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

No annotations are provided, so the description carries the behavioral burden. It discloses the returned data (columns, numeric flags, row count, provenance banner), which implies a read-only metadata call, but never states that explicitly, nor mentions cost, auth, or side effects.

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 compact sentences: one enumerating the payload, one stating the call ordering. No filler, and the usage directive sits at the end where it is easy to catch.

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?

With no output schema and no annotations, the description does the work of describing returns and when to call. It is complete for a zero-argument metadata tool, though it could note that the result is static/read-only to fully cover the behavioral gap.

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 takes zero parameters, so there is nothing for the description to disambiguate beyond what the schema provides. Baseline 4 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?

States a precise verb-and-resource ('The columns... row count... provenance banner of the Working Capital Quotes dataset') and enumerates exactly what it returns. An agent can distinguish it from dataset_stats or dataset_provenance by the explicit content list.

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 directs 'Call this first to learn the schema,' giving the agent a clear ordering cue relative to the sibling exploration tools. It stops short of naming when-not-to-use it or pointing to the alternatives by name, but the sequencing guidance is unambiguous.

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