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

Annotations already mark it read-only and open-world, and the description adds that it returns tags grouped by facet, which is useful behavioral detail beyond the annotations. It does not discuss rate limits or pagination, but the output schema covers return structure.

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 three sentences long, front-loaded with the core functionality, and contains no filler. Each sentence contributes either the output definition, usage guidance, or input reminder.

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 read-only tool with two fully documented parameters and an output schema, the description sufficiently covers what the tool returns and when to use it. The annotations and schema handle safety and parameter constraints, so nothing material 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?

Schema coverage is 100%, so the description does not need to compensate. It only repeats 'Input: a domain' without adding details about the enum values or the async option, both of which are already well documented in 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 states 'Return the enrichment taxonomy of a content domain' with specific output semantics ('every tag grouped by facet'), making the purpose concrete. This distinguishes it from sibling content tools like content_catalog or content_ranking by focusing on controlled vocabulary rather than content items or scores.

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 description directly says 'When to use this tool: an agent needs the controlled vocabulary to filter, classify or query content,' which gives clear invocation context. It does not name alternatives or exclusions, but the targeted use case is sufficient for a simple read-only lookup.

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