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

With no annotations, the description carries the full burden of behavioral disclosure. It does reveal the output contents and implies a read-only schema-inspection operation, but it never explicitly states that the tool makes no changes, nor does it describe any limitations, error behavior, or output format.

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 a single informative sentence plus a clear directive. Every phrase contributes value, and the most important information (what the tool returns and when to call it) is front-loaded with no 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 zero-parameter metadata tool, the description is largely sufficient: it tells the agent what it will receive and that it should be called first. It does not specify the exact return structure or define 'provenance banner', and it does not connect the schema to sibling tools, but these are minor gaps.

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 fully covers the input contract. The description adds no parameter-specific meaning, but none is needed; the baseline of 4 for zero-parameter tools applies.

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 (Kickoffo dataset) and the delivered information: columns, numeric flags, row count, and provenance banner. It does not explicitly differentiate from siblings like dataset_stats or dataset_provenance, though the 'Call this first to learn the schema' framing gives it a distinct 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?

The description gives explicit context for when to call it ('Call this first to learn the schema'), which is strong usage guidance. It stops short of naming alternatives or stating when not to use it, so it lacks the exclusion criteria needed for a 5.

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