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BananaLead

Find contacts on websites

find_website_contacts

For a list of websites (domains or URLs), reads the home, contact, legal-notice pages and sitemap and returns the emails (verified by SMTP), phones (international format, mobile or landline) and social links each site publishes. Use it after find_local_businesses or with any list of company websites.

Input Schema

NameRequiredDescriptionDefault
countryNo2-letter country to read national phone numbers, e.g. fr
websitesYesDomains or URLs, e.g. "nivon.com"
verify_emailsNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does reasonably well: it discloses the crawling strategy, that emails are SMTP-verified, that phones are normalized to international format, and that social links are collected. It omits operational realities such as credit/rate cost, blocking or failure behavior on unreachable sites, and latency for large lists.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, zero filler: the capability and its outputs come first, the routing hint second. Every clause (pages read, verification method, phone format) earns its place by adding meaning not present in the structured fields.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a 3-parameter tool with no output schema and no annotations, the description covers what it does, what it returns, and when to reach for it. Missing cost/quota expectations and behavior on failed lookups, but the core call decision is fully supported.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 67%, with country and websites already documented inline and only verify_emails lacking a schema description. The description implicitly explains verify_emails via "verified by SMTP" and restates that websites accepts domains or URLs, but adds no new syntax, format, or batching guidance for the 10,000-item limit. Baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb+resource (finds contacts on websites) and goes further to name the exact pages read (home, contact, legal-notice, sitemap) and the three output categories (SMTP-verified emails, international phones, social links). This mechanism-based description lets an agent distinguish it from siblings like find_work_emails or verify_emails without opening any schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

"Use it after find_local_businesses or with any list of company websites" gives explicit triggering context and names a companion tool, so the agent knows the intended workflow entry point. It stops short of saying when NOT to use it (e.g. when you only need work emails for named people) or what it costs per website.

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

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