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Found 10,596 Skills
Covers AWS security services and workflows — Security Hub V2 (OCSF) findings, connectors, aggregators, automation rules, and security posture summaries; Security Hub CSPM (V1/ASFF) controls and compliance standards; GuardDuty threat findings; Inspector vulnerability findings; Macie sensitive data findings; Detective investigation; and Security Lake configuration and data aggregation. Applicable when questions involve security posture, Exposure findings, CSPM failed controls, threat findings, vulnerability findings, sensitive data findings, automation rules, or cross-service security configuration across AWS environments. Procedures use standard AWS CLI syntax and work with or without the AWS MCP server.
Combine vector and keyword search for improved retrieval. Use when implementing RAG systems, building search engines, or when neither approach alone provides sufficient recall.
Integrate Vercel Blob for file uploads and CDN-delivered assets in Next.js. Supports client-side uploads with presigned URLs and multipart transfers for large files. Use when implementing file uploads (images, PDFs, videos) or troubleshooting missing tokens, size limits, client upload failures, token expiration errors, or browser compatibility issues. Prevents 16 documented errors.
Build Python APIs on Cloudflare Workers using pywrangler CLI and WorkerEntrypoint class pattern. Includes Python Workflows for multi-step DAG automation. Prevents 11 documented errors. Use when: building Python serverless APIs, migrating Python to edge, or troubleshooting async errors, package compatibility, handler pattern mistakes, RPC communication issues.
Expert guidance for fine-tuning LLMs with LLaMA-Factory - WebUI no-code, 100+ models, 2/3/4/5/6/8-bit QLoRA, multimodal support
Best practices for building with Gadget. Use when developers need guidance on models, actions, routes, access control, Shopify/BigCommerce integrations, frontend patterns, API usage, permissions, or framework decisions. Triggers "model", "action", "route", "permission", "access control", "multi-tenancy", "Shopify", "BigCommerce", "frontend", "API client", "filter", "pagination", "webhook", "background job"
Professional music creation with Suno AI V5 and Suno Studio. Use this skill when users want to create songs, playlists, corporate anthems, jingles, workout music, ambient soundscapes, or any AI-generated music. Triggers on requests mentioning Suno, music creation, playlist generation, song composition, or specific music projects like "create a track", "make a playlist", "compose music for", "corporate anthem", "workout mix", or any music production task.
Implement GraphRAG patterns combining knowledge graphs with retrieval for complex reasoning. Use this skill when building RAG over interconnected data or needing relationship-aware retrieval. Activate when: GraphRAG, knowledge graph, graph retrieval, entity relationships, Neo4j RAG, graph database, connected data.
Integrate digital health data sources (Apple Health, Fitbit, Oura Ring) and connect to WellAlly.tech knowledge base. Import external health device data, standardize to local format, and recommend relevant WellAlly.tech knowledge base articles based on health data. Support generic CSV/JSON import, provide intelligent article recommendations, and help users better manage personal health data.
Analyzes events through journalistic lens using 5 Ws and H, investigative methods, source evaluation, fact-checking, newsworthiness criteria, and ethical journalism principles. Provides insights on story angles, information gaps, credibility, public interest, and media framing. Use when: Breaking news, information verification, source analysis, story development, media criticism. Evaluates: Factual accuracy, source credibility, completeness, newsworthiness, bias, public interest.
Use this skill for setting up vector similarity search with pgvector for AI/ML embeddings, RAG applications, or semantic search. **Trigger when user asks to:** - Store or search vector embeddings in PostgreSQL - Set up semantic search, similarity search, or nearest neighbor search - Create HNSW or IVFFlat indexes for vectors - Implement RAG (Retrieval Augmented Generation) with PostgreSQL - Optimize pgvector performance, recall, or memory usage - Use binary quantization for large vector datasets **Keywords:** pgvector, embeddings, semantic search, vector similarity, HNSW, IVFFlat, halfvec, cosine distance, nearest neighbor, RAG, LLM, AI search Covers: halfvec storage, HNSW index configuration (m, ef_construction, ef_search), quantization strategies, filtered search, bulk loading, and performance tuning.
Enforces Supabase access patterns and service boundaries. Use only when working with Supabase projects. Centralizes Supabase in a dedicated layer and forbids calling Supabase from outside that boundary.