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Found 248 Skills
Gemini 3 Pro API/SDK integration for text generation, reasoning, and chat. Covers setup, authentication, thinking levels, streaming, and production deployment. Use when working with Gemini 3 Pro API, Python SDK, Node.js SDK, text generation, chat applications, or advanced reasoning tasks.
Spatial indexing and world streaming for Three.js building games with thousands of pieces. Use when optimizing building games, implementing spatial queries, chunk loading, or profiling performance. Includes spatial hash grids, octrees, chunk managers, and benchmarking tools.
This skill provides project-specific coding conventions, architectural principles, repository structure standards, testing patterns, and contribution guidelines for the better-chatbot project (https://github.com/cgoinglove/better-chatbot). Use this skill when contributing to or working with better-chatbot to understand the design philosophy and ensure code follows established patterns. Includes: API architecture deep-dive, three-tier tool system (MCP/Workflow/Default), component design patterns, database repository patterns, architectural principles (progressive enhancement, defensive programming, streaming-first), practical templates for adding features (tools, routes, repositories). Use when: working in better-chatbot repository, contributing features/fixes, understanding architectural decisions, following server action validators, implementing tools/workflows, setting up Playwright tests, adding API routes, designing database queries, building UI components, handling multi-AI provider integration Keywords: better-chatbot, chatbot contribution, better-chatbot standards, chatbot development, AI chatbot patterns, API architecture, three-tier tool system, repository pattern, progressive enhancement, defensive programming, streaming-first, compound component pattern, Next.js chatbot, Vercel AI SDK chatbot, MCP tools, workflow builder, server action validators, tool abstraction, DAG workflows, shared business logic, safe() wrapper, tool lifecycle
Use this skill when building AI applications with OpenAI Agents SDK for JavaScript/TypeScript. The skill covers both text-based agents and realtime voice agents, including multi-agent workflows (handoffs), tools with Zod schemas, input/output guardrails, structured outputs, streaming, human-in-the-loop patterns, and framework integrations for Cloudflare Workers, Next.js, and React. It prevents 9+ common errors including Zod schema type errors, MCP tracing failures, infinite loops, tool call failures, and schema mismatches. The skill includes comprehensive templates for all agent types, error handling patterns, and debugging strategies. Keywords: OpenAI Agents SDK, @openai/agents, @openai/agents-realtime, openai agents javascript, openai agents typescript, text agents, voice agents, realtime agents, multi-agent workflows, agent handoffs, agent tools, zod schemas agents, structured outputs agents, agent streaming, agent guardrails, input guardrails, output guardrails, human-in-the-loop, cloudflare workers agents, nextjs openai agents, react openai agents, hono agents, agent debugging, Zod schema type error, MCP tracing failure, agent infinite loop, tool call failures, schema mismatch agents
Complete guide for OpenAI's Assistants API v2: stateful conversational AI with built-in tools (Code Interpreter, File Search, Function Calling), vector stores for RAG (up to 10,000 files), thread/run lifecycle management, and streaming patterns. Both Node.js SDK and fetch approaches. ⚠️ DEPRECATION NOTICE: OpenAI plans to sunset Assistants API in H1 2026 in favor of Responses API. This skill remains valuable for existing apps and migration planning. Use when: building stateful chatbots with OpenAI, implementing RAG with vector stores, executing Python code with Code Interpreter, using file search for document Q&A, managing conversation threads, streaming assistant responses, or encountering errors like "thread already has active run", vector store indexing delays, run polling timeouts, or file upload issues. Keywords: openai assistants, assistants api, openai threads, openai runs, code interpreter assistant, file search openai, vector store openai, openai rag, assistant streaming, thread persistence, stateful chatbot, thread already has active run, run status polling, vector store error
Backend AI functionality with Vercel AI SDK v5 - text generation, structured output with Zod, tool calling, and agents. Multi-provider support for OpenAI, Anthropic, Google, and Cloudflare Workers AI. Use when: implementing server-side AI features, generating text/chat completions, creating structured AI outputs with Zod schemas, building AI agents with tools, streaming AI responses, integrating OpenAI/Anthropic/Google/Cloudflare providers, or encountering AI SDK errors like AI_APICallError, AI_NoObjectGeneratedError, streaming failures, or worker startup limits. Keywords: ai sdk core, vercel ai sdk, generateText, streamText, generateObject, streamObject, ai sdk node, ai sdk server, zod ai schema, ai tools calling, ai agent class, openai sdk, anthropic sdk, google gemini sdk, workers-ai-provider, ai streaming backend, multi-provider ai, ai sdk errors, AI_APICallError, AI_NoObjectGeneratedError, streamText fails, worker startup limit ai
