mistral_list_models
Retrieve available Mistral AI models to identify which model fits your AI workflow.
Instructions
List all available Mistral AI models.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| api_key | No |
Retrieve available Mistral AI models to identify which model fits your AI workflow.
List all available Mistral AI models.
| Name | Required | Description | Default |
|---|---|---|---|
| api_key | No |
Changes observed during successful MCP inspections.
v0.1.9v0.1.5Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, openWorldHint, and destructiveHint=false. The description adds only 'all available,' which minimally clarifies scope but does not add behavioral context such as authentication needs, pagination, or return shape.
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?
A single front-loaded sentence with zero waste. It states the action and resource immediately and contains no redundant or filler text.
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?
The tool is simple and annotations cover safety, but with no output schema the description does not explain what the returned model list contains or how authentication is handled. It is adequate for a basic list operation but leaves minor gaps.
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?
There is one parameter, api_key, with 0% schema description coverage. The description does not mention authentication or explain the parameter, though the name is largely self-explanatory, preventing a lower score.
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?
The description gives a specific verb and resource: 'List' and 'Mistral AI models,' which clearly separates it from mistral_chat_completion and mistral_create_embedding. It does not explicitly distinguish itself from other providers' list_models tools beyond the provider name, so it falls short of a 5.
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?
It states what the tool does but gives no when-to-use or when-not-to-use guidance and names no alternatives. An agent must infer that this is for model discovery rather than chat or embeddings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.