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

Annotations already indicate mutation and non-idempotency, and the description adds useful behavioral context beyond those: the job persists under the active API key's organization and completion is delivered by outbound webhook when callback_url is set. It also clarifies the async nature and returns a job_id.

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?

Two dense sentences, front-loaded with the core action and the decisive usage threshold. Every clause adds value: usage trigger, return value, polling workflow, persistence, and webhook behavior. No filler or redundancy.

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 description covers the essential workflow: how to invoke, what is returned, how to get status, where the job is persisted, and callback behavior. It is missing guidance on what constitutes valid contents for the required 'variables' parameter, but otherwise the tool can be called and monitored with confidence.

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 only 25%, so the description must compensate. It adds meaning for n_simulations ('Use for n_simulations > 500,000') and callback_url ('completion is delivered to it by outbound webhook'). However, it does not clarify the required 'variables' array or the 'objective' parameter, which remain undocumented and are important to call the tool correctly.

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 a specific verb and resource: 'Submit a long-running async simulation job.' It distinguishes itself from the polling siblings by saying it 'Returns a job_id — poll with get_job_status,' and from synchronous simulation tools by emphasizing the async and long-running nature.

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?

Provides an explicit trigger for use: 'Use for n_simulations > 500,000 or when you need a callback.' This is actionable guidance, though it does not explicitly name an alternative tool for smaller jobs or cases without a callback, which would have made the routing fully explicit.

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