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

With no annotations, the description carries the full burden and does so well: it discloses that FCC does not verify complaints, that counts are not per-subscriber rates and name no carriers, that free access is limited to the last 30 days while a Pro key unlocks history, that incomplete days are flagged rather than filled, and that values carry unit/date/source URL. These caveats are exactly the context an agent needs to interpret results responsibly.

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?

It is a single dense paragraph, but content is front-loaded with the dataset definitions before caveats and licensing. Nearly every clause adds usable information (sources, units, tier limits), though the licensing sentence could be trimmed.

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 multi-dataset retrieval tool with six optional parameters, no annotations, and no output schema, the description covers sources, dataset semantics, tier limits, caveats, and the shape of returned values (unit, date, source URL). Only pagination behavior and error cases are left implicit.

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?

Schema coverage is 67% and the description fills much of the gap: it explains the meaning of each dataset value, restricts state to 'complaints only' with US default, and ties start to the free/Pro history boundary. Only limit/offset go unexplained in prose, but limit has a schema description, so the residual gap is small.

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 (U.S. government mobile phone service data) and enumerates the three datasets it can return, so an agent knows exactly what the tool produces. It does not explicitly contrast itself with the many sibling tools, but the domain is distinctive enough that confusion is unlikely.

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?

Dataset semantics implicitly route usage ('complaints' for FCC counts, 'issues' by complaint type, 'cpi' for BLS price index) and it states that state=US is national vs. a state code. It never gives explicit when-to-use/when-not guidance relative to alternatives, leaving the agent to infer selection from the dataset labels.

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