Create a product from image URLs

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

The description reveals asynchronous behavior: it returns product_id immediately, downloads happen in the background, and the first video-direction draft runs later. It also discloses important constraints and side effects—public URLs only, 8MB skip limit, at most 9 images used, and no credit consumption—adding real behavioral context beyond the 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?

The description is front-loaded with purpose and contains no filler. It is somewhat long with multiple paragraphs, but each paragraph adds operational value—async behavior, polling instructions, alternative tool guidance, and credit semantics—so the length is justified, if not perfectly tight.

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 creation tool with no output schema, the description covers the full invocation picture: what inputs are needed, what happens on success, how to track progress, when to prefer an alternative, and cost implications. An agent has everything needed to call this tool correctly and interpret the immediate result.

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%, so the schema already documents all parameters. The description adds meaningful parameter-related constraints, especially for image_urls: they must be publicly reachable, cannot come from the caller's machine, images over 8MB are skipped, and at most 9 are used. This goes beyond the schema's 'Publicly reachable image URLs, most representative first' and earns more than the baseline 3.

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 opens with a specific verb and resource: 'Start a new InstantClips product from hosted product photos', and adds a precise scope condition ('for a product that has no public page to scrape'). It clearly distinguishes itself from import_product_from_url by naming what this tool is not for, so an agent can select it confidently.

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 description explicitly says to prefer import_product_from_url when a product page exists, and explains why: the scrape collects name, description, price, and brand identity for a better direction draft. It also gives lifecycle guidance: poll get_product until import_status is 'imported', making the tool's role in the workflow unmistakable.

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