💼 Open AI Automation
OpenAIのAPIを使って、テキストだけでなく画??
📺 まず動画で見る(YouTube)
▶ 【自動化】AIガチ勢の最新活用術6選がこれ1本で丸分かり!【ClaudeCode・AIエージェント・AI経営・Skills・MCP】 ↗
※ jpskill.com 編集部が参考用に選んだ動画です。動画の内容と Skill の挙動は厳密には一致しないことがあります。
📜 元の英語説明(参考)
Automate OpenAI API operations -- generate responses with multimodal and structured output support, create embeddings, generate images, and list models via the Composio MCP integration.
🇯🇵 日本人クリエイター向け解説
OpenAIのAPIを使って、テキストだけでなく画??
※ jpskill.com 編集部が日本のビジネス現場向けに補足した解説です。Skill本体の挙動とは独立した参考情報です。
⚠️ ダウンロード・利用は自己責任でお願いします。当サイトは内容・動作・安全性について責任を負いません。
🎯 このSkillでできること
下記の説明文を読むと、このSkillがあなたに何をしてくれるかが分かります。Claudeにこの分野の依頼をすると、自動で発動します。
📦 インストール方法 (3ステップ)
- 1. 上の「ダウンロード」ボタンを押して .skill ファイルを取得
- 2. ファイル名の拡張子を .skill から .zip に変えて展開(macは自動展開可)
- 3. 展開してできたフォルダを、ホームフォルダの
.claude/skills/に置く- · macOS / Linux:
~/.claude/skills/ - · Windows:
%USERPROFILE%\.claude\skills\
- · macOS / Linux:
Claude Code を再起動すれば完了。「このSkillを使って…」と話しかけなくても、関連する依頼で自動的に呼び出されます。
詳しい使い方ガイドを見る →- 最終更新
- 2026-05-17
- 取得日時
- 2026-05-17
- 同梱ファイル
- 1
💬 こう話しかけるだけ — サンプルプロンプト
- › OpenAI Automation で、私のビジネスを分析して改善案を3つ提案して
- › OpenAI Automation を使って、来週の会議用の資料を作って
- › OpenAI Automation で、現状の課題を整理してアクションプランに落として
これをClaude Code に貼るだけで、このSkillが自動発動します。
📖 Claude が読む原文 SKILL.md(中身を展開)
この本文は AI(Claude)が読むための原文(英語または中国語)です。日本語訳は順次追加中。
OpenAI Automation
Automate your OpenAI API workflows -- generate text with the Responses API (including multimodal image+text inputs and structured JSON outputs), create embeddings for search and clustering, generate images with DALL-E and GPT Image models, and list available models.
Toolkit docs: composio.dev/toolkits/openai
Setup
- Add the Composio MCP server to your client:
https://rube.app/mcp - Connect your OpenAI account when prompted (API key authentication)
- Start using the workflows below
Core Workflows
1. Generate a Response (Text, Multimodal, Structured)
Use OPENAI_CREATE_RESPONSE for one-shot model responses including text, image analysis, OCR, and structured JSON outputs.
Tool: OPENAI_CREATE_RESPONSE
Inputs:
- model: string (required) -- e.g., "gpt-5", "gpt-4o", "o3-mini"
- input: string | array (required)
Simple: "Explain quantum computing"
Multimodal: [
{ role: "user", content: [
{ type: "input_text", text: "What is in this image?" },
{ type: "input_image", image_url: { url: "https://..." } }
]}
]
- temperature: number (0-2, optional -- not supported with reasoning models)
- max_output_tokens: integer (optional)
- reasoning: { effort: "none" | "minimal" | "low" | "medium" | "high" }
- text: object (structured output config)
- format: { type: "json_schema", name: "...", schema: {...}, strict: true }
- tools: array (function, code_interpreter, file_search, web_search)
- tool_choice: "auto" | "none" | "required" | { type: "function", function: { name: "..." } }
- store: boolean (false to opt out of model distillation)
- stream: boolean
Structured output example: Set text.format to { type: "json_schema", name: "person", schema: { type: "object", properties: { name: { type: "string" }, age: { type: "integer" } }, required: ["name", "age"], additionalProperties: false }, strict: true }.
2. Create Embeddings
Use OPENAI_CREATE_EMBEDDINGS for vector search, clustering, recommendations, and RAG pipelines.
Tool: OPENAI_CREATE_EMBEDDINGS
Inputs:
- input: string | string[] | int[] | int[][] (required) -- max 8192 tokens, max 2048 items
- model: string (required) -- "text-embedding-3-small", "text-embedding-3-large", "text-embedding-ada-002"
- dimensions: integer (optional, only for text-embedding-3 and later)
- encoding_format: "float" | "base64" (default "float")
- user: string (optional, end-user ID for abuse monitoring)
3. Generate Images
Use OPENAI_CREATE_IMAGE to create images from text prompts using GPT Image or DALL-E models.
Tool: OPENAI_CREATE_IMAGE
Inputs:
- model: string (required) -- "gpt-image-1", "gpt-image-1.5", "dall-e-3", "dall-e-2"
- prompt: string (required) -- max 32000 chars (GPT Image), 4000 (DALL-E 3), 1000 (DALL-E 2)
- size: "1024x1024" | "1536x1024" | "1024x1536" | "auto" | "256x256" | "512x512" | "1792x1024" | "1024x1792"
- quality: "standard" | "hd" | "auto" | "high" | "medium" | "low"
- n: integer (1-10; DALL-E 3 supports n=1 only)
- background: "transparent" | "opaque" | "auto" (GPT Image models only)
- style: "vivid" | "natural" (DALL-E 3 only)
- user: string (optional)
4. List Available Models
Use OPENAI_LIST_MODELS to discover which models are accessible with your API key.
Tool: OPENAI_LIST_MODELS
Inputs: (none)
Known Pitfalls
| Pitfall | Detail |
|---|---|
| DALL-E deprecation | DALL-E 2 and DALL-E 3 are deprecated and will stop being supported on 05/12/2026. Prefer GPT Image models. |
| DALL-E 3 single image only | OPENAI_CREATE_IMAGE with DALL-E 3 only supports n=1. Use GPT Image models or DALL-E 2 for multiple images. |
| Token limits for embeddings | Input must not exceed 8192 tokens per item and 2048 items per batch for embedding models. |
| Reasoning model restrictions | temperature and top_p are not supported with reasoning models (o3-mini, etc.). Use reasoning.effort instead. |
| Structured output strict mode | When strict: true in json_schema format, ALL schema properties must be listed in the required array. |
| Prompt length varies by model | Image prompt max lengths differ: 32000 (GPT Image), 4000 (DALL-E 3), 1000 (DALL-E 2). |
Quick Reference
| Tool Slug | Description |
|---|---|
OPENAI_CREATE_RESPONSE |
Generate text/multimodal responses with structured output support |
OPENAI_CREATE_EMBEDDINGS |
Create text embeddings for search, clustering, and RAG |
OPENAI_CREATE_IMAGE |
Generate images from text prompts |
OPENAI_LIST_MODELS |
List all models available to your API key |
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