ai-llm-patterns
Anthropic Claude integration patterns: streaming, RAG with pgvector, tool use, model selection (Haiku/Sonnet/Opus), prompt caching, and cost management for AI-powered engineering.
Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
371 skills found
Anthropic Claude integration patterns: streaming, RAG with pgvector, tool use, model selection (Haiku/Sonnet/Opus), prompt caching, and cost management for AI-powered engineering.
Easily configure and add Model Context Protocol (MCP) servers to various AI coding clients like Cursor, Claude, VS Code, and more using an interactive or automated command-line interface.
Create high-performance AI skills by reverse-engineering successful GitHub projects and proven open-source methodologies.
RPI Plan Phase: Create chunk-based, dependency-aware implementation plans from research documents for structured, atomic development.
Break down complex development requests into sequenced, actionable tasks for multi-agent delegation in Claude Code environments.
Enriches vague prompts by performing codebase research and asking targeted questions to clarify user intent before execution.
Skill for managing MCP-based research, documentation lookups, and coordination between external search tools and plugin-backed memory systems.
Guide for integrating and managing custom Model Context Protocol (MCP) servers within the Cursor IDE environment.
Transform raw data into compelling, decision-driving narratives using visualization strategies, story frameworks, and persuasive structures for analytics and executive reporting.
Draft and optimize LinkedIn posts for 0 Finance using performance-backed hooks, professional storytelling, and strict regulatory compliance guidelines.
A testing utility designed to simulate prompt injection attacks and validate security scanners for AI agent skills.
Research technical documentation and automatically generate ready-to-use software agent skills in markdown format.