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

Annotations already declare readOnlyHint=true and openWorldHint=false, covering the safety profile. The description adds useful context beyond the annotations by specifying that results are limited to creators eligible for content assignments and that the output contains model_id and name/email for use downstream.

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?

Two sentences with no filler: the first states the core purpose, the second explains how to use the result. Every word earns its place and the most important information is front-loaded.

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 no output schema, the description is complete: it defines the return payload enough (model_id, name/email) and tells the agent how to consume it. No prerequisites, permissions, or edge cases are needed for a simple list operation.

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 is empty with zero parameters, so no parameter documentation is needed. The baseline of 4 applies for 0-param tools, and the description appropriately avoids inventing parameter details.

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 ('List') and resource ('creators (models) of the organization who can receive content assignments'), making its purpose unmistakable. It is clearly distinct from sibling list tools like list_assignments and list_categories because it names the exact entity type and eligibility scope.

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 provides explicit downstream guidance: 'Use the returned model_id (or the name/email) with create_assignment,' telling an agent when this tool is relevant. It does not explicitly say when not to use it or mention alternatives, but the linkage to create_assignment gives sufficient context.

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