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

Beyond the annotations, the description discloses exactly what is returned at each access tier (free vs signed-in vs Pro), that unknown domains trigger a live Meta Ad Library check, that a daily limit and a 5-new-domains-per-day free quota apply, and which fields are gated. This is precisely the kind of quota, fallback-behavior and tier-gating context annotations cannot convey.

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?

Information is front-loaded: the core question and result set come first, tier-gating and limits after. It is a dense single paragraph with no filler, though the parenthetical quota clauses make it slightly harder to scan than a short bulleted split would be.

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 single-parameter, no-output-schema lookup, the description covers everything an agent needs: what it returns, how results differ by plan, that live external lookups may occur, and that rate limits exist. Nothing material about calling it correctly 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?

Schema coverage is 100% and the single domain parameter is already documented with an example and the note that a URL works. The description adds only marginal meaning, implying that the domain is resolved to a Facebook page and that unresolved domains go to a live lookup. With one well-documented parameter, a baseline 3 is appropriate.

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 opens with a concrete question the tool answers ("Is this store running Meta ads?") and states the specific lookup: resolving a store domain to its Facebook page and returning advertising-since, live ads, trend, channels and platform. The verb and resource are unambiguous. It does not, however, name or contrast itself with siblings such as check_store or reveal_brand, so an agent must infer the distinction from other tool definitions.

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?

The framing question implies when the tool is appropriate (ad-activity checks on a store domain), and the plan-tier limits give useful context for repeat calls. But there is no explicit when-not guidance and no mention of the alternative siblings for related tasks like niche listing or signal search, so routing is left partly to inference.

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