mistral_create_embedding

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

No annotations are present, and the description does not disclose behavioral traits such as rate limits, size constraints, authentication needs (though api_key parameter exists), or error handling. For a tool performing vector embedding, expected behaviors like output format or dimension are omitted.

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?

The description is a single sentence with no extraneous words. However, it is slightly under-specified for the task; it could benefit from stating that embeddings are returned as vectors.

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?

Given the lack of output schema, the description should mention return type (e.g., vector of floats) or dimensions. It does not, leaving the agent guessing about the result format. Simple tool but incomplete.

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 67% (2 of 3 parameters described). The description adds no extra meaning beyond the schema; 'input' and 'model' are already described. The undocumented 'api_key' parameter is not clarified, but the baseline is set at 3 due to moderate schema coverage.

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 clearly states 'Create vector embeddings for text using Mistral's embedding model.' It includes a specific verb (create), resource (vector embeddings), and provider (Mistral), which differentiates it from sibling tools like openai_create_embedding or cohere_embed.

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?

No guidance on when to use this tool versus alternatives. No when-to-use, when-not-to-use, or mention of preferred scenarios are provided. The description solely states what it does without context for selection.

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