find_unused_types

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

With no annotations, the description carries the full burden of behavioral disclosure. It states the core behavior (returning unused classifiers) but does not mention whether it is read-only (likely implied by 'Return'), whether it scans the entire model, or any performance or side-effect implications. It is not misleading, but it offers minimal behavioral context beyond the primary purpose.

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, clear sentence that is front-loaded with the verb and resource. There is no redundancy or fluff. It earns its place by stating exactly what the tool does.

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 zero-parameter query tool with an output schema (has_output_schema: true), the description is complete. It defines the scope ('anywhere in the model') and the entity type ('classifiers'), and the output structure is covered by the schema. No additional context is needed for an agent to call it correctly.

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 the baseline is 4 per the rubric. The description correctly implies that no input is needed. Since there are no parameters to document, the description adds no parameter-specific meaning, but the baseline already 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 clearly states the verb 'Return' and the resource 'classifiers that are not used as a type anywhere in the model.' This is specific and unambiguous, and it distinguishes the tool from siblings like find_by_type (which finds by type) and find_by_name. An agent can immediately understand the tool's function without ambiguity.

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 gives no guidance on when to use this tool versus alternatives. It doesn't mention use cases (e.g., cleanup, refactoring) or contrast with find_by_type, find_unused, or other query tools. An agent is left to infer when this tool is appropriate, which is a significant gap for a model with many find tools.

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