Create Inference (v4)

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

Annotations already declare non-read-only, non-idempotent, and non-destructive behavior. The description adds the OpenAI Responses-API style context but no additional behavioral details such as streaming behavior, output format, or auth requirements. No contradictions with 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?

One short sentence, front-loaded with the verb and resource. No wasted words, and every part of the sentence contributes to understanding the tool's purpose.

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 16 parameters and several close siblings, but the description gives no guidance on selecting among them and no return-value context. It is minimally viable because the schema and annotations fill many gaps, but an agent is left guessing about usage boundaries.

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% and every parameter has a description. The description names the three primary parameters (model, input, tools), but this adds minimal value beyond what the schema already provides.

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 names the operation ('Create'), the resource ('v4 inference response'), and the API style ('OpenAI Responses-API'), making the core purpose clear. However, it does not distinguish this from the close sibling lyzr_create_response_v4, so it stops short of full differentiation.

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 when-to-use guidance, comparison to alternatives, or exclusions are provided. The description only restates the tool's purpose; an agent cannot tell when to choose this over lyzr_create_response_v4, lyzr_chat_completions_v4, or lyzr_chat.

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