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

Goes well beyond the lone destructiveHint=true: it discloses the async/non-blocking contract, the exact return payload shape, credit consumption, and the underlying queue POST semantics. It does not explain what makes the call 'destructive' or what auth the queue requires, but the side-effect and cost model are clearly surfaced.

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?

Three tight sentences with zero filler, front-loading the most decision-relevant fact (returns immediately) before the return shape and cost note.

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?

With no output schema, the description correctly enumerates the returned fields (request_id, response_url, status_url, cancel_url, queue_position) and covers cost and transport. It would be fully complete if it pointed at the polling/result siblings for the next step.

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 100%, so both parameters are already documented, including the note to use falai_get_model_schema for input fields. The description reinforces that model_id is used raw as a path segment and the body equals the model input, but adds no syntax or validation detail beyond the schema.

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?

States a specific verb and resource ('submit an inference request to the queue') and pins down the defining behavior: it returns immediately and does NOT wait for completion, which separates it from the synchronous sibling falai_run_model. It stops short of naming that sibling explicitly, so the differentiation is inferable rather than stated.

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 async framing implies the follow-up pattern of polling status and fetching results, but no sibling is named and no condition is given for choosing this over falai_run_model. The guidance is implied rather than explicit.

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