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

With no annotations, the description carries the full burden. It usefully discloses case-insensitive substring matching across any cell and a hard 50-row cap, but says nothing about ordering, pagination beyond the cap, or what happens when the cap truncates results — material for a search tool whose result set can be silently clipped.

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?

A single sentence that front-loads the resource, the match semantics, and the result cap. No filler.

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?

There is no output schema, so the description must convey the return shape. 'Rows of the dataset' is roughly sufficient to convey a row collection, but the fields per row and the behavior when more than 50 rows match are left unspecified.

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 50% (only query documented). The description compensates: it defines query as a cell-level case-insensitive contains match and explains that limit is capped at 50, adding meaning beyond the bare integer maximum 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?

States the operation (return rows whose cells contain the query) against a named resource (the Immigration Adviser Finder dataset) and bounds the result, so an agent knows exactly what it returns. It does not explicitly contrast itself with siblings like dataset_top or dataset_row, but the substring-match semantics are distinctive enough.

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?

Usage is only implied: 'cells contain the query' suggests free-text lookup, but there is no statement of when to prefer this over dataset_top, dataset_row, or entities_search, nor any precondition. Minimum viable at best.

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