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

No annotations are provided, so the description carries the full burden. It describes the content returned (source, date, licence, citation) and uses the word 'Read', which implies a read-only operation. However, it does not explicitly state that it makes no modifications, nor does it mention return format or any potential error conditions. For a simple metadata tool, this is adequate but not richly transparent.

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 zero waste. The key facts (source, date, licence, citation) are front-loaded, and the usage hint follows immediately. Every word earns its place; no filler or redundant phrasing.

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 tool with no parameters and no output schema, the description fully covers what an agent needs to know: what the tool provides and why to use it. The dataset name and the attribute purpose are stated. Nothing essential is missing for correct invocation.

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 input schema is trivially complete. Per the rubric, a 0-parameter tool earns a baseline of 4. The description adds no parameter-specific meaning, but none is needed since there is nothing to configure. It correctly focuses on what the tool returns rather than how to call it.

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 identifies the resource (Reqnix dataset) and the specific information provided (source, computed date, licence, citation). It also states a concrete use case ('attribute a figure correctly'), which distinguishes it from sibling tools that handle columns, rows, search, or stats. The verb 'Read' plus the content list makes the purpose unambiguous.

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 explicit usage context ('Read this to attribute a figure correctly') and implies it is the tool for provenance/metadata queries. It does not explicitly mention when not to use it or name alternatives, but the sibling names (dataset_columns, dataset_row, etc.) make the distinction obvious. Clear enough for an agent to select it appropriately.

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