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

With no annotations, the description must disclose behavioral traits. It does state the content returned (source, date, licence, citation), but does not explicitly confirm read-only semantics, absence of side effects, or any operational requirements. For a simple metadata retrieval, this is adequate but not exhaustive, so a 3 is appropriate.

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 a single, tightly worded sentence that front-loads the core content and then adds the usage directive. There is zero fluff; every word contributes to understanding. This is exemplary conciseness.

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?

Given the tool's simplicity (no parameters, no output schema), the description is fully complete. It explains what information is provided, for which dataset, and why one would use it. Nothing an agent needs to call it correctly is missing.

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 meaning. The baseline for 0 parameters is 4, and the description correctly focuses on the output and purpose rather than parameters.

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 function: it provides the source, computation date, licence, and citation for the Subsroom dataset. It also gives a specific use case ('to attribute a figure correctly'), which is distinct from the sibling tools that deal with columns, comparison, rows, search, stats, and top values. This is a precise verb+resource statement.

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 context for when to use the tool ('Read this to attribute a figure correctly'), but does not explicitly mention alternatives or when not to use it. Since the siblings are about data manipulation, the use case is implicit, but explicit exclusions are absent. This fits 'clear context, no exclusions'.

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