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Automate Mistral AI tasks via Rube MCP (Composio): completions, embeddings, fine-tuning, and model management. Always search tools first for current schemas.
Passed 15 of 18 test cases with the skill, and 6 of 18 without it.
and 11 more in the full report
11 fixed7 passed either way4 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 10 test cases the skill fixed. Same model, same prompt, with and without the skill.
When calling RUBE_MULTI_EXECUTE_TOOL for standard lightweight chat completion tasks, what default setting should be passed for sync_response_to_workbench unless bulk processing is required?
| Checked | Without skill | With skill |
|---|---|---|
| Specifies setting sync_response_to_workbench to false. | Missed | Passed |
The instructions your model reads when the skill loads.
Automate Mistral AI operations through Composio's Mistral AI toolkit via Rube MCP.
Toolkit docs: composio.dev/toolkits/mistral_ai
RUBE_MANAGE_CONNECTIONS with toolkit mistral_aiRUBE_SEARCH_TOOLS first to get current tool schemasGet Rube MCP: Add https://rube.app/mcp as an MCP server in your client configuration. No API keys needed — just add the endpoint and it works.
RUBE_SEARCH_TOOLS respondsRUBE_MANAGE_CONNECTIONS with toolkit mistral_aiAlways discover available tools before executing workflows:
RUBE_SEARCH_TOOLS: queries=[{"use_case": "completions, embeddings, fine-tuning, and model management", "known_fields": ""}]
This returns:
test cases passed, vs 6 / 18 without
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