check_visibility

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

Annotations already declare readOnlyHint=true and openWorldHint=false, establishing this as a safe read operation, so the bar for behavioral disclosure is lower. The description adds meaningful context by explicitly stating 'Returns stored data' and pointing to refresh_brand for freshness — a key behavioral trait that prevents agents from expecting live data. This is valuable context beyond the annotations.

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 two sentences, front-loaded with the core purpose, and every clause earns its place. The example queries and the refresh_brand note are high-value additions with zero waste.

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?

The tool has an output schema (so return format need not be explained), full schema coverage of both parameters, complete usage examples, and a clear alternative-path note. The description covers what the tool does, when to use it, what it returns (stored data), and when not to use it — complete for this complexity level.

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 100%: brand_id is 'Stable identifier of the tracked brand to inspect' and engines is fully documented with its enum options and default behavior. Since the schema handles all parameter semantics completely, the description isn't required to add param info, landing at the baseline of 3.

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 verb ('Get'), the resource (AI visibility data for a tracked brand), and scope (which AI assistants cite the brand, for which prompts, and competitor comparison). It distinctly separates this from siblings like get_visibility_history and compare_competitors by focusing on the current snapshot of citation data.

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 explicit example user queries ('how visible am I on AI?', 'who's citing my brand?', 'show me my AI visibility score') as triggers. Critically, it names a sibling alternative (refresh_brand) and explicitly directs when that should be used instead ('for fresh data, call refresh_brand'), satisfying the when/when-not requirements.

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