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

No annotations are supplied, so the description carries the full disclosure burden. It does implicitly signal a safe read-only operation by describing static metadata, but says nothing about caching, freshness guarantees, permissions, or the response shape. For a zero-parameter read, the residual risk is low, so this is adequate rather than poor.

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?

Two sentences, no filler. The returned fields are front-loaded and the actionable instruction comes second, which is the right ordering for an agent scanning for a purpose.

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?

With no output schema, the description must convey what comes back, and it does by listing the four data points (source, date, licence, citation). Anything further, such as exact field names or citation formatting, would be a nice-to-have rather than a gap that would cause a mis-call.

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 takes zero parameters, so there is nothing for the description to disambiguate; the baseline of 4 applies. The schema is empty and consistent with a no-argument metadata lookup.

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 names a specific resource (the EntitySearch HQ dataset) and enumerates exactly what it returns: source, computation date, licence, and citation. That scope is unambiguous against siblings like dataset_columns, dataset_stats, or dataset_row, none of which expose attribution metadata.

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?

"Read this to attribute a figure correctly" gives a clear triggering condition for using the tool. It stops short of naming alternatives or stating when-not-to-use it, but for a single-purpose metadata endpoint no realistic confusion exists.

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