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Search Tool Integration , found 18 results

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CrewAI Multi-Agent Orchestration

crewai-multi-agent

Orchestra-Research/AI-Research-SKILLs

CrewAI orchestrates autonomous multi-agent teams for role-based collaboration, sequential or hierarchical workflows, and production-grade orchestration with memory and tool integrations without LangChain.

HuggingFace Tokenizer Suite

huggingface-tokenizers

Orchestra-Research/AI-Research-SKILLs

High-performance Rust-backed tokenization toolkit with Python bindings, offering BPE/WordPiece/Unigram, custom vocabulary training, alignment tracking, and production-ready integrations for NLP pipelines.

Automate Insighto AI Tasks

insighto-ai-automation

ComposioHQ/awesome-claude-skills

Automate Insighto AI operations by discovering tool schemas via Rube MCP, validating Insighto AI connections, and executing workflows through Composio’s toolkit to keep integrations resilient.

Automating Video Generation in CI/CD

klingai-ci-integration

jeremylongshore/claude-code-plugins-plus-skills

This tool allows developers to integrate advanced AI video generation (using Kling AI) directly into continuous integration and continuous deployment pipelines (e.g., GitHub Actions, GitLab CI). Automate the creation of marketing videos, product demos, or regression video testing whenever code changes or a release occurs, ensuring consistent and timely video asset updates.

LangChain Architecture for LLM Applications

langchain-architecture

sickn33/antigravity-awesome-skills

Master the LangChain framework, the industry standard for building sophisticated and production-grade Large Language Model (LLM) applications. This skill covers core concepts including autonomous agents, multi-step chains, memory management, Retrieval-Augmented Generation (RAG), and external tool integration, enabling the development of complex, stateful AI systems.

Lindy AI Agent Debugging Bundle

lindy-debug-bundle

jeremylongshore/claude-code-plugins-plus-skills

A comprehensive diagnostic toolkit designed for advanced troubleshooting of Lindy AI agents. This bundle systematically collects environment information (OS, Python, Node.js), tests API connectivity for webhooks and major integrations (Slack, Notion, Gmail), reviews task history, and guides the user in generating a full, structured support ticket for technical support.

LLM Integration Patterns

llm-integration

rohitg00/awesome-claude-code-toolkit

Practical guide to integrating Claude models: covers API client usage, streaming responses, tool calls, RAG pipelines, document chunking, cost-aware model selection, and anti-pattern warnings for efficient LLM workflows.

OpenAI Automation Toolkit

openai-automation

ComposioHQ/awesome-claude-skills

Automate OpenAI API workflows through the Composio MCP integration, covering text and multimodal responses with structured outputs, embeddings, image generation, and model discovery.

Integrating Google Gemini API for AI Projects

gemini-api-integration

sickn33/antigravity-awesome-skills

This comprehensive guide covers all aspects of integrating the Google Gemini API into your applications using Python or Node.js. It details basic text generation, advanced multimodal inputs (text, image, audio), streaming responses, function calling/tool use, multi-turn chat implementation, and production best practices like model selection and robust error handling.

Building M365 Copilot Declarative Agents

mcp-create-declarative-agent

github/awesome-copilot

A comprehensive guide for developers to build advanced, declarative agents for Microsoft 365 Copilot. This skill details the integration process using a Model Context Protocol (MCP) server, allowing the agent to connect with external systems, select tools, and handle complex authentication (OAuth 2.0/SSO). You will learn to generate key JSON manifests required for deployment.

Single-Cell Omics Generative Modeling Toolkit

K-Dense-AI/scientific-agent-skills

A comprehensive Python framework utilizing deep generative models and variational inference for advanced single-cell genomics analysis. It supports the integration and analysis of diverse multi-modal data types, including single-cell RNA-seq, ATAC-seq, CITE-seq, and spatial transcriptomics. Key applications include probabilistic batch correction, cell type annotation, and multi-omics integration.

Migrating AI Integrations to Cohere

cohere-migration-deep-dive

jeremylongshore/claude-code-plugins-plus-skills

This comprehensive guide provides a deep dive into migrating AI applications from major LLM providers (like OpenAI or Anthropic) to the Cohere platform. It covers critical technical steps, including API call adaptation, re-vectorizing embeddings, migrating tool definitions, and implementing the Adapter Pattern for seamless, gradual re-platforming of existing AI services.

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