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

Annotations cover readOnlyHint/openWorldHint, and the description goes well beyond them: it discloses determinism, that no LLM is in the lookup path, the $0.20 USDC x402 price, and the full unpaid-call recovery flow (PaymentRequired challenge + retry with signed payload in _meta). That payment/auth protocol is exactly the operational context annotations cannot express.

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?

Information-dense and front-loaded: identity → scope limits → sibling disambiguation → determinism → payment. Each sentence carries a distinct fact, though the long parenthetical citation and price/payment block make it heavier than strictly necessary for tool selection.

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?

For a read-only, no-output-schema lookup, the description covers selection, scope, sibling boundaries, and the payment barrier, which is what an agent needs to invoke it. It does not describe the shape of the returned feasibility data, a minor gap given no output schema exists to carry that.

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 the baseline is 3, but the description adds real query semantics: it establishes the closed vendor set, notes the 'at least one of technique, vendor, or campaign' rule, and states which techniques actually succeeded, letting the agent judge which values yield signal. It stops short of documenting value syntax beyond what the schema already carries.

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 ('deterministic lookup against one specific empirical study') with a named citation, subject matter, and conclusion (1.08% success rate). It explicitly distinguishes itself from the two closest siblings, /ot/ai-exposure and /ot/ai-uplift, so an agent can route correctly without opening schemas.

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?

Names both alternatives and what each covers, and the scope constraints ('only 3 vendors tested', 'only Network/Register-Tags ever succeeded') implicitly define when results are meaningful. However, there is no explicit 'use this when / use the sibling when' construction; the agent must infer the selection condition from the parentheticals.

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