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

With no annotations, the description carries the full behavioral burden. It discloses the maximum result size (50 rows) and the searchable fields, but does not cover read-only nature, pagination, default limits, or authentication requirements.

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 a single dense sentence that is appropriately sized and front-loads the core search target. It wastes little space, though it could be slightly more scannable.

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 4-parameter search tool with no annotations, no output schema, and 0% parameter description coverage, the description covers core search semantics and filters. It still omits default limit behavior, pagination, and whether q is required or optional.

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%, so the description must compensate. It explains q as matching name, commercial name, website, address, or authority; region as accepting id or name; service as accepting slug or name; and constrains output to 50 rows.

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?

Describes a search over entities in the Immigration Adviser Finder register, specifying which fields are matched. The purpose is clear, but it does not explicitly differentiate this tool from siblings such as entity_lookup, entities_in, or dataset_search.

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 implies usage by describing optional region and service filters, along with a result cap. However, it does not explain when to use this tool instead of alternatives like entity_lookup or entities_in.

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