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Found 84 Skills
Manage and query Agent Platform RAG Engine Corpora and retrieve grounded contexts using the Google GenAI SDK. Use when listing RAG corpora or files, inspecting a corpus, retrieving contexts, or generating content grounded in a RAG corpus. Do not use for standard database queries (use SQL/Spanner skills), Google Workspace RAG, or other RAG products like gRAG.
Manages and orchestrates prompts in Agent Platform. Use when you need to create, list, retrieve, version, or delete managed prompts in Agent Platform. Don't use for model training, model deployment to endpoints, or managing non-Agent Platform prompts.
List available large language models and send chat completion requests programmatically. Use this skill when you need to call an LLM within a snippet, including model comparison, visual understanding, batch inference, and model performance testing.
Create new AI chat interface components for the ai-elements library following established composable patterns, shadcn/ui integration, and Vercel AI SDK conventions. Use when creating new components in packages/elements/src or when the user asks to add a new component to ai-elements.
Guide for assistant-cloud persistence and authorization. Use when setting up thread persistence, file uploads, or authentication.
Vercel AI platform guidance covering AI SDK, AI Gateway, Vercel Agent, and MCP. Use when building AI-powered or agentic workloads on Vercel.
Design patterns for building AI-powered interfaces like chatbots and intelligent assistants in React.
Guides the usage of the Gemini API on Agent Platform with the Google Gen AI SDK. Use when the user asks about using Gemini in an enterprise environment or explicitly mentions Vertex AI, Google Cloud, or Agent Platform. Covers SDK usage (Python, JS/TS, Go, Java, C#), capabilities like Live API, tools, multimedia generation, caching, and batch prediction.
Vercel and Next.js deployment best practices including server components, edge functions, AI SDK integration, and performance optimization.
Migrate an application with hardcoded LLM prompts to a full LaunchDarkly AI Configs implementation in five stages: extract prompts, wrap in the AI SDK, add tools, add tracking, add evals/judges. Use when the user wants to externalize model/prompt configuration, move from direct provider calls (OpenAI, Anthropic, Bedrock, Gemini) to a managed AI Config, or stage a full hardcoded-to-LaunchDarkly migration.
Scaffolds evaluation suites for the Axiom AI SDK. Generates eval files, scorers, flag schemas, and config from natural-language descriptions. Use when creating evals, writing scorers, setting up flag schemas, or configuring axiom.config.ts.
Comprehensive guide for building AI agents that interact with Solana blockchain using SendAI's Solana Agent Kit. Covers 60+ actions, LangChain/Vercel AI integration, MCP server setup, and autonomous agent patterns.