get_visibility_score

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

No annotations are provided, and the description does not explicitly state that the tool is read-only or has no side effects, but it is reasonable to infer from the scoring nature. The description does not disclose auth requirements or rate limits, but it outlines the output structure adequately for a simple query tool.

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 description is a single, well-structured sentence of 18 words that front-loads the core purpose and efficiently specifies the output components (score, breakdowns, recommendations), with no wasted words.

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?

Given the simple input schema (one required parameter) and no output schema, the description fully explains what the tool returns: an overall score, per-platform breakdowns, and recommendations, meeting the needs for agent invocation.

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?

With 100% schema description coverage (the brand parameter is described as 'The brand name to score'), the description does not add significant new meaning beyond the schema, only reiterating that it scores 'for a brand'. 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?

The description clearly states the tool calculates an overall AI visibility score (0-100) for a brand across all four AI platforms, specifying the verb, resource, and included outputs (per-platform breakdowns and recommendations), distinguishing it from siblings like check_brand_visibility or get_recommendations.

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 provides no explicit guidance on when to use this tool versus siblings (e.g., check_brand_visibility, get_recommendations), nor does it mention when not to use it, leaving the agent to infer the appropriate context.

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