Atlas / Skills / composiohq / Mistral Ai Automation

Mistral Ai AutomationSAFE

skills/composiohq/mistral-ai-automation

A curated list of awesome Claude Skills, resources, and tools for customizing Claude AI workflows

Verdict
SAFE
Grade
B
Trust score
89 /100
Version
—
Hosts
1 documented
License
—
Stars
76,843
01

Overview

A curated list of awesome Claude Skills, resources, and tools for customizing Claude AI workflows

Read from source at commit 661fa6b4bb7bOBSERVED · 2026-10-11
02

Host compatibility

What the documentation claims. We have not run a compatibility test.

HostStatusNotes
cursormentioned
03

What it tells the agent

The instruction file, verbatim from the audited commit — this is the text the model reads, and the surface the audit's instruction layer examines. Quoted here so you can judge it without cloning anything.

---
name: Mistral AI Automation
description: "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 Composio MCP integration."
requires:
  mcp:
    - rube
---

# 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:** [composio.dev/toolkits/mistral_ai](https://composio.dev/toolkits/mistral_ai)

---

## Setup

1. Add the Composio MCP server to your client: `https://rube.app/mcp`
2. Connect your Mistral AI account when prompted (API key authentication)
3. 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 |

---

*Powered by [Composio](https://composio.dev)*
04

Trust audit

SAFEgrade B · trust 89/100 Nothing in the source contradicts what it says it does. Grade A is reserved for packages that have also passed the behavioural sandbox.

LayerWhat it checksResult
L0Provenance & inventoryPASS
L1Static analysis of the codeNA
L2Instruction surface (what it tells the agent)PASS
L3Class-specific surfacePASS
L4Behavioural (sandbox)SKIPPED

What the source does

Filesystem
none-observed
Network
none-observed
Shell
none-observed
Dependencies
pinned
Secrets in source
none-found

Findings (0)

No findings outside the package's declared scope.

Gates applied: no_behavioural_pass.

Audited 2026-10-11 · audit v0.4.1 · source sha 661fa6b4bb7bfull audit observations/trust-audit/skill/composiohq__mistral-ai-automation.json · Report an issue / request a re-scan
05

Audit history

Every audit this skill has had.

DateSourceVerdictGradeScoreChange
2026-10-11661fa6b4bb7bSAFEB89first audit
06

Questions

What does the Mistral Ai Automation skill do?

A curated list of awesome Claude Skills, resources, and tools for customizing Claude AI workflows

Is Mistral Ai Automation safe to install?

The audit found nothing in the source that contradicts what it says it does, and graded it B (89/100). Grade A is held back for packages that have also passed a sandboxed behavioural run, which is why a clean skill reads B.

What can Mistral Ai Automation access on my machine?

The audit observed no filesystem, network or shell use at all in its source.

What do I need installed to use Mistral Ai Automation?

Its own instructions reference s3key. Dependencies are pinned to exact versions.

Which assistants does Mistral Ai Automation work with?

Its documentation mentions cursor. That is what the text claims, not a compatibility test we ran.

How current is this page?

The grade is for one exact copy of the source (661fa6b4bb7b), read on 2026-10-11. The repository is watched, and a new audit runs when it changes — this is the first audit.

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