Validate whether one or more email addresses are deliverable. For a single email use 'email'. For bulk (up to 50) use 'emails' array. Checks MX records, identifies disposable/role addresses.
| Name | Required | Description | Default |
|---|---|---|---|
| No | Single email address to validate | ||
| emails | No | List of email addresses for bulk validation (up to 50) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is clear. The description adds behavioral detail about checking MX records and identifying disposable/role addresses, which reveals the tool's internal checks. It also states the bulk limit, which is a useful constraint beyond the schema.
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 three short sentences, front-loaded with the core purpose. Every sentence provides distinct information: purpose, parameter selection, and validation checks. No filler or redundancy.
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 simplicity (two optional params, no output schema), the description covers the essential behavioral aspects: what it validates, the batch limit, and the type of checks performed. It could mention the response format, but that is not critical for selection. Overall, it is sufficient for an agent to decide when to use 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 documents both parameters (email and emails), so baseline is 3. The description adds the distinction between single and bulk usage and reinforces the 50-email limit, clarifying when to use each parameter. This adds semantic value beyond the schema's descriptions.
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 uses the verb 'Validate' with a clear resource ('email addresses') and specifies 'deliverable', making the tool's purpose unmistakable. It also distinguishes between single and bulk usage, which aligns with the two parameters. This clearly separates it from sibling tools like find_email or enrich_contact.
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 explicitly says 'For a single email use email. For bulk (up to 50) use emails array', providing concrete guidance on parameter selection. It implies the use case (checking deliverability) but does not explicitly contrast with alternatives like find_email. A clear alternative statement would elevate this, but the guidance is sufficient.
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.
Several tools occupy nearly identical roles (create_contact/add_contacts/save_contacts_to_crm/upload_contacts; add_companies/create_company; search_contacts/search_crm_contacts/find_contacts_at_companies), and the names don't clearly reveal whether they operate on saved or prospected data. Although the descriptions clarify some boundaries, an agent would frequently need to read many descriptions carefully to avoid mis-selection.
Most tools follow a snake_case verb_noun pattern such as list_campaigns, create_deal, and update_contact. Minor deviations like company_intelligence, get_icp, load_more_contacts, and the inconsistent use of add_/create_/upload_/save_ for similar creation actions keep it from being fully consistent.
51 tools is far beyond the well-scoped range and exceeds the 50+ extreme threshold. Even for a broad CRM/prospecting/marketing platform, exposing this many tools at once makes agent selection costly and unwieldy.
Contact and company creation/read/update are covered, but delete is absent across the board, and campaigns can be drafted, listed, and measured but not edited, activated, paused, or deleted. Deals, forms, and landing pages also lack update/delete lifecycle actions, creating meaningful dead ends for common CRM workflows.
