find_emails

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

With no annotations provided, the description carries the full burden and performs well by disclosing specific behaviors: it scrapes websites, generates pattern-based candidates from a contact name, verifies via SMTP, and returns emails sorted by confidence score. This goes well beyond a simple 'find emails' statement, though it does not mention rate limits or failure modes.

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?

The description is tightly structured in three sentences: purpose, process, and unique value proposition. Each sentence contributes substantive information without redundancy, making it appropriately sized and front-loaded.

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 tool's moderate complexity (multi-step pipeline) and the absence of an output schema or annotations, the description covers the essentials: what it does, how it works, and what it returns (verified emails sorted by confidence). It omits potential edge cases or caveats, but remains largely complete for an agent to understand when and how to invoke it.

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?

The schema already provides 100% description coverage for all three parameters, so the baseline is 3. The tool description adds minimal extra parameter-specific meaning, though it does connect the contact_name parameter to the pattern-generation process, which is a slight enhancement over the schema.

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 clearly states the tool's function: 'Find email addresses for a business.' It then details the process (scraping, pattern generation, SMTP verification) and differentiates itself from siblings by framing it as a 'Hunter.io replacement' for comprehensive email discovery, distinguishing it from verify_email and verify_emails_batch.

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?

The description offers clear context for when to use the tool (when you need to find and verify business emails) and even notes that it requires no API key. However, it does not explicitly state when not to use it or point to alternative sibling tools like verify_email, so it lacks explicit exclusions/alternatives.

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