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

With no annotations provided, the description carries the full burden of behavioral disclosure. It is transparent about what the tool returns: source, computed date, licence, and citation. It implies a read-only metadata operation by saying 'Read this,' and no side effects are suggested. It could mention output format, but the content disclosure is sufficient for this simple tool.

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 sentences with no wasted words. The first sentence enumerates the key content fields, and the second gives the practical use case. The most important information is front-loaded.

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 tool whose output is a small set of provenance metadata fields, the description is complete. It tells the agent what data is returned and why to use the tool. No output schema exists, but the description explicitly lists the return fields, so an agent knows what to expect.

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 input schema has zero parameters, so there is nothing for the description to explain about parameter usage. Schema coverage is 100% by default. The description correctly focuses on behavior rather than parameters, matching the baseline expectation.

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 identifies the specific resource (DoorsetBook dataset provenance) and states exactly what information is provided: source, computation date, licence, and citation. This clearly distinguishes it from sibling tools like dataset_row or dataset_search, which operate on data content rather than 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?

The description gives a clear usage context: 'Read this to attribute a figure correctly.' This tells the agent when the tool is appropriate. It does not explicitly name alternative tools or state when not to use it, but the unique provenance purpose makes the intended usage unambiguous.

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