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List Fine-Tuning Jobs

mistral_list_fine_tuning_jobs
Read-onlyIdempotent

List and filter Mistral AI fine-tuning jobs by model, status, or creator to monitor training progress and manage runs.

Instructions

List fine-tuning jobs.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNoPage
modelNoFilter by model
statusNoFilter by status
page_sizeNoResults per page
created_by_meNoOnly my jobs

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

C2/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds nothing beyond that: no pagination behavior, no indication of default page size of 100 or the 100-item cap, no result ordering. With annotations carrying the load the bar is lower, but zero added context warrants a low score.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness2/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The single sentence is short and front-loaded, but it is under-specified rather than concise — it conveys no information an agent could not derive from the tool name. Brevity here costs utility.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a listing tool with five optional filter parameters and no output schema, the description omits filtering semantics, pagination expectations, and return shape. The structured fields carry everything; the description is not complete enough to guide correct invocation on its own.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the baseline of 3 applies — the schema documents page, model, status (with a full enum), page_size, and created_by_me. The description contributes no additional meaning, but it is not required to given full coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose2/5

Does the description clearly state what the tool does and how it differs from similar tools?

"List fine-tuning jobs." is essentially a restatement of the tool name and title with no additional specificity. It does state a verb and a resource, but it draws no distinction from siblings like mistral_list_models or mistral_list_batch_jobs beyond the resource noun embedded in the name itself.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines1/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no when-to-use guidance, no mention of alternatives (e.g., mistral_get_fine_tuning_job for a single job), and no note that the five filter parameters control the result set. An agent gets nothing about context or selection criteria.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.