list_topics

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

There are no annotations, so the description carries the transparency burden; it clearly indicates a read-only listing behavior ('List all topics') and notes that topics organize prompts. It does not discuss empty results or pagination, but for a simple read tool the core behavior is adequately disclosed.

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 with the main operation front-loaded and examples to clarify what a topic is. There is no redundant or filler text.

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 one-parameter read tool with fully described parameters, the description supplies enough context: what the tool returns, how topics relate to prompts, and the brand scope. No output schema is present, but the expected output is self-evident from 'List all topics'.

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% because brandId is already described as 'The brand UUID from list_brands'. The tool description restates the brand scope but does not add new parameter guidance beyond the schema.

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 uses a specific verb ('List'), identifies the resource ('topics'), and scopes it to a brand. It also defines topics as groupings of related prompts, which separates this tool from sibling tools like list_prompts.

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 statement is clear that this tool is for retrieving all topics configured for a given brand, and the topic-grouping context implies 'use this when you need topic structure rather than raw prompts.' It does not explicitly name alternatives or when-not-to-use conditions, so it falls just short of a 5.

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