mistral_get_modelRetrieve details for a single model (base or fine-tuned). Management API: GET /v1/models/{model_id}.
| Name | Required | Description | Default |
|---|---|---|---|
| model_id | Yes | The model id, e.g. mistral-large-latest or a fine-tuned model id. |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint=true. Description adds endpoint and model scope, but no additional behavioral traits (e.g., rate limits, authentication).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with purpose, efficient and no waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Simple tool with one parameter and no output schema; description lacks specific return details but is adequate for a basic get operation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with a clear description of model_id. Description does not add new parameter information beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states verb 'Retrieve details' and resource 'single model', and distinguishes from sibling 'list_models' by specifying single model.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Implied usage from description ('single model') but no explicit when-to-use or alternatives compared to list_models.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool targets a distinct resource and action (e.g., cancel batch job, create agent, delete file, list agents) with no functional overlap. The descriptions clearly differentiate the purposes.
All tools follow the consistent 'mistral_verb_noun' pattern, with verbs like cancel, create, delete, get, list. The singular/plural noun usage is standard and predictable.
15 tools is well-scoped for a management API covering agents, batch jobs, files, libraries, and models. It is neither too few nor too many for the apparent domain.
The tool set provides basic read and some write operations, but lacks updates for agents and libraries, and does not allow creating batch jobs or libraries. This creates notable gaps for full lifecycle management.