Read the answers behind the numbers

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

Annotations already mark it read-only, and the description adds context about scoping to the active project and the answer attributes returned: brand named, position, and cited sources. It does not discuss pagination or response details, but the schema covers cursor and limit, and no contradiction exists.

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 sentences, front-loads the core meaning, and includes a practical call-condition without filler. Every phrase contributes.

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?

The description conveys the purpose, scope, and key response fields for a tool with no output schema, and the input schema covers all parameters. It still leaves response shape and pagination to be inferred from the cursor/limit parameters rather than describing them explicitly.

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?

All eight parameters have schema descriptions, so the schema carries the semantic load. The description adds no parameter-level guidance beyond that, giving the baseline score of 3.

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 names a specific resource (the answers assistants gave on prompts) and a concrete verb context (listing them with brand-named status, position, and cited sources). It distinguishes itself from siblings like get_visibility_summary by stating it is for explaining a visibility figure rather than restating it.

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?

It explicitly states when to call the tool: 'when a visibility figure needs explaining rather than restating.' However, it does not name the alternative tools or give when-not-to-use conditions, so it falls short of full exclusion guidance.

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