langchain-chat-models
A unified interface for integrating and managing LLM chat providers like OpenAI, Anthropic, Google, Azure, and Bedrock within LangChain applications.
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505 skills found
A unified interface for integrating and managing LLM chat providers like OpenAI, Anthropic, Google, Azure, and Bedrock within LangChain applications.
Expert assistant for designing and optimizing production-grade Trigger.dev background jobs, AI workflows, and resilient asynchronous task architectures in TypeScript.
A comprehensive moderation toolkit for Civitai, providing automated user management, strike systems, image review, content regulation, and CSAM reporting via tRPC API.
Transform text into professional Mermaid diagrams. Automatically handles syntax, subgraphs, and layout rules for clean flowcharts, sequence diagrams, and process maps.
A structured guide for novelists to navigate the seven-step writing process, from constitution and specification to planning, tasking, drafting, and quality analysis.
Process massive files and large codebases (10M+ tokens) by recursively chunking, sub-querying, and aggregating results to overcome LLM context limits.
A comprehensive aphorism and quote management system for thematic content enrichment, research, and newsletter curation.
Implement professional-grade test automation strategy, manage test pyramids, detect anti-patterns, and integrate with CI/CD for resilient, fast, and high-quality software testing.
A comprehensive framework for deep analysis of articles, papers, and long-form content using 10+ thinking models like SCQA, First Principles, and Systems Thinking.
Validate and enforce consistent markdown document structure, including YAML frontmatter positioning, correct heading hierarchy, and logical content organization for Obsidian vaults.
AI-native product management tool for startups. Features automated competitor research, gap analysis using the WINNING filter, PRD generation, and GitHub Issues integration for prioritized, signal-based roadmap planning.
Token-efficient codebase navigation through intelligent symbol indexing, domain chunking, and architectural layer filtering. Reduce token usage by 60-95% when exploring or developing complex systems.