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

Annotations already declare readOnly, idempotent, non-destructive and open-world behavior, so the safety profile is covered. The description adds that the result is a directory of canonical slugs plus descriptions and that filtering is optional, but says nothing about result size, ordering, or whether the full list is returned when no query is given.

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?

Three tight sentences with the core purpose first, then the disambiguation from industries, then the filter behavior. No filler, though the slug/description enumeration is slightly redundant with the examples.

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?

Output schema exists, so return shape need not be explained, and the tool is a simple single-parameter listing. What is missing is filter-matching behavior and result-set expectations, minor gaps for a discovery tool.

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 0%, so the description has to carry the single parameter, and it does state that 'query' filters the domain directory. It does not describe matching semantics (substring vs. exact vs. fuzzy) or what the query matches against, so it only partially compensates.

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 and resource ('Lists AI research fields with canonical slugs and descriptions') and gives concrete examples of the domains returned. It explicitly distinguishes these research domains from commercial company industries, which separates it from the sibling list_industries.

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?

Clear that the domain directory can be filtered with an optional query, and the industries exclusion routes the agent away from list_industries. It does not say when to prefer this over search_research, but the browse-vs-search split is reasonably implied.

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