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

Annotations already declare readOnly, non-destructive, idempotent, and closed-world behavior. The description adds value beyond annotations by specifying that it does not execute untrusted code and that it returns a repaired draft, giving relevant security and output context. No contradiction with annotations.

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, with two sentences that front-load the core function and then add a critical safety note and pricing. Every sentence earns its place, and there is no redundant repetition of schema or annotation information.

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 parameters and strong annotations, the description covers the main functionality and return value ('repaired draft'), plus security and pricing context. It lacks details on error handling or edge cases, but given the simplicity, it is relatively complete. Without an output schema, describing the return as a 'repaired draft' is sufficient.

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 has zero parameters, so there is no parameter schema to clarify. Per the rubric, a baseline of 4 is appropriate for no parameters. The description does not need to explain parameter semantics, and the 100% schema coverage is trivial in this case.

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 uses a specific verb ('Normalize'), identifies the resource ('a supplied JSON Schema'), and states the core outcomes ('identify contradictions, and return a repaired draft'). This clearly distinguishes it from sibling tools like json-quality or structured-data-transform by focusing on schema repair rather than quality checks or data transforms.

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 repairing/normalizing JSON Schemas, and the safety note about not executing untrusted code suggests a specific context, but it does not explicitly state when to use it versus alternatives or provide any exclusions. The presence of sibling tools with similar themes (e.g., json-quality) makes the lack of explicit guidance a moderate gap.

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