Mistral chat completion

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

Annotations already provide readOnlyHint=true and destructiveHint=false. Description adds that it returns structured content with assistant text and token usage, and does not stream, providing useful behavioral context beyond annotations.

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?

Four sentences, front-loaded with purpose, followed by usage guidelines and behavioral notes. No wasted words; every sentence adds value.

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?

Output schema exists, so description need not detail return values. It covers purpose, usage context, alternatives, and a behavioral note (no streaming). For a tool with 8 params, it is fairly complete but could mention that the model parameter affects capabilities (e.g., reasoning models).

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 description coverage is 63% (5 of 8 parameters have descriptions in schema). Description does not add parameter-level semantics beyond what schema provides; it focuses on output and usage. Baseline of 3 is appropriate.

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 'Generate a chat completion using a Mistral model' and distinguishes from siblings like Codestral for code and Ministral for cheap classification. Verb and resource are specific.

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?

Explicitly suggests when to use (French/European language tasks), when to use alternatives (Codestral for code, Ministral for classification), and warns against using for streaming, directing to a streaming variant.

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