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

With no annotations, the description carries the burden of behavioral disclosure. It states what information the tool provides but does not explicitly say it is read-only or non-mutating. The directive 'Call this first' strongly implies safe introspection, but the lack of an explicit safety statement prevents a higher score.

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?

Two short sentences in which every phrase earns its place: the first lists the returned content, the second gives the call sequence. It is front-loaded with the most important information and contains no filler.

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 tool with no output schema, the description adequately names the key returned components (columns, numeric flags, row count, provenance banner) and when to call it. It does not describe the exact response format, but that is a minor gap for such a simple metadata tool.

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 input schema has zero parameters, and schema coverage is 100%, so there are no parameter semantics the description needs to explain. Per the baseline rule for zero-parameter tools, a 4 is appropriate.

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 (Termslane dataset) and the specific outputs: columns, numeric flags, row count, and provenance banner. It lacks an explicit verb like 'returns' or 'lists', which keeps it from a 5, but the content is unmistakable and distinct from sibling tools like dataset_search or dataset_stats.

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?

'Call this first to learn the schema' gives explicit positional guidance, making it clear this is the entry-point tool for schema discovery. It does not mention when not to use it or name alternatives, but for a zero-parameter metadata tool 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.