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

With no annotations, the description carries the full burden, and it usefully discloses that the call is "Free" and "processes no data," i.e. a read-only, zero-cost, side-effect-free operation. It does not discuss auth requirements or any rate limits, but for a static reference endpoint this is solid behavioral context.

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, front-loaded with the returned content and ending with the routing cue and cost note. The enumerated list is dense but every item is meaningful information an agent needs, with no filler.

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?

There is no output schema, so the description must describe the payload — and it does, itemizing all four categories of returned data plus the per-call limits. An agent knows precisely what it will get and when to call it, leaving nothing essential uncovered.

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 per the rubric the baseline is 4. There is nothing for the description to disambiguate beyond confirming this is a no-argument call.

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 uses a specific verb (Returns) and enumerates exactly what the resource contains: aggregation functions, date bucket formats, row labels, and per-call limits. It clearly reads as a discovery/reference tool rather than an executor, implicitly contrasting with aggregate_rows, though it never names that sibling explicitly.

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?

It gives a clear trigger — "Call this first if you are unsure what is available" — which tells the agent when to reach for this instead of guessing. It stops short of stating when not to call it or naming aggregate_rows as the alternative for actual computation.

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