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

Annotations declare a non-read-only, open-world, non-idempotent write, but the description adds the crucial behavioral context those hints only imply: data leaves the system to a third party and must be gated behind user consent, with no fabricated details. It also flags the consent flag's meaning, which an agent otherwise might set carelessly.

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?

Two sentences, front-loaded with purpose, then the precondition workflow and a hard prohibition. Every clause earns its place with no filler.

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 13-parameter, no-output-schema tool, the description covers purpose, required inputs, and the consent gate well. It doesn't say what the caller gets back or what happens after submission, but with no output schema that omission is minor.

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 value by prioritizing which fields must be collected (name, email or phone, summary) and by calling out that quote_url and report_url come from this conversation. It does not explain the enum/interest semantics beyond the schema, so it stays just above baseline.

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 first sentence states a specific verb+resource+destination: it sends the user's contact details and project summary to Holston AI for follow-up. This clearly distinguishes it from all siblings (audit_ai_visibility, build_quote, build_systems_map), which produce artifacts rather than transmit data externally.

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?

Explicit when-to-use and when-not-to-use: collect name, email/phone, and summary, show the user exactly what will be sent, get explicit agreement, and never call without it or with made-up details. The preconditions and prohibitions leave nothing to inference.

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