post-segment-inferences

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions that the process 'creates a new Asset,' implying a write operation, but does not specify permissions, rate limits, error handling, or the nature of the output (e.g., format, size). This leaves significant gaps in understanding the tool's behavior beyond basic functionality.

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 concise and front-loaded, consisting of two clear sentences that state the action and outcome without unnecessary details. It efficiently communicates the core purpose, though it could be slightly more structured by including key usage notes.

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?

Given the tool's complexity (13 parameters, no output schema, no annotations), the description is inadequate. It lacks details on output format, error conditions, performance characteristics, and how parameters affect the segmentation process. This makes it incomplete for effective agent use in a rich context.

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 description does not add any parameter-specific information beyond what the input schema provides. With a schema description coverage of 77%, the baseline is 3, as the schema documents most parameters adequately. The description fails to compensate for the 23% gap or provide additional context on parameter interactions.

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 the action ('Trigger the segmentation of an image') and the outcome ('create a new Asset with the segmentation mask as a child'), making the purpose specific and understandable. However, it does not explicitly differentiate from sibling tools like 'post-remove-background-inferences' or 'post-detect-inferences', which might also involve image processing, so it misses full sibling distinction.

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 provides no guidance on when to use this tool versus alternatives, such as other image processing tools in the sibling list. It lacks context on prerequisites, use cases, or exclusions, leaving the agent without clear usage instructions.

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