jpskill.com
💼 ビジネス コミュニティ 🟡 少し慣れが必要 👤 経営者・事業責任者・マーケ

💼 Replicate Automation

Replicate Automation

ReplicateのAIモデルを使った予測実行やファイルアップロード

⏱ 求人原稿の改善 半日 → 15分

📺 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 Replicate AI model operations -- run predictions, upload files, inspect model schemas, list versions, and manage prediction history via the Composio MCP integration.

🇯🇵 日本人クリエイター向け解説

一言でいうと

ReplicateのAIモデルを使った予測実行やファイルアップロード

※ 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. 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. 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. 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\

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

  • Replicate Automation で、私のビジネスを分析して改善案を3つ提案して
  • Replicate Automation を使って、来週の会議用の資料を作って
  • Replicate 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。

Replicate Automation

Automate your Replicate AI model workflows -- run predictions on any public model (image generation, LLMs, audio, video), upload input files, inspect model schemas and documentation, list model versions, and track prediction history.

Toolkit docs: composio.dev/toolkits/replicate


Setup

  1. Add the Composio MCP server to your client: https://rube.app/mcp
  2. Connect your Replicate account when prompted (API token authentication)
  3. Start using the workflows below

Core Workflows

1. Get Model Details and Schema

Use REPLICATE_MODELS_GET to inspect a model's input/output schema before running predictions.

Tool: REPLICATE_MODELS_GET
Inputs:
  - model_owner: string (required) -- e.g., "meta", "black-forest-labs", "stability-ai"
  - model_name: string (required) -- e.g., "meta-llama-3-8b-instruct", "flux-1.1-pro"

Important: Each model has unique input keys and types. Always check the openapi_schema from this response before constructing prediction inputs.

2. Run a Prediction

Use REPLICATE_MODELS_PREDICTIONS_CREATE to run inference on any model with optional synchronous waiting and webhooks.

Tool: REPLICATE_MODELS_PREDICTIONS_CREATE
Inputs:
  - model_owner: string (required) -- e.g., "meta", "black-forest-labs"
  - model_name: string (required) -- e.g., "flux-1.1-pro", "sdxl"
  - input: object (required) -- model-specific inputs, e.g., { "prompt": "A sunset over mountains" }
  - wait_for: integer (1-60 seconds, optional) -- synchronous wait for completion
  - cancel_after: string (optional) -- max execution time, e.g., "300s", "5m"
  - webhook: string (optional) -- HTTPS URL for async completion notifications
  - webhook_events_filter: array (optional) -- ["start", "output", "logs", "completed"]

Sync vs Async: Use wait_for (1-60s) for fast models. For long-running jobs, omit it and use webhooks or poll via REPLICATE_PREDICTIONS_LIST.

3. Upload Files for Model Input

Use REPLICATE_CREATE_FILE to upload images, documents, or other binary inputs that models need.

Tool: REPLICATE_CREATE_FILE
Inputs:
  - content: string (required) -- base64-encoded file content
  - filename: string (required) -- e.g., "input.png", "audio.wav" (max 255 bytes UTF-8)
  - content_type: string (default "application/octet-stream") -- MIME type
  - metadata: object (optional) -- custom JSON metadata

4. Read Model Documentation

Use REPLICATE_MODELS_README_GET to access a model's README in Markdown format for detailed usage instructions.

Tool: REPLICATE_MODELS_README_GET
Inputs:
  - model_owner: string (required)
  - model_name: string (required)

5. List Model Versions

Use REPLICATE_MODELS_VERSIONS_LIST to see all available versions of a model, sorted newest first.

Tool: REPLICATE_MODELS_VERSIONS_LIST
Inputs:
  - model_owner: string (required)
  - model_name: string (required)

6. Track Prediction History and Files

Use REPLICATE_PREDICTIONS_LIST to retrieve prediction history, and REPLICATE_FILES_GET/REPLICATE_FILES_LIST to manage uploaded files.

Tool: REPLICATE_PREDICTIONS_LIST
  - Lists all predictions for the authenticated user with pagination

Tool: REPLICATE_FILES_LIST
  - Lists uploaded files, most recent first

Tool: REPLICATE_FILES_GET
  - Get details of a specific file by ID

Known Pitfalls

Pitfall Detail
Model-specific input keys Each model has unique input keys and types. Using the wrong key causes validation errors. Always call REPLICATE_MODELS_GET first to check the openapi_schema.
File upload encoding REPLICATE_CREATE_FILE requires base64-encoded content. Binary files treated as text (UTF-8) will fail with decode errors.
Public vs deployment paths Public models must be run via REPLICATE_MODELS_PREDICTIONS_CREATE. Using deployment-oriented paths causes HTTP 404 failures.
Sync wait limits wait_for supports 1-60 seconds only. Long-running jobs need async handling via webhooks or polling REPLICATE_PREDICTIONS_LIST.
Image model constraints Image models like flux-1.1-pro have specific constraints (e.g., max width/height 1440px, valid aspect ratios). Check the model schema first.
Stale file references Heavy usage creates many uploads. Routinely check REPLICATE_FILES_LIST to avoid using stale file_id references.

Quick Reference

Tool Slug Description
REPLICATE_MODELS_GET Get model details, schema, and metadata
REPLICATE_MODELS_PREDICTIONS_CREATE Run a prediction on a model
REPLICATE_CREATE_FILE Upload a file for model input
REPLICATE_MODELS_README_GET Get model README documentation
REPLICATE_MODELS_VERSIONS_LIST List all versions of a model
REPLICATE_PREDICTIONS_LIST List prediction history with pagination
REPLICATE_FILES_LIST List uploaded files
REPLICATE_FILES_GET Get file details by ID

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