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

With no annotations, the description carries the full burden. It discloses the tool is free, lists exact returned data (label and category count), and implies a read-only listing through 'Lists.' This covers the key behavioral traits for a zero-parameter metadata tool.

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 short sentences with no filler. The core action and output are front-loaded, and the cost and usage hint fit in one word ('Free') and one imperative ('Call it first').

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 zero-parameter listing tool with no output schema, the description is complete: it states what the tool returns, that it is free, and exactly how it fits into the workflow with topic_scorer_find. No critical information is missing.

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 tool has zero parameters, so the baseline is 4; the description appropriately omits parameter details. There is nothing further needed because the input schema is empty.

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 ('Lists') paired with a concrete resource ('the six taxonomies') and defines the output contents ('label and category count'). It clearly distinguishes this tool from siblings like topic_scorer_find and topic_scorer_score by describing a metadata-listing operation.

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 gives an explicit call order: 'Call it first to pick the taxonomy for topic_scorer_find.' This is clear context for when to use it, though it does not explicitly discuss when not to use it or compare against all sibling tools.

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