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

With no annotations, the description carries the full burden of behavioral disclosure. It states what the tool returns: source, computation date, licence, and citation, which is the tool's core behavior. It does not explicitly state that it is read-only, but the wording and nature of provenance metadata strongly imply a safe read operation with no side effects.

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. It front-loads the specific content returned and follows with a practical use instruction. Every word earns its place.

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 metadata-retrieval tool, the description is complete. It names the dataset, the exact fields returned, and the intended purpose. The absence of an output schema is adequately compensated by the enumeration of return contents.

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, and the schema is an empty object, so there is nothing meaningful to document. The baseline for 0-parameter tools is 4, and the description appropriately does not attempt to invent parameter guidance.

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 clearly identifies the tool's resource, the FindAgency HQ dataset, and the exact provenance fields it exposes: source, computed date, licence, and citation. It lacks an explicit action verb like 'returns' or 'lists', but the title and phrasing make the purpose unmistakable. It is distinct enough from sibling tools like dataset_stats or dataset_columns, though it does not explicitly name a sibling for comparison.

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 provides a clear usage context: 'Read this to attribute a figure correctly.' This tells an agent when to consult the tool. It does not mention alternatives or explicitly say when not to use it, but the narrow provenance scope makes that omission minor.

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