflang, canonicals, and live SERP-based ranking checks. Also use when the user mentions "SEO audit," "technical SEO," "why am I not ranking," "SEO issues," "on-page SEO," "meta tags review," "SEO health check," "my traffic dropped," "lost rankings," "not showing up in Google," "site isn't ranking," "Google update hit me," "page speed," "core web vitals," "crawl errors," or "indexing issues." Use this even if the user just says something vague like "my SEO is bad" or "help with SEO" — start with an audit. For building pages at scale to target keywords, see programmatic-seo. For implementing structured data, see schema-markup. For AI search optimization, see ai-seo.
Azure AI Search SDK for Python. Use for vector search, hybrid search, semantic ranking, indexing, and skillsets. Triggers: "azure-search-documents", "SearchClient", "SearchIndexClient", "vector search", "hybrid search", "semantic search".
Universal SQL performance optimization assistant for comprehensive query tuning, indexing strategies, and database performance analysis across all SQL databases (MySQL, PostgreSQL, SQL Server, Oracle). Provides execution plan analysis, pagination optimization, batch operations, and performance monitoring guidance.
JPA/Hibernate patterns for entity design, relationships, query optimization, transactions, auditing, indexing, pagination, and pooling in Spring Boot.
Explains SEO for web applications including crawling, indexing, Core Web Vitals, structured data, and SEO challenges with SPAs. Use when optimizing for search engines, discussing SEO implications of architecture decisions, or implementing SEO best practices.