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). The description adds genuine context beyond them: the score scale (0-100) and the important edge case that the composite is null when nothing has been measured yet. It does not cover freshness/staleness or whether a score must first be generated, so not a full 5.

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?

A single dense sentence with zero filler, front-loading the action and resource before the return contents. Every clause earns its place.

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?

With an output schema present, return shape need not be re-explained, and the description still adds the meaningful null-score semantic. The only gap is the missing routing context relative to score_ai_visibility for a tool whose value depends on knowing when a scorecard already exists.

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?

Only one parameter, fully documented in the schema (100% coverage) including its source ('from list_domains'). The description adds no parameter-level detail, so the baseline 3 applies.

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 ('Read') and resource ('AI Visibility Scorecard') and enumerates the payload (composite score, latest score, confidence, per-dimension recommendations). It does not, however, explicitly distinguish itself from near-siblings like score_ai_visibility (which presumably computes) or get_share_of_voice, leaving the agent to infer the boundary.

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?

There is no explicit when-to-use guidance: nothing tells the agent when to call this versus score_ai_visibility (recompute) or get_share_of_voice. Usage is only implied by the word 'Read'.

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