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

Annotations already establish read-only, idempotent, non-destructive, open-world behavior, and the description adds rich non-obvious context on top: generation runs on Agent Harbor's own hardware with no third-party AI provider, claims are individually validated against scraped evidence with unsupported claims struck and provenance attached, and the failure/charge policy is spelled out.

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?

Content is front-loaded (domain -> returned profile -> validation) followed by short sentences on privacy, billing, and failure policy, with no filler. The first sentence is long and densely packed, but nearly every clause carries decision-relevant 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 must describe returns, and it does: business name, firmographics, and technology-stack summary with provenance. Privacy, validation, idempotent read semantics, and the payment/failure model are all covered, leaving nothing an agent needs in order to call it or interpret a failure missing.

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?

Only one parameter exists and schema coverage is 100%, so the schema fully documents the domain format ('Bare domain, no scheme or path, e.g. mailchimp.com'). The description says only 'Given a company domain' and adds no syntax or edge-case semantics beyond what the schema provides, matching the baseline 3.

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 description names a specific verb (enrich/returns) and resource (validated company profile: business name, firmographics, technology-stack summary) driven by a single domain input. The emphasis on model-written, claim-checked, provenance-bearing output implicitly separates it from raw-scrape siblings like scrape_business and company_card.

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?

Usage context is implied through the billing model ('Costs $0.05 USDC per successful call', 'Not charged on failure'), which lets an agent reason about when it is worth calling. However, there is no explicit when-to-use or when-not guidance, and no sibling such as scrape_business or company_card is named as an alternative.

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