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Found 14 Skills
INVOKE THIS SKILL when creating, reading, updating, or deleting Arize AI integrations. Covers listing integrations, creating integrations for any supported LLM provider (OpenAI, Anthropic, Azure OpenAI, AWS Bedrock, Vertex AI, Gemini, NVIDIA NIM, custom), updating credentials or metadata, and deleting integrations using the ax CLI.
Use this skill when integrating a third-party auth provider (Clerk, Auth0, WorkOS, Kinde, Stytch) with InsForge for authentication and RLS. Covers JWT configuration, client setup, database RLS policies, and provider-specific gotchas for each supported integration.
Use when building a custom provider integration on top of @prefactor/core so your app can instrument agent, llm, and tool workflows without relying on a prebuilt adapter package.
Use when choosing which Prefactor SDK skill to load for agent instrumentation or for building a custom provider integration on top of @prefactor/core.
AI image generation with OpenAI, Azure OpenAI, Google, OpenRouter, DashScope, MiniMax, Jimeng, Seedream and Replicate APIs. Supports text-to-image, reference images, aspect ratios, and batch generation from saved prompt files. Sequential by default; use batch parallel generation when the user already has multiple prompts or wants stable multi-image throughput. Use when user asks to generate, create, or draw images.
Guide for adding new AI provider packages to the AI SDK. Use when creating a new @ai-sdk/<provider> package to integrate an AI service into the SDK.
Complete guide for integrating a new LLM backend into MassGen. Use when adding a new provider (e.g., Codex, Mistral, DeepSeek) or when auditing an existing backend for missing integration points. Covers all ~15 files that need touching.
Answer questions about the AI SDK and help build AI-powered features. Use when developers: (1) Ask about AI SDK functions like generateText, streamText, ToolLoopAgent, or tools, (2) Want to build AI agents, chatbots, or text generation features, (3) Have questions about AI providers (OpenAI, Anthropic, etc.), streaming, tool calling, or structured output.
Develop examples for AI SDK functions. Use when creating, running, or modifying examples under examples/ai-functions/src to validate provider support, demonstrate features, or create test fixtures.
Integration patterns and best practices for adding persistent memory to LLM agents using the Letta Learning SDK
Better environment variable management for agents and humans with full type safety, CLI-based remote environment synchronization, and environment validation. Use when setting up typed config schemas, validating env variables, or managing remote env vars across Vercel, Netlify, Railway, Cloudflare, and Fly.io with better-env.
Comprehensive operational knowledge for ZeroClaw, the fast, small, fully autonomous AI assistant infrastructure built in Rust. Covers CLI, 30 providers, 14 channels, config, hardware, deployment, and security.