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Clean an email list

clean_email_list
Read-only

Clean a list of email addresses before an import or campaign: dedupes, removes invalid syntax, and (optionally) strips disposable and role accounts. Returns the cleaned list plus a summary of what was removed.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
emailsYesEmail addresses to clean.
remove_disposableNoRemove disposable/throwaway addresses. Default true.
exclude_role_accountsNoRemove role accounts (info@, support@, ...). Default false.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false, and openWorldHint=false, so the safety profile is covered. The description adds real value beyond that: it says what is removed and that the response includes the cleaned list plus a removal summary, so an agent knows mutations are non-destructive transformations of the input.

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?

One front-loaded sentence plus a short return-value clause, with no filler or redundancy. The core action and the notable optional behaviors are stated before the response shape.

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?

No output schema exists, but the description compensates by describing the return (cleaned list plus removal summary). With only three boolean/array parameters and full annotation coverage, nothing essential for a correct call is missing, though edge cases like handling of duplicates across case differences are not mentioned.

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

Parameters4/5

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

Schema coverage is 100%, so the baseline is 3. The description goes slightly beyond the schema by framing the disposable and role-account flags as optional behaviors layered onto the core cleaning pass, helping the agent understand that these are toggles on an otherwise always-on dedupe/validation pipeline.

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 and resource ('Clean a list of email addresses') and enumerates the concrete operations (dedupe, invalid-syntax removal, disposable/role stripping). This is clearly distinguishable from siblings like verify_email, verify_batch, or extract_emails, which validate or extract rather than clean.

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?

Gives clear usage context ('before an import or campaign'), which tells the agent when this tool belongs in a workflow. It does not, however, name or exclude alternatives such as verify_email/verify_batch for validation-only needs, so the routing guidance is contextual rather than explicit.

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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