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

Annotations already declare readOnly, idempotent, non-destructive, and closed-world behavior, so the safety profile is covered. The description adds genuinely new behavioral context: it is free, requires no model, spends no check, and only reads prior measurements — useful cost/side-effect disclosure beyond the structured hints.

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?

Front-loads the purpose ('how a site's AI visibility reading has moved over time') before the parenthetical detail and the free/no-check note. Dense with semicolons but every clause earns its place; no filler.

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?

An output schema exists, so return values need not be spelled out. The description covers what the tool yields, the historical scope, and the zero-cost behavior; the only gap is explicit routing against sibling measurement tools, which is minor given the 'reads what was already measured' framing.

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?

There is a single required parameter with 100% schema description coverage, and the description adds no URL syntax or format beyond what the schema states. Per the baseline rule, a 3 is appropriate when the schema fully documents the lone parameter.

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 resource (a site's AI visibility reading) and explicitly scopes it to movement over time, listing the concrete weekly data points (identity score, crawlers, llms.txt, Organization schema, top fix). This distinguishes it conceptually from fresh-measurement siblings like analyze_site, though it never names a sibling directly.

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 clause 'Free, no model, and no check is spent: it reads what was already measured' implies this is for retrieving existing history rather than triggering a new run, which guides usage. However it never explicitly contrasts with alternatives such as analyze_site or visibility_fixes, leaving the when-to-use decision largely to inference.

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