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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It lists the returned content (columns, numeric flags, row count, provenance banner) and implies a read-only schema lookup, but it does not explicitly state that there are no side effects, permissions required, or error behavior. Adequate but not fully 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?

Two short sentences, with the first front-loading the exact information returned and the second adding a clear usage directive. Every sentence earns its place with no filler or redundancy.

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 0-parameter, no-output-schema tool, the description covers the key return elements (columns, numeric flags, row count, provenance banner) and the recommended call order. It is reasonably complete, though adding output format details or an explicit read-only label would strengthen it.

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 properties, so there are no parameters to describe. The schema already captures the absence of parameters, and the description adds no misleading parameter information. Baseline 4 applies for 0-parameter tools.

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 returns the dataset's columns, which are numeric, the row count, and the provenance banner. 'Call this first to learn the schema' reinforces its role as the schema-discovery tool. This differentiates it from siblings like dataset_provenance and dataset_stats by focusing on schema/shape rather than rows, stats, or comparisons.

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 instruction 'Call this first to learn the schema' gives explicit timing guidance, positioning this as the initial step. It does not explicitly contrast it with sibling alternatives, but the clear context of being the first schema-related call is sufficient guidance.

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