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OpenAI Apps SDK / ChatGPT plugins (developers.openai.com/plugins) のリファレンス。 ChatGPT 内アプリを MCP サーバーとして公開する側の API。 window.openai, useOpenAiGlobal, registerAppTool, ui://widget, _meta, openai/outputTemplate, OAuth, plugin.json / mcp.json (Agent Plugins), MCP Events, Plugin Extensions, Checkout API, 接続テスト・審査・申請。
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将问题和选定的项目文件交给另一个AI模型，获取代码审查、故障调查或设计建议。可在执行前检查发送内容和令牌用量，并选择API或浏览器方式运行。
Design autonomous coding agents with patterns inspired by Cline and OpenAI Codex. Explore tool calling interfaces, permission and approval systems, browser automation, and workflows where people review or guide the agent's actions.
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Ask AI questions, generate code, and summarize text through 9Router using OpenAI or Anthropic request formats. Receive responses incrementally with streaming, and use provider combinations that automatically try another provider when needed.
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Build and troubleshoot ChatGPT apps with an MCP server that exposes tools and an optional interactive widget. Use current official documentation and examples to create scaffolds, configure security settings, and guide local validation and deployment when requested.
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Call Gemini and OpenMaaS models such as Llama, DeepSeek, and Qwen through Google Cloud Agent Platform. Prepare authentication and SDK code, run prompts, configure connection endpoints, and troubleshoot common request errors.
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Build, refactor, and troubleshoot ChatGPT apps with an MCP server, which exposes tools to the assistant, and an interactive widget. Use official documentation and examples to plan tools, scaffold code, configure security settings, and validate local operation.
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Query ProteomeXchange through its PROXI API to inspect datasets, libraries, proteins, peptide forms, and spectra. Receive concise summaries focused on a dataset or identifier, and save complete responses when more detail is needed.
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Retrieve HLA alleles, forms of HLA genes, and cell metadata from the public IPD API. Filter allele records by name, limit returned items, and receive concise summaries, with raw JSON or text available on request.
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Look up compound–target binding data in BindingDB using PDB or UniProt identifiers, or search for similar chemical structures. Receive concise summaries of matching records, with full API responses saved to a file when requested.
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Query the ChEMBL API for molecules, biological targets, activity records, and mechanisms of action. Search by text or look up an identifier, then receive concise summaries or JSON output when machine-readable results are needed.
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Retrieve public eQTL Catalogue association data, linking genes and genetic variants, along with study metadata. Filter requests to specific identifiers and receive concise Markdown summaries or raw JSON when machine-readable output is requested.
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Look up existing predictions and protein information in the AlphaFold Protein Structure Database. Retrieve concise structure metadata, UniProt summaries, sequence summaries, and annotations, with an option to save the full response for later inspection.
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Retrieve study, mutation, clinical, and sample data from cBioPortal and turn the results into concise summaries. Use it to browse studies, inspect molecular profiles, or look up mutations for specified genes.
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Generate character reference images from a short description, including full-body, face, side, and back views. Use one reference image to guide the set, regenerate individual views, and track versions and images that need updating.
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Guide for ingesting the latest OpenAI TypeSpec specification into the openai-dotnet SDK. Use this when asked to update or ingest OpenAI API specs, copy base TypeSpec files from upstream, fix client TSP compile errors, or run code generation for new API areas.
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千问AI平台（Qianwen AI Platform / DashScope）官方文档离线知识库，用于检索并回答模型选择、API Key、OpenAI 兼容接口、DashScope SDK、文本与多模态生成、图像/视频/语音、Realtime API、Embedding、Reranking、Function Calling、MCP、批量调用、计费、Token Plan、API/SDK/CLI 参考和模型更新等问题，也可基于官方文档生成示例代码与排障建议。当用户提到千问AI平台、Qianwen AI Platform、DashScope、通义千问 API、百炼 API、DASHSCOPE_API_KEY 或具体千问/万相模型接入时使用；千问聊天产品的一般使用、模型原理论文解读或无关的阿里云产品问题不使用。
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Generate diagrams, flowcharts, and conceptual illustrations using OpenAI gpt-image-2 (default) or gpt-image-1. Use for: algorithm/code flow diagrams, system architecture sketches, conceptual illustrations, and any figure that does NOT represent actual code execution output (data plots, model results, etc. must still be generated by running Python code). Requires OPENAI_API_KEY and OpenAI organization verification when used from Claude Code / API path. OpenAI Codex subscribers can use built-in $imagegen without an API key.
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Reference guide for connecting popular APIs to Home Assistant via Node-RED, YAML, or custom integrations. Covers authentication, endpoints, and complete working examples for: energy APIs (Tibber, Nordpool), weather (SMHI, OpenWeatherMap, yr.no), transport (SL, Trafikverket, Resrobot), smart home clouds (Shelly, Tuya, Philips Hue, IKEA), and global APIs (OpenAI, Spotify, Google Calendar, Telegram, GitHub). Use this skill whenever the user mentions a specific external service, API, or data source they want to connect to Home Assistant - even if they don't say "API".
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OpenAI API (developers.openai.com) の画像生成・画像入力リファレンス。 GPT Image 2.5 (`gpt-image-2.5-sunburst` / `flare`), Images API `images.generate` / `images.edit`, mask, reference images, quality xhigh / max, image prompting, image_generation tool (Responses API), vision (画像入力, detail, image tokens, cost calculator, vision fine-tuning)。 Sora 2 / Videos API は 2026-09-24 終了 (履歴のみ)。
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OpenAI API (developers.openai.com) の Responses API リファレンス。 text generation, embeddings, gpt-6-astra / gpt-6.1-sol / gpt-6-luna, structured outputs, streaming, function calling, programmatic / async tool calling, conversation state, prompt caching, prompt cache diagnostics, reasoning (configuration_update), background mode, compaction, multi-agent, WebSocket mode (mid-turn steering, stream_id), webhooks, error codes, rate limits, Realtime server controls, 公式 SDK (Python / JS / .NET / Java / Go / Ruby), openai CLI, Chat Completions / Assistants 移行, deprecations。
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Create character, scene, and product images from structured descriptions of style, composition, lighting, and color. Guide generation with reference images and aspect ratio settings, using a Python script connected to a supported image generation service.
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Set up Langfuse to record LLM application activity, costs, and response times. Manage prompt versions, organize evaluation datasets, and compare results to investigate failures and guide improvements using recorded evidence.
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Set up cognee and run a first Python example that stores information and retrieves it with a question. Covers virtual environments, API key configuration, optional packages, and basic troubleshooting.
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