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Clean an email list

clean_email_list

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.

TDQS

A4.2/5.0
Behavior3/5

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

With no annotations, the description discloses core behavior (deduping, syntax removal, optional stripping) and return value (cleaned list + summary). It lacks details on side effects, authorization needs, or credit consumption, which are expected for an API tool.

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?

The description is two sentences: one short, one longer. It is front-loaded with the core purpose and every sentence is informative without waste.

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 tool with 3 parameters and no output schema, the description adequately covers what it does and what it returns (cleaned list + summary). Minor gaps exist, like error handling or output format details, but it is largely complete.

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 each parameter has a description. The tool description adds value by explaining the overall process (deduping, syntax removal) beyond the boolean switches, providing context that the schema alone does not.

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?

The description clearly states the verb ('Clean') and resource ('email list'), specifying actions (dedupes, removes invalid syntax, optionally strips disposable/role accounts). It implicitly distinguishes from sibling tools like verify_email and verify_batch by focusing on list cleaning before import/campaign.

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?

The description explicitly says 'before an import or campaign', giving clear usage context. It does not name alternatives or state when not to use, but the context is sufficient for an agent to decide.

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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TDQS

A4.2/5.0
Disambiguation5/5

Each tool has a clearly distinct purpose. Overlaps like verify_batch vs submit_bulk are explicitly differentiated by synchronous vs asynchronous behavior. Extraction, cleaning, verification, and management tools are well-separated.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern (e.g., register_account, verify_email, get_job_status). There is no mixing of conventions or vague verbs.

Tool Count5/5

15 tools cover the domain of email verification and account management without redundancy. Each tool fills a specific role—single verification, batch sync, bulk async, job polling, results retrieval, list cleaning, extraction, domain health, credit purchasing, and account management.

Completeness5/5

The tool set provides complete lifecycle coverage: account registration, usage tracking, credit purchase, email verification (single, batch, bulk with async), job management, list cleaning, email extraction, and domain health checks. No obvious gaps for the intended functionality.