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

With no annotations, the description carries the full burden. It discloses the output (URL, 1200x630, no login), the indicative nature of position/scale, and even instructs the agent to say so when showing the image. It does not cover edge cases such as invalid logo URLs or error behavior, but the core behavioral profile is clear.

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 the core purpose and each sentence serves a distinct function: purpose, inputs, output characteristics, limitation, and usage context. There is no filler.

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 tool with no output schema, the description adequately compensates by describing the return value and its properties. It also tells the agent when to invoke it and what to communicate to the buyer. Minor gaps, such as failure modes or error handling, prevent a 5.

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 the parameters are already well documented. The description reinforces slug and logo_url but adds no new meaning for company_name or for behavior when logo_url is omitted; baseline 3 is appropriate.

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+resource: 'Render an indicative placement image showing a buyer their logo on a product, and return its URL.' It clearly distinguishes itself from siblings by framing this as an indicative preview, not a production proof.

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 gives explicit when-to-use context: 'Use after search_products or get_product, once a buyer wants to see how something would look' and an explicit when-not: this is NOT a production proof. However, it does not name an alternative sibling tool for production proofs, only 'the desk issues the real one.'

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