optimization.solve

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

With no annotations, the description carries the full burden and does a decent job: sync blocks until completion, async returns immediately with run_id and status, and a repeated client_request_id returns the existing run rather than starting a duplicate. That idempotency disclosure is valuable. Missing are error semantics on an invalid problem, whether runs persist/can be cancelled, and any cost or rate-limit context.

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 short sentences, front-loaded with the core action, then branching behavior, then the idempotency caveat. Nothing restates the name or the schema, and every clause carries information an agent could act on.

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?

An output schema exists, so return values needn't be spelled out, and the async return shape is described anyway. For a tool whose single required parameter is a deeply nested problem spec with expression syntax, evaluator IDs, and budget/timeout knobs, the description leaves the agent without guidance on constructing a valid problem or on what happens when a budget is exhausted.

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 0%, so the description must compensate. It does well for execution_mode (whose schema has no enum, so the two accepted values and their meaning come entirely from the description) and client_request_id (explains the dedupe semantics). But the required `problem` object — variables, objective kind, constraints, budget, algorithm, evaluator_params — gets no semantic explanation at all, leaving the dominant payload documented only by structure.

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 opening sentence gives a specific verb and resource ("Run the optimization") and the body routes the async path to optimization.get_result, so the agent can tell it apart from that sibling. It does not, however, distinguish it from optimization.validate_problem or list_evaluators, which is the more likely confusion for a first-time caller.

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?

It clearly frames the sync-vs-async decision and the follow-up call needed in async mode, which is real usage guidance. It gives no when-not guidance, no prerequisite (e.g. validating the problem first, registering evaluators needed for kind="registered" objectives), and no statement about how expensive or long-running a call is.

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