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.
542 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.
Tamagui library best practices for architecture, configuration, compiler optimization, and component patterns.
Manage your personal OpenAnt task history, status, and assignments. Retrieve, track, and review tasks as a worker or creator.
Transform AI agents into proactive partners using WAL Protocol, persistent memory buffers, and autonomous cron scheduling to anticipate needs and improve performance.
Expert guidance for Google Ads Script development including AdsApp API, campaign management, keyword bidding, automated rules, performance reporting, and spend optimization.
Complete project architecture and structure guide for LobeHub. Use for codebase exploration, project organization, file location, and architectural context.
Streamline continuous fuzzing for open-source projects using the OSS-Fuzz CLI framework to build harnesses, manage configurations, and generate coverage reports.
Automates the creation of isolated git worktree environments for parallel feature development and environment setup.
High-performance document intelligence library for extracting text, tables, code, and metadata from 91+ file formats, with OCR and LLM-ready output.
Automate your entire Git lifecycle from commit and PR creation to CI monitoring and branch merging, enforcing conventional commits throughout.
Create, refine, and optimize high-quality YAML prompts for AI assistants using structure guidelines, template patterns, and quality standards.
A standardized template for creating and documenting modular Agent Skills to ensure consistent, efficient context engineering across AI agent systems.