langchain-chat-models
A unified interface for integrating and managing LLM chat providers like OpenAI, Anthropic, Google, Azure, and Bedrock within LangChain applications.
Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
545 skills found
A unified interface for integrating and managing LLM chat providers like OpenAI, Anthropic, Google, Azure, and Bedrock within LangChain applications.
A command-line tool and Expo module for interacting with Apple HealthKit, allowing you to seed, query, and verify health data in development.
Manage Jules (Google's async AI coding agent) directly from your terminal. Create, monitor, and interact with Jules coding sessions, approve plans, and handle feedback loops across repositories.
Generate high-quality text-to-speech audio using Microsoft Edge's neural voice engine via uvx edge-tts.
Comprehensive AI-generated text detection framework. Features multi-layer analysis of vocabulary, structural patterns, model-specific fingerprints, and technical metadata artifacts to identify AI authorship.
Language-agnostic debugging framework: scientific method, stack trace analysis, logging strategies, and advanced techniques like Git bisect and rubber ducking.
Enable long-running, multi-session autonomous development tasks with state tracking, resumable execution, and dual-agent planning-execution workflows.
Development guide for lemline-core, the stateless Serverless Workflow engine. Manage workflow execution, node navigation, state transitions, JQ expression evaluation, error handling, and parallel fork logic.
Production-grade React 19 and TypeScript patterns featuring hooks, state management, TanStack Query, form validation with Zod, and performance optimization workflows.
Profiles application performance using k6, Artillery, or JMeter to measure latency, throughput, and error rates. Ideal for planning load, stress, and soak tests to identify bottlenecks.
Database schema validation, data integrity testing, migration validation, transaction isolation, and query performance testing. Ensure ACID compliance and referential integrity for data-driven applications.
A framework for managing the end-to-end LLM project lifecycle, from evaluating task-model fit and pipeline architecture design to implementing structured output parsing and agent-assisted development.