Bulk-verify a LIST of email addresses. Submits the whole list, waits for completion, and returns one result per email (same fields as verify_email). Best for cleaning lead lists. Charges 1 Fox Credit per email. Large lists that don't finish quickly return a jobId to poll with get_job.
| Name | Required | Description | Default |
|---|---|---|---|
| wait | No | Wait for results in this call (default true). Set false to just get a jobId. | |
| emails | Yes | Email addresses to verify |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description fully discloses behavior: submits entire list, waits for completion (or returns jobId), returns one result per email, charges per email, and recommends polling for large lists. No contradictions.
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?
Three sentences, each adding value: purpose, behavior/pricing, and fallback for large lists. Front-loaded and no wasted words.
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 lack of output schema, description covers input, behavior, and output format (same as verify_email). It mentions pricing and polling but omits error handling or rate limits. Still reasonably complete for a bulk verification tool.
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% with parameter descriptions. The description adds context on 'wait' behavior (default true, set false to get jobId) and implies email array is a list, but does not add new constraints beyond 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 verifies a list of emails (bulk), using specific verbs and resource. It distinguishes from siblings like verify_email (single) and find_emails (search).
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 says 'Best for cleaning lead lists' and mentions polling with get_job for large lists. It implies use for bulk but does not explicitly exclude single email verification (use verify_email) or when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool has a unique, clearly defined purpose: find_email for single lookup, find_emails for bulk, verify_email for single verification, verify_emails for bulk, plus separate tools for checking credits and polling async jobs. No overlap.
All tool names follow a consistent verb_noun pattern in snake_case (e.g., find_email, verify_emails, get_credits, get_job). The convention is uniform and predictable.
With 6 tools, the server is well-scoped, covering both single and batch operations for finding and verifying emails, plus needed auxiliary functions (credits, job polling). This is optimal for the domain.
The tool set provides a complete workflow: finding emails (single/bulk), verifying emails (single/bulk), checking credits, and handling async jobs. No obvious missing operations for the stated purpose.
