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Glama

run_email_validation

Validate an email address and return deliverability signals to reduce bounces. Use it to check email quality before sending or adding contacts.

Instructions

Validates an email address and returns deliverability signals.

Input Schema

NameRequiredDescriptionDefault
emailYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv1.0.1
    • removedInput schema / properties / email / description
      Removed value: -"Email address to validate."
  2. First observedv1.0.0

TDQS

C2.9/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden. It hints that the call is read-only and returns 'deliverability signals', but doesn't disclose what validation depth is performed (syntax, MX, SMTP probe), whether it requires credentials/rate limits, or how long it takes. Thin for a zero-annotation tool.

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

Conciseness4/5

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

A single front-loaded sentence with no filler; the purpose is stated immediately. It is efficient, though arguably under-specified rather than maximally concise.

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

Completeness3/5

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

For a one-parameter tool with no output schema, the description does say a result set comes back, which is useful. However 'deliverability signals' is vague about what an agent will actually receive (valid/invalid/risky/catch-all?), leaving the return contract underspecified.

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?

Only one parameter and schema description coverage is 0%, but the parameter name ('email') and format are self-evident from the schema. The description adds 'email address' but nothing about format nuance, normalization, or edge cases, so it neither harms nor compensates.

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

Purpose4/5

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

States a specific verb ('validates') and resource ('email address') plus the nature of the result ('deliverability signals'). It is reasonably distinct from run_email_enrichment and run_email_finder in the sibling list, though it never explicitly names those alternatives to draw the boundary.

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

Usage Guidelines2/5

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

No guidance on when to use this versus run_email_enrichment, run_email_finder, or run_linkedin_email, all of which appear in the sibling list. No prerequisites or conditions given; the agent must infer the use case.

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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