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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, closed-world), and the description adds substantial context beyond them: result ordering, the full set of item fields, the status lifecycle values, the 0-to-1 range of target_share, and the meaning of an empty page. Because there is no output schema, this return-shape disclosure is doing real work rather than repeating structured data.

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 leading sentence front-loads the action, scope, and ordering before the domain explainer, which is the right structure. The rest is dense but nearly every clause carries information; the item-field enumeration is long yet justified by the absence of an output schema. Minor loss for being one undifferentiated block with no visual breaks.

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 zero-required-parameter list tool with no output schema, the description supplies ordering, filter semantics, per-item fields, and an explicit empty-result caveat — covering the main ways an agent could misread this tool. Only small gaps remain, such as total-count behavior or what happens with an invalid filter value.

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 50%: limit and cursor are documented in the schema, while status and client_id are bare enums/UUIDs. The description labels these two as 'Filters' and restates the status values in prose, but adds no semantics the schema lacks — nothing about what a client_id refers to or how status filters interact. 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?

States a specific verb and resource ('Lists the Citation Scans'), the scope ('in the connected account'), and the ordering ('newest first'). It goes further by defining what a Citation Scan actually is (fixed buyer questions in one category/country across AI answer engines, recording cited websites), which makes the tool's output intelligible without any external domain knowledge.

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?

Names the two filters (client_id, status) and explains the empty-page semantics ('none were returned for these filters, not that the account has none'), which is exactly the kind of interpretation guidance that prevents wrong conclusions. It stops short of explicitly routing between this and get_citation_scan or list_diagnostics, so no true when-not guidance is present.

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