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

Annotations only declare readOnly/openWorld/destructive hints; the description adds genuinely non-obvious behavior: the data source (research/e5/proxies.json), the staleness rule (observations older than 30 days are omitted), and the output limitations (estimates for full saved package bills only, unknown costs returned as null, no live prices). These are exactly the caveats an agent needs to interpret results correctly.

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 purpose is front-loaded in sentence one and each following sentence adds a distinct constraint (data source, freshness window, estimate scope, null handling). The telegraphic phrasing is dense but nothing is redundant; it could have been split slightly more readably.

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 only safety-annotations, the description carries the burden of describing returns, and it does a fair job: offers carry observed_on dates, bills are estimates, unknown costs are null. What is still missing is the shape/ordering of results and whether multiple offers per provider are returned, so an agent can invoke it correctly but cannot fully predict the payload.

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 description coverage is 0% for both parameters, so the description must compensate; it does partly by noting monthly_gb is optional and that product_type is the anchor dimension. However, it does not enumerate the product_type enum values (residential, datacenter, isp_static_residential, mobile) or clarify how monthly_gb is matched (exact, minimum, or tiered), leaving semantics thin for the one unconstrained numeric input.

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 opening sentence names the resource (captured proxy offers) and the two filter dimensions (product type, optional monthly GB), so an agent can tell what it retrieves. It is phrased as a question rather than a verb+resource statement, and it never contrasts itself with siblings like compare_scrapers, though the proxy-offer domain is specific enough to disambiguate.

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 real scope boundary: 'Estimates full saved package bills only; IP offers are separate and unknown costs remain null. No live prices or performance measurements.' That tells the agent when this tool's output is useful versus when it would need a live-price tool. It stops short of naming an alternative sibling or stating positive preconditions, so it is strong context without explicit routing.

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