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

Annotations already declare readOnlyHint=true, openWorldHint=false and idempotentHint=true, so the safety profile is covered. The description adds genuinely new context beyond them: the data is an archived snapshot rather than a live measurement and nothing external is fetched, which matters for assessing staleness and trust. It stops short of noting how often the archive is refreshed or whether sample size varies by category.

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 primary return payload and closed with the crucial archived-vs-live caveat. The long enumeration of returned fields is dense but each item informs an agent's decision about whether this data answers its question; only 'with sample size and scan date' feels marginally tacked on.

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 carries the full burden of describing return values — and it does so thoroughly, listing every field group an agent would need. Combined with the single, fully documented parameter and complete annotation coverage, an agent has everything required to invoke this correctly and interpret the result.

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 100% and already lists the six allowed category values, so the baseline is 3. The description goes further by explaining the semantic consequence of omission — a ranked summary across every category rather than simply 'all categories' — which tells an agent what shape the result takes, not just that the filter is skipped.

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?

States a specific verb and resource — returns Citehound's archived scan data for one category — and then enumerates exactly what that payload contains (average, median, range, pillar breakdowns, crawler counts, failed checks, sample size, date). It also distinguishes the no-argument mode as a ranked cross-category summary, so an agent can tell it apart from scan_site and the report-generating siblings.

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 description makes the key usage decision explicit: pass a category for one benchmark, omit it for a ranked summary across all categories. It also rules out the most likely wrong invocation by stating this is archived data and 'not a live scan', which routes an agent needing fresh data toward scan_site. It does not explicitly name that sibling or say when to prefer get_methodology/get_sample_report, so it falls short of a full 5.

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