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

No annotations are provided, so the description carries the behavioral burden. It communicates that this is a read-only provenance lookup and outlines what information the agent should expect to receive. It does not mention permissions or edge cases, but the tool's simplicity and zero-parameter interface make that omission minor.

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 one direct sentence with no wasted phrasing. It front-loads the output contents and closes with a practical attribution purpose, making it easy for an agent to parse quickly.

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 no-argument provenance retrieval tool, the description sufficiently covers what the agent will receive and why it should be called. There is no output schema, so the description's enumeration of source, date, licence, and citation is enough for correct usage.

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, so the description does not need to explain parameter behavior. It still adds semantic value by indicating that the returned provenance includes source, computed date, licence, and citation.

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 exact resource ('Background Check Quotes dataset') and the specific information returned: source, computed date, licence, and citation. This makes it immediately distinguishable from sibling tools like dataset_search, dataset_stats, and dataset_columns.

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 clear contextual guidance: read this to attribute a figure correctly. It does not explicitly name alternatives or state when not to use it, but for a provenance metadata endpoint the suggested use case is clear enough.

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