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Found 398 Skills
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
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
Creates, configures, and updates Databricks Lakeflow Spark Declarative Pipelines (SDP/LDP) using serverless compute. Handles streaming tables, materialized views, CDC, SCD Type 2, and Auto Loader ingestion patterns. Use when building data pipelines, working with Delta Live Tables, ingesting streaming data, implementing change data capture, or when the user mentions SDP, LDP, DLT, Lakeflow pipelines, streaming tables, or bronze/silver/gold medallion architectures.
Build AI-first applications with RAG pipelines, embeddings, vector databases, agentic workflows, and LLM integration. Master prompt engineering, function calling, streaming responses, and cost optimization for 2025+ AI development.
Implement Server-Sent Events for real-time server-to-client updates. Use for live feeds, notifications, and streaming data.
Process substitution, named pipes (FIFOs), and advanced IPC patterns for efficient bash data streaming (2025)
Apply React Router 7 framework mode best practices including server-first data fetching, type-safe loaders/actions, proper hydration strategies, middleware authentication, handle metadata, useMatches/useRouteLoaderData hooks, and maximum type safety. Use when working with React Router 7 framework mode, implementing loaders, actions, route protection, breadcrumbs, streaming with Suspense/Await, URL search params, form validation, optimistic UI, resource routes (API endpoints), route configuration, or building SSR applications.
Manifold is a prediction market platform where users trade on the outcomes of real-world events using play-money (mana) and prize-cash. Use this skill to interact with the Manifold API for market discovery, trading, market creation, portfolio management, WebSocket streaming, and comments.
Use this skill to build, run, deploy, evaluate, and troubleshoot Go agents with Google's Agent Development Kit (`google.golang.org/adk`), including llmagent config, tools/integrations, callbacks/plugins, sessions/state/memory, workflows, streaming, MCP/A2A, and runtime/deployment patterns.
Anthropic Claude API patterns for Python and TypeScript. Covers Messages API, streaming, tool use, vision, extended thinking, batches, prompt caching, and Claude Agent SDK. Use when building applications with the Claude API or Anthropic SDKs.
FFmpeg-based 4-step video creation: Validate, Prepare, Encode, Verify. Use when user wants to combine a static image with audio to create an MP4 video, create a music video from cover art, or produce podcast/YouTube video from an image and audio file. Use for "image to video", "static video", "mp4 from image", "album art video", or "audio visualization". Do NOT use for video editing, live streaming, or generating images.
Build AI agents with Pydantic AI — tools, capabilities, structured output, streaming, testing, and multi-agent patterns. Use when the user mentions Pydantic AI, imports pydantic_ai, or asks to build an AI agent, add tools/capabilities, stream output, define agents from YAML, or test agent behavior.