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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false. The description adds valuable behavioral detail: it probes each entity via ai_visibility_check, ranks by score, surfaces most/least recognized, and returns a ranked list with score/confidence/signal density. It goes beyond annotations without contradicting them.

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 three sentences, front-loaded with the main action, then process, then use case and output. The example quote adds helpful context without redundancy. Every sentence 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?

No output schema exists, so the description properly explains return values (ranked list with score, confidence, signal density). It covers purpose, process, and use case. It doesn't mention first-entry-subject handling (but schema does) or potential cost/time implications, but for a moderate-complexity tool with rich annotations and 100% schema coverage, it is sufficiently complete.

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 100%, so baseline is 3. The description reinforces that entities are 'your brand + N competitors' but does not add significant meaning beyond the schema's per-parameter descriptions. It doesn't elaborate on the models/_apiKey interplay or context parameter beyond what schema already provides.

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 uses a specific verb 'Compare' with a clear resource 'AI visibility across multiple entities side-by-side.' It distinguishes from the sibling ai_visibility_check by explicitly describing multi-entity comparison and ranking, while also referencing the underlying probe mechanism. This makes the purpose unmistakable.

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 an explicit use case ('competitive AI-marketing audits') with a concrete example query. It implies the single-entity alternative (ai_visibility_check) by saying 'across multiple entities,' but does not explicitly state 'use ai_visibility_check for a single entity' or mention when not to use this tool. Clear context but no formal exclusions.

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