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

With no annotations, the description bears the burden of behavioural disclosure. It does specify what is returned (source, date, licence, citation) and 'Read this' implies a read-only operation, but it does not explicitly state that it is non-destructive or requires no permissions. The added context about content is helpful, yet the safety profile is only implied.

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 succinct sentences with no filler: the first lists the exact content returned, and the second front-loads the usage context. Every word earns its place, and the most relevant information appears first.

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, output-schema-free tool, the description covers the essentials: what the data refers to, what fields are present, and when to use it. The only small gap is the exact return format, but this is unlikely to block 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 schema already covers everything; the baseline for 0 parameters is 4. The description need not elaborate, and adding parameter details would have been redundant.

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 names a specific verb and resource: it returns the source, compute date, licence, and citation for the Card Machine Pricing dataset. This clearly distinguishes it from siblings like dataset_row or dataset_stats, which analyze data rather than explain its provenance.

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 states a clear usage context: 'Read it to attribute a figure correctly,' signalling when this tool is appropriate. It does not name exclusions or alternatives, but given that no sibling fulfils this provenance role, the guidance is sufficient.

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