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

Annotations already declare readOnly/idempotent/non-destructive, so the description correctly spends its budget elsewhere: it discloses one-entry-per-platform with best-first ordering, no cursor/limit/date window, and critically that an empty slice retains the selected Scan and never falls back to an older one. These are non-obvious behavioral traits an agent needs.

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?

Purpose is front-loaded, which is good, but the tail sentences (scanDate, scanCompletedAt, subjectContext) read as internal notes whose value is diminished by the presence of an output schema. Several clauses are dense and jargon-heavy ('finite canonical AI platform catalogue', 'empty slice retains the selected Scan').

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 12-parameter cross-Scan tool, the description covers the genuinely tricky parts: entity resolution for Sites vs Topics, filter effects, empty-slice/no-fallback semantics. With an output schema present it does not need to describe return values, and it adequately fills the remaining gaps.

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 92%, so the schema already carries most parameter meaning (e.g. brandId's default/neutral-topic rule is largely restated). The description adds the metric=visibility default and notes that region and prompt classification filters affect values, but does not meaningfully extend the well-documented parameters.

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: comparing one entity metric across the canonical AI platform catalogue within a Scan. This is clearly the per-platform breakdown tool, distinguishable in concept from get_visibility_overview or get_visibility_timeline, though no sibling is named explicitly.

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?

Provides entity-resolution context (Sites use primary entity, Topics use saved focal entity or need brandId) and states the metric default. However, it never says when to prefer this over siblings like get_visibility_overview or get_visibility_timeline, nor names any exclusion. Usage is implied rather than contrasted with alternatives.

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