llm-integration
A toolkit for building robust LLM integrations: API patterns, streaming, function calling, RAG pipelines, and cost-effective model routing.
Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
148 skills found
A toolkit for building robust LLM integrations: API patterns, streaming, function calling, RAG pipelines, and cost-effective model routing.
Manage isolated LlamaFarm development environments using git worktrees for parallel agent sessions and service testing.
Real-time observability dashboard for PAI multi-agent activity, featuring live WebSocket streaming, session tracing, and agent workflow debugging.
A standardized workflow for converting raw PM notes, workshops, or rough drafts into polished, validated, and repository-compliant AI skills.
Orchestrate end-to-end quality engineering across CI/CD pipelines, from commit-stage unit testing and shift-left strategies to production-stage synthetic monitoring and compliance gates.
Implement Google Gemini API vision capabilities for image/document analysis including captioning, object detection, segmentation, and multi-image comparison.
Execute z.AI CLI for multimodal analysis, web search, reader, and GitHub repo exploration via CLI and MCP.
Multi-perspective AI consultation for technical architecture, complex refactoring, and structured debugging.
Build RAG systems to ground LLMs in proprietary data. Includes vector database integration, embedding strategies, hybrid search, and advanced retrieval patterns for FastAPI backends.
ClawHub is the official registry and CLI tool for managing OpenClaw AI agent skills. Search, install, version-control, and publish custom skills to your local OpenClaw workspace.
Train and manage neural networks in distributed E2B sandboxes using the Flow Nexus platform, supporting custom architectures like Transformers, LSTMs, and GANs.
A wise conductor of expert agents. It helps you achieve goals by summoning, orchestrating, and creating specialized AI experts. Features intellectual humility, multi-agent debate, and self-learning pattern capture.