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Create Batch Job

mistral_create_batch_job

Submit a batch processing job to Mistral AI using specified model, input file IDs, and endpoint, enabling efficient asynchronous processing of large request volumes.

Instructions

Create a new batch processing job.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modelYesModel
endpointYesEndpoint
metadataNoMetadata
input_filesYesInput file IDs

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

C2.8/5.0
Behavior2/5

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

Annotations already declare this as a non-destructive, non-idempotent mutation (readOnlyHint=false, idempotentHint=false). The description adds nothing beyond that: it does not explain that repeated calls create duplicate jobs (the practical meaning of non-idempotent) or that the job runs asynchronously. With annotations carrying the safety profile, the description still leaves behavioral gaps.

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

Conciseness3/5

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

It is a single short sentence, which is efficient, but it is essentially a restatement of the title and adds almost no information. Brevity here reflects under-specification rather than disciplined conciseness.

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 create tool involving file IDs, a nested metadata object, and an endpoint enum, with no output schema, the description should explain what a batch job does and what it returns. It provides none of this, leaving an agent without enough context to invoke it confidently.

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 all four parameters (model, endpoint, input_files, metadata) are already documented in the schema. The description adds no meaning beyond the schema, which is the expected baseline when the schema does the heavy lifting.

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

Purpose4/5

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

The description states a specific verb and resource ('Create a new batch processing job'), which is clearer than the title alone. However, it offers no differentiation from sibling creation tools like create_fine_tuning_job or create_agent, so an agent must rely on the name to disambiguate.

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

Usage Guidelines2/5

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

There is no guidance on when to use this tool versus alternatives such as create_fine_tuning_job, nor any prerequisites (e.g., that input files must already be uploaded via upload_file). The agent is left to infer the entire usage context.

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