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

With no annotations, the description carries the entire burden and does so thoroughly: it discloses the return structure (signals with source/source_url/verified_at, three 0-100 scores, checks with evidence and lookup links, a headline read and recommendation), the cost ('counts as 2 checks'), the API-key requirement, the degraded path for personal webmail (individual_or_unverified, no scores), that a possible list match is only 'review', and that message is hashed and never stored.

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-loads the when-to-call and the primary inputs before diving into the return shape and caveats, so the most decision-relevant content comes first. It is dense and much of the middle is a single run-on enumeration of outputs, which costs some readability, but almost every clause carries actionable 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?

For a 19-parameter tool with no output schema and no annotations, the description is unusually complete: it explains inputs, the output payload, scoring ranges, recommendation values, cost, auth requirement, and edge-case behavior. An agent would know both when to call it and what to expect back.

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 the schema already documents all 19 parameters including enums and formats. The description only loosely maps inputs ('the sender's e-mail or the company domain, the company name, the context') without adding format or interaction semantics beyond what the schema states. Baseline 3 is appropriate.

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 ('qualify' a business that contacted you) and immediately scopes it to an inbound form submission, inquiry or outreach reply. It is clearly distinguishable from check_email, screen and verify_business because it describes a multi-source qualification report rather than a single lookup.

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?

Gives a clear trigger ('Before you engage with a business that contacted you') plus hard boundaries ('Businesses only', 'Requires an API key', 'Not for credit, employment, insurance or housing decisions about any person'). It does not explicitly contrast itself with the sibling tools (screen, verify_business, check_email), so the alternative-selection guidance is implied rather than stated.

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