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

With no annotations, the description fully discloses key behaviors: it deletes all stored models, self-initializes a fresh one with tools at 0 sats and proper UUIDs, returns the new model, and is restricted to operators requiring proof. This is comprehensive for a destructive action.

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 three short, well-structured sentences. It front-loads the main purpose, details the process, and ends with restrictions. Every sentence adds value without redundancy.

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 destructive nature and one optional parameter, the description covers behavior and restrictions adequately. However, it omits parameter details and does not mention return format (though output schema exists). It is mostly complete but could improve parameter clarity.

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 input schema has one parameter (dpop_token) with 0% description coverage. The description does not explain this parameter's purpose or relationship to the required nsec-signed proof, leaving a gap despite the parameter being optional with a default.

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 tool erases all pricing models and restores a viable default, using specific verbs like 'erase' and 'restore'. It explicitly distinguishes from siblings like get/set pricing models by detailing the reset process.

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 specifies that the tool is restricted to operators and requires nsec-signed proof, providing clear context for who should use it and prerequisites. However, it does not explicitly state when not to use it or compare with alternatives like schwab_set_pricing_model.

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