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

Annotations only provide destructiveHint=true, so the description carries most of the burden — and it does: it discloses the async task pattern, the return value (task_key), and concrete rate limits, which are real operational constraints. It doesn't explain pricing/quota consumption or what happens if the task is never polled, but the essential behavior is covered.

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 sentence, front-loaded with the action, then the follow-up call, then the constraint, with the API endpoint appended. Dense and largely waste-free, though the trailing 'Printful: POST /mockup-generator/create-task/{id}' is marginally useful for agents that reason about endpoints.

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?

For a 10-parameter nested async tool with no output schema, the description supplies the critical missing piece: the return value (task_key) and the polling follow-up. The remaining detail lives in the well-covered schema, so an agent has what it needs to call and complete the workflow.

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% with 10 parameters fully documented (files vs product_template_id, store_id token semantics, width bounds, formats), so the schema does the heavy lifting and a baseline 3 applies. The description adds only the loose phrase 'for a design on a catalog product' and contributes no parameter-level detail beyond it.

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+resource ('Start generating product mockups for a design on a catalog product') and immediately names the polling sibling printful_get_mockup_task, so it is distinguishable from every other tool in the sibling list.

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?

Explicitly tells the agent what to do next ('poll printful_get_mockup_task for the images') and flags the rate-limit regime (10/min established, 2/min new), which shapes when it's safe to call. It stops short of stating when this tool is the wrong choice versus, e.g., using a product template directly, but the workflow guidance is clear.

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