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

With no annotations, the description carries the full behavioral burden. It usefully discloses the operator-only restriction and Schnorr-signed proof requirement, but does not explain side effects such as whether the existing pricing model is overwritten, reversibility, or error behavior on invalid proof.

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 short sentences with the core action and restriction front-loaded. Every sentence adds relevant information with no wasted 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?

For a mutation tool with no annotations and 0% schema description coverage, the description should explain the required 'model_json' format and how the proof/dpop_token is supplied. It gives auth context but leaves the agent unable to correctly populate the required parameter.

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 0%, so the description must compensate for two undocumented parameters. It mentions a proof but does not connect it to the 'dpop_token' parameter, and it gives no information about the required 'model_json' content or format.

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: 'Set the active pricing model.' This clearly distinguishes the tool from sibling operations like get_pricing_model and reset_pricing_model by action and scope. The operator restriction adds further precision about the tool's domain.

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?

'RESTRICTED to operator' and 'Requires a valid proof...' give clear prerequisites and usage context. It does not explicitly name alternatives such as get_pricing_model or reset_pricing_model, but the conditions for use are well communicated.

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