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

It goes well beyond annotations by disclosing 'Cannot spend money', the auditable component-level scores, the CAP on severe properties, and that unmeasurable components are never estimated. These are non-obvious behaviors that materially change how an agent should interpret the result.

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 dense but every sentence earns its place: the when, the exclusions, the auditability, the cap, and the estimation policy. It is front-loaded with the use condition and structured so critical limitations come before the scoring details are absorbed.

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?

With no output schema, the description still explains how results are composed (score, weight, basis) and how severe properties cap the total. It also explains what happens for unmeasurable components, which covers the main risks an agent would face when invoking this 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?

The input schema covers both parameters thoroughly (domain and domains) at 100% coverage. The description adds context about scoring candidate names but does not add new parameter-level constraints or formats; the schema already carries the semantic weight.

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 action and resource: 'Grade candidate names' on a set of measurable properties. It explicitly differentiates itself from check_live (availability), search-ranking prediction, and trademark search, so an agent can tell it apart from siblings without inspecting schemas.

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 says exactly when to use the tool: when the user is choosing between names or asks whether a name is any good. It also names the alternatives to use instead, including check_live for availability and explicit exclusions for search-ranking and trademark search, leaving no ambiguity.

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