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 states what information is returned (source, date, licence, citation) but does not explicitly confirm read-only behavior, mention error conditions (e.g., if provenance is unavailable), or note any side effects. The description is accurate but not deeply transparent about behavioral edge cases.

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 concise sentences with no redundancy. The first sentence lists the returned fields (source, date, licence, citation) and the second provides the use case. The title is short and informative. 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 simple parameterless tool with no output schema, the description adequately covers what the agent needs to know: what fields will be returned and why to use the tool. It does not address edge cases like missing provenance data, but given the low complexity, this is a minor gap.

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 schema has zero parameters, so the baseline of 4 applies. The description does not need to explain any parameters since none exist, and it does not attempt to invent parameter semantics. This is appropriate for a parameterless tool.

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 states the tool's purpose: it provides provenance information (source, date computed, licence, citation) for the PayoffCompass dataset. The title 'Where this data comes from, and how to cite it' reinforces the purpose, and it is easily distinguished from sibling tools that query data values (dataset_search, dataset_stats, dataset_top) versus this metadata/provenance tool.

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 an explicit use case: 'Read this to attribute a figure correctly.' This implies when to use the tool (when citation/provenance is needed) and implicitly contrasts with sibling data-query tools. It does not explicitly name alternatives or state when not to use it, but the guidance is sufficient for the tool's simplicity.

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