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

Annotations already declare the full safety profile (readOnlyHint, idempotentHint, destructiveHint=false, openWorldHint=false), so the behavioral burden is light. The description adds the useful context that this is a scoped, workspace-and-brand-specific read across four AI platforms, but says nothing about result size, ordering, or pagination.

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 compact sentences with no filler; the resource definition comes first and the downstream create_prompt linkage is front-loaded in the second clause. Every phrase earns its place.

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 simple one-parameter read tool with annotations covering safety and no output schema, the description is nearly sufficient. It explains what is returned conceptually, though it omits return shape details such as pagination or whether topic_id values map one-to-one with prompts.

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?

Schema description coverage is 100%, and the single brand_id parameter is fully documented in the schema, including the fallback behavior for single-brand workspaces. The description adds no parameter detail of its own, so the baseline 3 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 names the specific resource — the topics and buyer questions tracked for a brand — and scopes it to the workspace, with the four AI engines listed as the query targets. It also routes to create_prompt via topic_id, which helps distinguish it from other list-style siblings, though it doesn't directly contrast with list_brands.

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?

Usage is implied rather than stated: the note that it 'gives the topic_id create_prompt needs' tells the agent this is the lookup step before create_prompt. There is no explicit when-not guidance or mention of conditions like empty results or when another listing tool would be preferable.

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