openai_create_embedding

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

No annotations are provided, so the description should disclose behavioral traits. It only states 'create', implying mutation, but embeddings are typically read-only. It does not mention external API calls, rate limits, or that an API key is required. The single sentence is insufficient for behavioral transparency.

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 9 words, making it very concise. However, the brevity comes at the expense of completeness. It is front-loaded with the core purpose, but lacks structured detail.

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 has no output schema, so the description should explain return values (e.g., embedding vectors). It does not mention the format of the response (e.g., array of floats), nor does it address batch handling or how the input parameter is processed. Given the complexity of 5 parameters, the description is 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?

The schema description coverage is 60%, with descriptions for input, model, and dimensions, but none for api_key or org_id. The tool description adds no parameter-level information, leaving the purpose of the undocumented parameters unclear. It does not clarify that api_key is required for authentication.

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 the action ('Create') and resource ('vector embeddings'), and specifies the provider ('OpenAI embedding model'). This distinguishes it from similar sibling tools like mistral_create_embedding or togetherai_create_embedding, but does not elaborate further on the type of embeddings.

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?

The description provides no guidance on when to use this tool versus alternatives. It lacks information about prerequisites (e.g., API key setup), context for embedding use cases, or any mention of when not to use it.

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