Cutout Lab

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

The readOnlyHint annotation already tells the agent this is a non-mutating read, so the bar is lower. The description adds useful scoping context ('free', 'today', 'for the API key') but says nothing about reset timing, per-day vs rolling window, rate limits, or behavior when the quota hits zero.

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?

A single front-loaded sentence with the scope qualifiers ('free', 'today', 'API key') packed in and no filler. Every word constrains the meaning of the result.

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 zero-parameter read tool with readOnlyHint coverage, the description is nearly complete. Since there is no output schema, it would help to say what the response looks like (a count, plus whether a reset time is included), but the core return value is adequately conveyed.

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?

The tool takes zero parameters and the schema is an empty object, so there is nothing for the description to disambiguate. The baseline for a parameterless tool applies, with no param-related gaps to penalize.

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 names a specific verb and resource ('Return how many free remove_background calls remain') and scopes it to 'today' and 'for the API key'. Its relationship to the only sibling, remove_background, is clear from the wording – this reports quota rather than performing the operation – though it never states that contrast explicitly.

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?

Usage is only implied: an agent can infer this should be checked before spending calls on remove_background. There is no explicit when-to-use or when-not-to-use guidance, and no mention of what to do when the quota is exhausted.

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

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

The annotations already declare readOnlyHint and openWorldHint, so the safety profile is covered. The description adds useful behavioral context beyond that: the default transparent PNG output and the solid-colour subject output when bg_color is set, plus the exactly-one-input constraint.

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 sentences, front-loaded with the core action, followed by the input constraint and output behavior. There is no redundant or filler wording.

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?

With no output schema, the description appropriately explains the return format and the bg_color variant. It leaves minor details such as error behavior and how format interacts with transparency to the schema, which is acceptable for this tool's complexity.

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 high at 83%, so the baseline is 3. The description adds meaningful semantics not enforced by the schema: exactly one of image_url or image_base64 must be provided even though no parameters are required, and bg_color changes the output to a solid background.

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 states a specific verb and resource: remove the background from an image and return the cutout. It is immediately clear what the tool does and what it produces, with no ambiguity against the only sibling, get_quota.

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 a clear input-sourcing rule: provide exactly one of image_url or image_base64. There are no meaningful alternative tools to compare against, but it does not spell out when-not-to-use cases or failure conditions.

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