Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
123 skills found
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.
Analyzes markdown files to identify token-wasting patterns, providing actionable suggestions to optimize documentation for LLM consumption and token efficiency.
Convert various documents, media, and web content into Markdown using markitdown, ideal for LLM processing and text analysis.
Implement production-grade AI agents with LangGraph, tool-calling guardrails, SSE streaming, and episodic memory. Includes anti-patterns, fix pairs, and stateful architecture patterns.
Systematically extract insights, decisions, and constraints from research documents, technical papers, and architectural design files.
Guides agent memory system implementation, compares frameworks (Mem0, Zep, Letta, LangMem, Cognee), and designs persistence architectures for cross-session knowledge retention.
Upstash Vector DB setup, semantic search, namespaces, and embedding models. Ideal for building high-performance vector search features in Next.js 16/Vercel projects.
Advanced Google search using a real, JavaScript-rendered Chrome browser. Ideal for scraping full page content, site-specific queries, and time-filtered results.
Search the web using Tavily's LLM-optimized search API for relevant, source-cited content without writing code.
A systematic, multi-angle web research agent. Use for deep investigation, complex queries, and as a mandatory pre-research step before content generation to ensure evidence-backed, high-quality results.
Manage isolated LlamaFarm development environments using git worktrees for parallel agent sessions and service testing.
Crawl websites to extract content as clean markdown files. Ideal for documentation, research, and offline knowledge management.