Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
161 skills found
AI language tutor for personalized learning through conversation, grammar lessons, vocabulary drills, and flashcards. Supports 100+ languages including Spanish, French, Japanese, and Mandarin.
Anthropic Claude integration patterns: streaming, RAG with pgvector, tool use, model selection (Haiku/Sonnet/Opus), prompt caching, and cost management for AI-powered engineering.
Leverage the Figma MCP server to fetch design data, extract assets, and transform Figma nodes into production-ready React and Tailwind code with design system alignment.
Diagnose, isolate, and mitigate LLM context failures like lost-in-middle, poisoning, distraction, and context clash to improve agent reliability.
Supermemory is a long-term memory infrastructure for AI agents, enabling persistent context, user profiles, and semantic RAG across multi-modal knowledge bases.
Anthropic Claude AI models for high-performance coding, large-context analysis, and GUI interaction.
Guides agent memory system implementation, compares frameworks (Mem0, Zep, Letta, LangMem, Cognee), and designs persistence architectures for cross-session knowledge retention.
Generate publication-quality statistical plots from CSV or JSON data files using AI-driven automated visualization.
A structured repository of Agent Skills for context engineering, multi-agent architectures, and production-grade agent system optimization.
Implementation patterns for MERIDIAN autonomous AI agents using Claude API, including BaseAgent lifecycle, structured tool use, token budget enforcement, and cron scheduling.
A RAG-based AI solver for high school Chinese GSAT exams, featuring structured knowledge retrieval, reasoning templates, and explainable AI outputs.
Behavioral guidelines for LLMs to reduce coding mistakes, follow best practices, and improve output quality by enforcing simplicity, surgical changes, and goal-driven verification.