Emails And Contacts

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

No annotations exist, so the description carries the full burden. It discloses async behavior, performance expectations ('crawl/enrichment to take longer'), and progress tracking via requests_get. It does not mention rate limits or auth requirements, but for a contact-discovery tool these are less critical.

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?

Well-structured bullets, front-loaded with a one-sentence summary. Some redundancy between 'Best for' and 'Prefer this tool when' sections, but overall each line conveys distinct usage guidance.

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?

Given the output schema and full parameter descriptions, the description covers purpose, selection criteria, execution modes, and a key alternative. It could mention more edge cases (e.g., rate limits, validation use cases) but is largely complete.

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 has 100% description coverage for all 5 params. The description adds domain/URL context for the query field and explains when to use async mode, but it does not go beyond schema for webhook or preferred_contacts.

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 opening line uses a specific verb ('Find') and identifies exact data types (emails, phones, social/contact data) and scope (company domains). It explicitly differentiates from company_insights by contrasting contact data vs. company metadata.

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?

Provides explicit 'Prefer this tool when' conditions, async-mode guidance, and a named alternative ('Use company_insights instead when...'). This tells the agent both when to select and when to avoid this tool.

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