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

With no annotations, the description must carry the behavioral disclosure burden. It discloses what information is returned (columns, numeric indicators, row count, provenance banner) and implies a read-only metadata operation, but it does not explicitly state side effects, permissions, or performance characteristics. The description is adequate but not deeply 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, front-loads the key output items, and ends with a clear usage directive. There is no fluff or redundant information, so every sentence earns its place.

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 simple, parameterless metadata tool with no output schema, the description covers the main return items and gives a clear invocation order. It could be more explicit about the response shape or format, but nothing critical seems missing for an agent to decide to call 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 tool has zero parameters, so per the calibration baseline this dimension should be scored 4. The description correctly references no inputs and focuses entirely on the output, which is appropriate for a parameterless schema-introspection tool.

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 tool's purpose: returning the Siftvo dataset's columns, numeric flags, row count, and provenance banner, plus the directive to call it first to learn the schema. It is specific about the resource and output items, though it does not explicitly differentiate itself from siblings like dataset_stats or dataset_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 gives clear usage context by saying 'Call this first to learn the schema,' which positions it as the initial exploration step. It does not mention alternative tools or when not to use it, but the sequencing guidance is useful and explicit.

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