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

No annotations exist, so the description carries full responsibility. It discloses exactly what data is returned (columns, numeric flags, row count, provenance banner) and implicitly signals a safe read operation. It does not mention pagination or output formatting, but for a simple schema tool this is adequate.

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 sentences, with the essential content front-loaded and the usage directive appended. Every word earns its place; no filler or repetition of the title.

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, no-output-schema tool, the description covers the key return values and the recommended calling order. The only minor gap is the unexplained term 'provenance banner,' but it is a domain-specific label rather than a missing behavioral detail.

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 there is nothing for the description to add. The baseline of 4 applies here because no parameter semantics are needed, and the description avoids inventing fake parameter guidance.

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 provides columns, numeric indicators, row count, and provenance banner — a specific schema-discovery resource. However, it lacks an explicit verb like 'returns' and does not directly distinguish itself from sibling dataset_provenance, relying on 'Call this first' to imply its discovery role.

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?

Explicitly instructs 'Call this first to learn the schema,' which tells an agent exactly when to invoke it. It does not mention exclusions or alternatives, but the guidance is clear enough for a zero-parameter discovery tool.

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