skeleton_rig_gltf_skin_validator

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions a cost of 0.040 USDC on Base L2, indicating a payment requirement, and lists the specific checks performed, implying a read-only audit. However, it does not explicitly state read-only nature, output format, error behavior, or preconditions. Some value is added, but gaps remain.

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 a single concise sentence that front-loads the core purpose and lists specific checks, followed by the cost information. There is no wasted wording, and the structure is efficient.

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 specialized nature of the tool, lack of output schema, and no annotations, the description does not specify the return value format (e.g., report, JSON), the exact structure of the 'payload' input, or any preconditions. This leaves the agent uncertain about how to interpret results or construct input, making it incomplete.

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% as both parameters (payload and paymentSignature) have descriptions in the schema. The tool description adds no additional parameter-specific meaning beyond what the schema already provides, so the baseline of 3 applies.

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 'Audits' and a specific resource 'glTF skeletal skinning data', and lists three concrete checks: non-normalized joint weights (>1.0), missing inverse bind matrices, and cyclic joint hierarchy loops. This clearly distinguishes it from sibling tools like validate_gltf_structure, which likely validates overall glTF structure.

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 implies usage for glTF skinning validation but does not explicitly state when to use this tool versus alternatives such as validate_gltf_structure. There are no exclusions or references to other tools, so the agent must infer applicability from the described checks.

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