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List email accounts

email_account_list
Read-onlyIdempotent

Mailboxes connected for email steps (Google, Microsoft or IMAP). A campaign with an EMAIL step needs at least one attached via campaign_update → emailAccountIds. Unlike the single LinkedIn account, several mailboxes are allowed and sends rotate across them — ask the user which, do not attach all of them. Connecting a new one is email_account_oauth_url (Google/Microsoft) or email_account_add_imap, both Pro-only.

Input Schema

NameRequiredDescriptionDefault
statusNoFilter by status.
userIdNoRead a SUB-ACCOUNT instead of your own data. Accepted only from an agency owner, and only for an account inside your own agency: take the id from `subaccount_list` and never construct or guess one. An id outside that list is refused. Omit it to read your own data, and name the account to the user when you pass it.
keywordNoFree-text search.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already declare a safe, idempotent read, so the bar is lower; the description still adds real context — multiple mailboxes allowed, sends rotate across them, and account creation is Pro-only. It doesn't mention whether results are paginated or what status/keyword filtering actually does on the returned set.

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?

Four sentences, each doing work: resource definition, dependency, cardinality rule, creation path. Front-loaded with what the tool is; the Pro-only note is a slightly trailing detail but not wasted.

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?

With no output schema and full parameter documentation in the schema, the description covers the operational essentials an agent needs: why this list matters, how many to attach, and where to create new entries. It stops short of describing the shape of a returned account (id, provider, status), which would have made it complete.

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 description coverage is 100% and the schema already explains status, userId (with the subaccount_list constraint) and keyword. The description adds nothing about parameters, so baseline 3 applies.

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?

Opens with a concrete resource definition — 'Mailboxes connected for email steps (Google, Microsoft or IMAP)' — so the agent knows exactly what is enumerated. It distinguishes itself from email_account_get/add_imap by implication rather than explicit contrast, keeping it short of a 5.

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

Usage Guidelines5/5

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

Gives explicit preconditions ('A campaign with an EMAIL step needs at least one attached via campaign_update → emailAccountIds'), an explicit behavioral rule ('ask the user which, do not attach all of them'), and routes to the correct siblings for creating accounts (email_account_oauth_url, email_account_add_imap). It also contrasts against the LinkedIn account case, so the agent knows why cardinality differs.

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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