DYOE Company Research ($0.10)

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

Annotations already cover read-only and open-world status, and the description adds material context beyond them: the concrete data sources (RDAP registry, HTTPS reachability, on-page contact signals, DYOE human-vouch registry), the 'sources disclosed, not a black box' property, and the paid x402/Base pricing model. The gap is that it never says how the $0.10 payment is actually settled (e.g. whether a wallet/approval sibling must be called first), which is the highest-risk unknown for an agent invoking a paid 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?

Front-loaded with the core purpose and deliverable list, then the source-disclosure claim, then input and price — a sensible ordering with no filler sentences. The middle em-dash list is dense and slightly run-on, but every clause carries information.

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?

There is no output schema, so the description carries the return-value burden — and it discharges it by enumerating the dossier contents an agent will receive. Combined with the disclosed sources and the explicit per-call price, an agent has enough to decide, call, and anticipate the response.

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% and there is a single required parameter, so the baseline is 3. The description's 'Input: ?target=domain' restates the parameter name and hints at the expected domain form, but adds no format rules, normalization, or failure behavior beyond the schema's own example.

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 ('Research') and resource ('a company or website') and then enumerates the actual deliverables — legitimacy verdict, domain age, contact paths, social presence, scam red flags. That makes the scope concrete enough to pick over a generic lookup. It does not, however, explicitly differentiate itself from adjacent siblings such as dyoe_verify, dyoe_reputation, or dyoe_audit, which an agent must infer.

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?

'Research a company or website in one call' and 'background checks for agents' imply the use case (consolidated due diligence) but give no explicit when-to-use/when-not and name no alternative tool. Usage is inferable rather than stated, which is the definition of minimum-viable guidance.

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