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

With no annotations, the description carries the full disclosure burden, and it does state the concrete content returned: endpoints, parameters, rate limits, CSV downloads, and attribution terms. This tells an agent what to expect beyond a vague 'reference.' It doesn't mention return format (text vs structured) or whether it is read-only, so it stops short of full transparency.

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 tight sentences: the first front-loads the content inventory, the second gives the usage condition. No filler, no repetition of the name or title, and the most decision-relevant information (when to call it) is easy to locate.

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 parameterless documentation tool with no output schema, the description is sufficient: it says what content is available and when to reach for it. Slightly more detail on response shape would make it fully self-contained, but nothing essential is missing.

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 no parameter semantics to document and the baseline is 4. No schema detail is required or missing.

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 names a specific resource — the underlying free API — and enumerates what it covers: endpoints, parameters, rate limits, CSV downloads, and attribution terms. This clearly distinguishes it from the sibling data-query tools, which return market data rather than API documentation. It lacks a crisp verb+resource formulation but the purpose is unambiguous.

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 explicit routing guidance: 'Use when a tool here does not cover the exact query,' which positions it as the fallback for the 21 sibling data tools. The condition is precise and actionable, though no counter-examples or exclusions (e.g. don't use this when a data tool already fits) are spelled out.

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