cosense
A comprehensive automation skill for Cosense (formerly Scrapbox) enabling page reading, searching, creating, and safe editing via API.
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140 skills found
A comprehensive automation skill for Cosense (formerly Scrapbox) enabling page reading, searching, creating, and safe editing via API.
Essential guide to llmemory for document storage and search: installation, database setup with pgvector, document ingestion, hybrid/semantic retrieval, and building RAG systems with multi-tenant support.
Automates the integration of Python and TypeScript type hints to enhance IDE intellisense, error detection, and AI code comprehension.
Automates TypeScript type generation from Rust tool schemas to ensure end-to-end type safety between server and client in MCP-based projects.
A local RAG semantic memory system using Qdrant and Ollama. Ideal for recalling workspace files, notes, project decisions, and user preferences with high-relevance vector search.
Persistent, Git-friendly memory for Claude. Automatically store and retrieve project decisions, bug fixes, and coding patterns in a local .mv2 file.
Upstash Vector DB setup, semantic search, namespaces, and embedding models. Ideal for building high-performance vector search features in Next.js 16/Vercel projects.
Query the Pollinations text API with web-search enabled models like Gemini and Perplexity for grounded, real-time research.
Enforce strict Python 3.12+ type safety and modern annotation standards for high-quality, maintainable codebases.
Local hybrid search engine for markdown notes, documentation, and codebase knowledge bases to reduce token consumption and improve retrieval efficiency.
TypeScript development standards for LobeHub, covering type safety, async patterns, import organization, UI component integration, and performance optimization.
Accelerate task retrieval with a high-performance, debounced search engine supporting multi-token AND logic, relevance ranking, and real-time text highlighting across task titles, descriptions, and tags.