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

Annotations already cover the safety profile (readOnlyHint=true, destructiveHint=false), yet the description goes well beyond them: payment mechanism (x402, $9 USDC in _meta['x402/payment']), conditional billing tied to a 12/16 engine-answer threshold, 2-4 minute runtime, and what happens on invalid input or failed runs (error, not charged). That is exactly the beyond-annotation context the dimension rewards.

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?

It leads with what the tool produces, then covers cost and timing, then failure behavior. It is dense but every sentence earns its place, particularly the return-value enumeration, which substitutes for the absent output schema.

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 no output schema, the description carries the full burden of explaining returns and does so item by item (per-engine answers, mention rate, domain citations, visibility score, competitor share overall and per engine, cited sources, report_url). Combined with payment, latency, and error semantics, an agent can call and interpret this correctly.

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%, so url, brand, and topic are already fully documented with defaults in the schema, making 3 the baseline. The description adds no parameter-level syntax or formatting detail beyond what the schema supplies.

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+resource: a '16-engine AI visibility report' with the exact method (five category questions asked 3 times, 240 answers) and the exact engine list. That precision separates it cleanly from siblings scan_site and pricing without opening either schema.

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 cost ($9 USDC), latency (2-4 minutes), and billing condition (not charged unless 12 of 16 engines answer) give decision-relevant context for choosing it, but the description never states when to prefer this over scan_site or pricing, nor any exclusions. Usage is implied by the expense/depth signals rather than stated.

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