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

Annotations already declare the full safety profile (readOnly, idempotent, non-destructive, closed-world), so the burden is light. The description adds useful context about the data's derivation and return contents (usage counts, fact ids), but says nothing about rate limits, caching, or pagination behavior tied to the limit parameter.

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?

A single front-loaded sentence led by the verb with no filler. It packs purpose and return content efficiently, though the trailing clause about usage counts and fact ids makes it a bit dense.

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 list tool with annotations covering safety and no output schema, the description partly covers return contents. It is still missing any parameter guidance for limit and brandId, so an agent lacks enough to call it precisely with scoping or page sizes.

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 0% for both parameters. The description implies a brand scope ('the brand's') but never explains brandId or what limit controls (result count, range 1-100). With two undocumented parameters it does not compensate for the schema gap.

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?

States a specific verb (List) and resource (brand's macro content topics), and adds that they are grouped from creator facts with usage counts and fact ids. This separates it from list_creator_facts (the raw facts) reasonably well, though it never names that sibling explicitly.

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 phrase 'grouped from its creator facts' implies the tool derives aggregated topics rather than raw facts, hinting at when it is useful. However, there is no explicit when-to-use, when-not, or alternative-tool guidance, leaving the agent to infer its place among the many list_* siblings.

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