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Found 261 Skills
Payhip platform help — digital downloads, courses, memberships, coaching, store builder, marketing tools, API. Use when setting up a Payhip store or product, choosing between Payhip Free vs Plus vs Pro plan, configuring Payhip coupons or affiliate program, connecting Payhip to an email service provider, embedding Payhip on an existing website, troubleshooting Payhip checkout or payment issues, or managing Payhip webhooks and license keys. Do NOT use for general digital product strategy without a Payhip context (use /sales-digital-products).
LP, MILP, and QP (beta) with cuOpt — C API only. Use when the user is embedding LP, MILP, or QP in C/C++.
Use this skill when an existing multi-day public-class teaching site needs to be condensed and re-packaged for a corporate in-house training — typically a half-day or one-day intensive (e.g. 4-day public class → 6-hour corporate). Triggers on phrases like "企業包班", "濃縮版", "客製化課程", "corporate edition", "intensive version", "in-house training", "single-file deliverable", "客戶端課程", "壓縮成一天", or when the user wants a single-folder zippable deliverable for a client. This skill builds on top of an existing site — picking units, condensing time allocation, embedding data into a single HTML, setting up asset fallback chains, and producing an offline-ready package.
Install and configure Ollama for local embeddings with GrepAI. Use this skill when setting up private, local embedding generation.
Configure LM Studio as embedding provider for GrepAI. Use this skill for local embeddings with a GUI interface.
Guide for Vercel AI SDK v6 implementation patterns including generateText, streamText, ToolLoopAgent, structured output with Output helpers, useChat hook, tool calling, embeddings, middleware, and MCP integration. Use when implementing AI chat interfaces, streaming responses, agentic applications, tool/function calling, text embeddings, workflow patterns, or working with convertToModelMessages and toUIMessageStreamResponse. Activates for AI SDK integration, useChat hook usage, message streaming, agent development, or tool calling tasks.
Build AI-first applications with RAG pipelines, embeddings, vector databases, agentic workflows, and LLM integration. Master prompt engineering, function calling, streaming responses, and cost optimization for 2025+ AI development.
PostgreSQL-based semantic and hybrid search with pgvector and ParadeDB. Use when implementing vector search, semantic search, hybrid search, or full-text search in PostgreSQL. Covers pgvector setup, indexing (HNSW, IVFFlat), hybrid search (FTS + BM25 + RRF), ParadeDB as Elasticsearch alternative, and re-ranking with Cohere/cross-encoders. Supports vector(1536) and halfvec(3072) types for OpenAI embeddings. Triggers: pgvector, vector search, semantic search, hybrid search, embedding search, PostgreSQL RAG, BM25, RRF, HNSW index, similarity search, ParadeDB, pg_search, reranking, Cohere rerank, pg_trgm, trigram, fuzzy search, LIKE, ILIKE, autocomplete, typo tolerance, fuzzystrmatch
Use when adding interactive 3D scenes from Spline.design to web projects, including React embedding and runtime control API.
Vector embeddings with HNSW indexing, sql.js persistence, and hyperbolic support. 75x faster with agentic-flow integration. Use when: semantic search, pattern matching, similarity queries, knowledge retrieval. Skip when: exact text matching, simple lookups, no semantic understanding needed.
Access Telnyx LLM inference APIs, embeddings, and AI analytics for call insights and summaries. This skill provides Python SDK examples.
Display and manipulate PDF documents using PDFKit. Use when embedding PDFView to show PDF files, creating or modifying PDFDocument instances, adding annotations (highlights, notes, signatures), extracting text with PDFSelection, navigating pages, generating thumbnails, filling PDF forms, or wrapping PDFView in SwiftUI.