depth_anything_disparity_normalizer

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

With no annotations provided, the description carries the full burden and does disclose the core transformation and the specific artifacts eliminated, which is meaningful behavioral detail. However, it does not describe output format, failure behavior, state changes, or whether the input is modified, and the pricing note is useful but not a behavioral trait.

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 two sentences with no wasted words: the core operation is front-loaded, the artifact types are specified, and the pricing is cleanly parenthesized. It is compact yet information-dense, appropriate for the technical domain.

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?

There is no output schema, and the only parameter documentation is generic, so an agent still cannot determine the exact payload shape or what the normalized result will look like. The description explains the tool's purpose and cost, but not the full call contract needed for a correct invocation. This is a significant gap for a paid processing tool.

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 baseline is 3, but the payload description is generic ('Input parameters or JSON string payload') and gives little real semantic value. The tool description hints that the payload relates to disparity depth maps, but it does not specify required JSON fields, encodings, or formats, and paymentSignature is only explained in the schema.

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 operation (normalizes), a specific input class (raw affine-invariant and metric disparity depth maps), and the concrete artifacts it removes (infinity bleeding and boundary halo artifacts) before 3D reprojection. This clearly distinguishes it from sibling tools like depth_to_normal_map_generator, which transforms depth into normal maps rather than normalizing disparity.

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 phrase 'before 3D reprojection' gives the agent an explicit pipeline context for when to use this tool, and the description clarifies the accepted input state (raw affine-invariant and metric disparity depth maps). It does not name alternative tools or exclusion scenarios, but the usage context is clear enough for selection.

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