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Gemini Deep Research

sickn33/antigravity-awesome-skills

Uses the Gemini API to autonomously plan, search, read, and synthesize detailed research reports with streaming status updates, structured outputs, and the ability to continue previous investigations for market analysis, technical reviews, or due diligence.

On-Device LLM Integration for Apple Platforms

foundation-models-on-device

affaan-m/everything-claude-code

This guide details integrating FoundationModels for running Large Language Models (LLMs) directly on the device (iOS 26). It covers advanced patterns including text generation, extracting structured data using @Generable, implementing custom tool calling for domain logic, and streaming responses for real-time UI updates. Key features emphasize strong privacy and offline capability, ensuring no data leaves the device.

Instructor Structured Outputs

Orchestra-Research/AI-Research-SKILLs

Instructor lets you shape LLM responses into validated Pydantic models, automatically retrying failed extractions, parsing complex JSON with type safety, and streaming partial outputs across Anthropic, OpenAI, and other providers.

LangChain Production Patterns Guide

langchain-sdk-patterns

jeremylongshore/claude-code-plugins-plus-skills

This comprehensive guide outlines essential, production-grade patterns for building robust LangChain applications. Learn best practices for implementing type-safe structured output using Zod, handling provider fallbacks, processing inputs concurrently with batching, optimizing user experience with streaming, and ensuring reliability through caching and retries.

Build M365 Agents with TypeScript SDK

sickn33/antigravity-awesome-skills

This comprehensive SDK provides tools for building enterprise-grade AI agents integrated across the Microsoft 365 ecosystem, including Teams and Copilot Studio. It supports advanced features such as Express hosting, structured routing, streaming responses via Azure OpenAI, and direct client integration, enabling developers to build sophisticated business automation solutions.

Mistral AI Core Workflow for Chat Completions

mistral-core-workflow-a

jeremylongshore/claude-code-plugins-plus-skills

This comprehensive workflow guide covers all production-ready patterns for Mistral AI chat completions. It demonstrates critical advanced features including multi-turn conversation management, real-time streaming responses, structured JSON output using schemas, and implementing robust guardrails and moderation. Ideal for building scalable, production-grade conversational AI applications and advanced chat interfaces.

Mistral AI Chat Completion Quickstart

mistral-hello-world

jeremylongshore/claude-code-plugins-plus-skills

This comprehensive guide provides minimal working examples for integrating with the Mistral AI API. It demonstrates core LLM functionalities including basic chat completion, streaming responses, multi-turn conversations, and generating structured JSON output. Use this guide when starting a new Mistral integration, testing API connections, or learning advanced AI patterns using TypeScript or Python.

Mistral AI SDK Best Practices

mistral-sdk-patterns

jeremylongshore/claude-code-plugins-plus-skills

This guide provides production-ready patterns for integrating the Mistral AI SDK in both TypeScript and Python. It covers essential best practices such as singleton client management, handling structured JSON output, implementing streaming responses, concurrent asynchronous processing, and robust error handling with exponential backoff. Use this when establishing team coding standards or refactoring Mistral API usage.

Vercel AI SDK for Next.js Development

vercel-ai-sdk-expert

sickn33/antigravity-awesome-skills

An expert guide for developing production-grade AI applications, chatbots, and generative UIs using the Vercel AI SDK, Next.js, and React. Covers core concepts including streaming text (`streamText`), managing chat state (`useChat`), implementing complex tool/function calling, and ensuring robust structured data generation (JSON schemas) across multiple LLM providers.

Advanced Anthropic Messages API Patterns

clade-model-inference

jeremylongshore/claude-code-plugins-plus-skills

This guide covers advanced usage of the Anthropic Messages API. Learn how to implement real-time streaming responses, utilize system prompts for persona control, process visual inputs (Vision), and enforce structured data output (JSON). This is essential for building sophisticated, robust, and multi-modal Claude-powered applications.

Cloud LLM Provider Regression Testing

cloud-provider-regression-test

SharpAI/DeepCamera

Automates comprehensive regression testing for all enabled cloud Large Language Model (LLM) providers. This includes verifying core connectivity, standard chat completion, structured JSON output, and Server-Sent Events (SSE) streaming capabilities. Essential for ensuring the reliability and stability of multi-cloud AI integrations in a CI/CD pipeline.

Anthropic Core Messages API Workflow

clade-core-workflow-a

jeremylongshore/claude-code-plugins-plus-skills

This skill provides the comprehensive workflow for interacting with the Anthropic Messages API. It covers advanced features including streaming responses, multimodal vision input, generating structured JSON output using system prompts, and managing multi-turn conversations. It redirects users to the current, primary guide for all Claude API patterns.

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