A-Curated-List-of-Awesome-Claude-Skills Mistral AI Automation

Automate Mistral AI operations -- manage files and libraries, upload documents for fine-tuning, batch processing, and OCR, track fine-tuning jobs, and build RAG pipelines via the Claude Skill MCP integration.

install

source · Clone the upstream repo

git clone https://github.com/Engineer1999/A-Curated-List-of-Awesome-Claude-Skills

Claude Code · Install into ~/.claude/skills/

T=$(mktemp -d) && git clone --depth=1 https://github.com/Engineer1999/A-Curated-List-of-Awesome-Claude-Skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/app-automations/mistral-ai-automation" ~/.claude/skills/engineer1999-a-curated-list-of-awesome-claude-skills-mistral-ai-automation && rm -rf "$T"

manifest: app-automations/mistral-ai-automation/SKILL.md

source content

Mistral AI Automation

Automate your Mistral AI workflows -- upload files for fine-tuning, batch processing, and OCR, manage document libraries for RAG-enabled agents, list and retrieve files, track fine-tuning jobs, and integrate Mistral AI into cross-app data pipelines.

Toolkit docs: claude-skills.ai/toolkits/mistral_ai

Setup

Add the Claude Skill MCP server to your client:
```
https://rube.app/mcp
```
Connect your Mistral AI account when prompted (API key authentication)
Start using the workflows below

Core Workflows

1. Upload Files to Mistral AI

Use

MISTRAL_AI_UPLOAD_FILE

to upload files for fine-tuning, batch processing, or OCR.

Tool: MISTRAL_AI_UPLOAD_FILE
Inputs:
  - file: object (required)
    - name: string -- destination filename (e.g., "training_data.jsonl")
    - mimetype: string -- MIME type (e.g., "application/pdf", "application/jsonl")
    - s3key: string -- S3 key of a previously downloaded/stored file
  - purpose: "fine-tune" | "batch" | "ocr" (default "fine-tune")

Limits: Maximum file size is 512 MB. For fine-tuning, only

.jsonl

files are supported.

2. List and Retrieve Files

Use

MISTRAL_AI_LIST_FILES

to browse uploaded files with pagination, and

MISTRAL_AI_RETRIEVE_FILE

to get metadata for a specific file.

Tool: MISTRAL_AI_LIST_FILES
Inputs:
  - limit: integer (optional, min 1)
  - after: string (file ID cursor for next page)
  - order: "asc" | "desc" (default "desc")

Tool: MISTRAL_AI_RETRIEVE_FILE
Inputs:
  - file_id: string (required) -- UUID obtained from List Files

3. Create Document Libraries

Use

MISTRAL_AI_CREATE_LIBRARY

to group documents into libraries for use with RAG-enabled Mistral AI agents.

Tool: MISTRAL_AI_CREATE_LIBRARY
Inputs:
  - name: string (required) -- e.g., "Project Documents"
  - description: string (optional)

4. Upload Documents to a Library

Use

MISTRAL_AI_UPLOAD_LIBRARY_DOCUMENT

to add documents to a library for RAG retrieval by Mistral AI agents.

Tool: MISTRAL_AI_UPLOAD_LIBRARY_DOCUMENT
  - Requires library_id and file details
  - Call RUBE_GET_TOOL_SCHEMAS for full input schema before use

5. List Libraries and Download Files

Use

MISTRAL_AI_LIST_LIBRARIES

to discover available document libraries, and

MISTRAL_AI_DOWNLOAD_FILE

to retrieve file content.

Tool: MISTRAL_AI_LIST_LIBRARIES
  - Lists all document libraries with metadata (id, name, document counts)
  - Call RUBE_GET_TOOL_SCHEMAS for full input schema

Tool: MISTRAL_AI_DOWNLOAD_FILE
  - Downloads raw binary content of a previously uploaded file
  - Call RUBE_GET_TOOL_SCHEMAS for full input schema

6. Track Fine-Tuning Jobs

Use

MISTRAL_AI_GET_FINE_TUNING_JOBS

to list and filter fine-tuning jobs by model, status, and creation time.

Tool: MISTRAL_AI_GET_FINE_TUNING_JOBS
  - Supports filtering by model, status, creation time, and W&B integration
  - Call RUBE_GET_TOOL_SCHEMAS for full input schema

Known Pitfalls

Pitfall	Detail
Fine-tune file format	Only `.jsonl` files are supported for fine-tuning uploads. Other formats will be rejected.
File size limit	Maximum upload size is 512 MB per file.
File object structure	`MISTRAL_AI_UPLOAD_FILE` requires an `s3key` referencing a previously stored file, not raw binary content. Use a download action first to stage files in S3.
Pagination cursors	`MISTRAL_AI_LIST_FILES` uses cursor-based pagination via the `after` parameter (file ID). Continue fetching until no more results are returned.
Library document processing	Uploaded library documents are processed asynchronously. They may not be immediately available for RAG queries after upload.
Schema references	Several tools ( `MISTRAL_AI_UPLOAD_LIBRARY_DOCUMENT` , `MISTRAL_AI_LIST_LIBRARIES` , `MISTRAL_AI_GET_FINE_TUNING_JOBS` , `MISTRAL_AI_DOWNLOAD_FILE` ) require calling `RUBE_GET_TOOL_SCHEMAS` to load full input schemas before execution.

Quick Reference

Tool Slug	Description
`MISTRAL_AI_UPLOAD_FILE`	Upload files for fine-tuning, batch processing, or OCR
`MISTRAL_AI_LIST_FILES`	List uploaded files with pagination
`MISTRAL_AI_RETRIEVE_FILE`	Get metadata for a specific file by ID
`MISTRAL_AI_DOWNLOAD_FILE`	Download content of an uploaded file
`MISTRAL_AI_CREATE_LIBRARY`	Create a document library for RAG
`MISTRAL_AI_LIST_LIBRARIES`	List all document libraries with metadata
`MISTRAL_AI_UPLOAD_LIBRARY_DOCUMENT`	Add a document to a library for RAG
`MISTRAL_AI_GET_FINE_TUNING_JOBS`	List and filter fine-tuning jobs

Part of the Claude Skills Hub