Complete guide for Google Gemini API using the CORRECT current SDK (@google/genai v1.27+, NOT the deprecated @google/generative-ai). Covers text generation, multimodal inputs (text + images + video + audio + PDFs), function calling, thinking mode, streaming, and system instructions with accurate 2025 model information (Gemini 2.5 Pro/Flash/Flash-Lite with 1M input tokens, NOT 2M). Use when: integrating Gemini API, implementing multimodal AI applications, using thinking mode for complex reasoning, function calling with parallel execution, streaming responses, deploying to Cloudflare Workers, building chat applications, or encountering SDK deprecation warnings, context window errors, model not found errors, function calling failures, or multimodal format errors. Keywords: gemini api, @google/genai, gemini-2.5-pro, gemini-2.5-flash, gemini-2.5-flash-lite, multimodal gemini, thinking mode, google ai, genai sdk, function calling gemini, streaming gemini, gemini vision, gemini video, gemini audio, gemini pdf, system instructions, multi-turn chat, DEPRECATED @google/generative-ai, gemini context window, gemini models 2025, gemini 1m tokens, gemini tool use, parallel function calling, compositional function calling
Use this skill for Next.js App Router patterns, Server Components, Server Actions, Cache Components, and framework-level optimizations. Covers Next.js 16 breaking changes including async params, proxy.ts migration, Cache Components with "use cache", and React 19.2 integration. For deploying to Cloudflare Workers, use the cloudflare-nextjs skill instead. This skill is deployment-agnostic and works with Vercel, AWS, self-hosted, or any platform. Keywords: Next.js 16, Next.js App Router, Next.js Pages Router, Server Components, React Server Components, Server Actions, Cache Components, use cache, Next.js 16 breaking changes, async params nextjs, proxy.ts migration, React 19.2, Next.js metadata, Next.js SEO, generateMetadata, static generation, dynamic rendering, streaming SSR, Suspense, parallel routes, intercepting routes, route groups, Next.js middleware, Next.js API routes, Route Handlers, revalidatePath, revalidateTag, next/navigation, useSearchParams, turbopack, next.config
Complete knowledge domain for Cloudflare Workers AI - Run AI models on serverless GPUs across Cloudflare's global network. Use when: implementing AI inference on Workers, running LLM models, generating text/images with AI, configuring Workers AI bindings, implementing AI streaming, using AI Gateway, integrating with embeddings/RAG systems, or encountering "AI_ERROR", rate limit errors, model not found, token limit exceeded, or neurons exceeded errors. Keywords: workers ai, cloudflare ai, ai bindings, llm workers, @cf/meta/llama, workers ai models, ai inference, cloudflare llm, ai streaming, text generation ai, ai embeddings, image generation ai, workers ai rag, ai gateway, llama workers, flux image generation, stable diffusion workers, vision models ai, ai chat completion, AI_ERROR, rate limit ai, model not found, token limit exceeded, neurons exceeded, ai quota exceeded, streaming failed, model unavailable, workers ai hono, ai gateway workers, vercel ai sdk workers, openai compatible workers, workers ai vectorize
Complete guide for OpenAI's traditional/stateless APIs: Chat Completions (GPT-5, GPT-4o), Embeddings, Images (DALL-E 3), Audio (Whisper + TTS), and Moderation. Includes both Node.js SDK and fetch-based approaches for maximum compatibility. Use when: integrating OpenAI APIs, implementing chat completions with GPT-5/GPT-4o, generating text with streaming, using function calling/tools, creating structured outputs with JSON schemas, implementing embeddings for RAG, generating images with DALL-E 3, transcribing audio with Whisper, synthesizing speech with TTS, moderating content, deploying to Cloudflare Workers, or encountering errors like rate limits (429), invalid API keys (401), function calling failures, streaming parse errors, embeddings dimension mismatches, or token limit exceeded. Keywords: openai api, chat completions, gpt-5, gpt-5-mini, gpt-5-nano, gpt-4o, gpt-4-turbo, openai sdk, openai streaming, function calling, structured output, json schema, openai embeddings, text-embedding-3, dall-e-3, image generation, whisper api, openai tts, text-to-speech, moderation api, openai fetch, cloudflare workers openai, openai rate limit, openai 429, reasoning_effort, verbosity
Use when designing animations for gaming apps, streaming platforms, entertainment portals, or interactive media
CRITICAL: Use for MolyKit AI chat toolkit. Triggers on: BotClient, OpenAI, SSE streaming, AI chat, molykit, PlatformSend, spawn(), ThreadToken, cross-platform async, Chat widget, Messages, PromptInput, Avatar, LLM