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text-em-all

Add an account user

add_account_user
Destructive

MUTATES Text-Em-All data: adds a new user to your account (a master user can do this). Text-Em-All API: POST /v1/account/users. Provide the user's fields via fields using the API's PascalCase names (e.g. UserName, FirstName, LastName, EmailAddress, Permissions). Returns the created user.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fieldsNoAdditional documented Text-Em-All fields to send verbatim in the JSON write body, using the API's PascalCase names (e.g. CallerID, TextNumberID, Lists, RetryTimes). Merged OVER the typed fields above.
lastNameNoLast name (LastName).
userNameNoThe new user's login username (UserName).
firstNameNoFirst name (FirstName).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.9/5.0
Behavior4/5

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

Annotations only give destructiveHint=true, and the description adds real context beyond that: it flags the mutation ('MUTATES Text-Em-All data'), states the master-user authorization requirement, and discloses that the created user is returned. It does not cover irreversibility or what happens to sibling/related records, keeping it out of the top band.

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?

Front-loads the mutation warning and endpoint, then the parameter guidance and return value — a logical, compact order. Slightly padded by an example field list that mostly restates the schema.

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 mutation tool with no output schema, the description compensates by stating the return value ('Returns the created user'), the auth requirement, and how to supply fields. Nothing essential for correct invocation is missing, though irreversibility/error behavior is not addressed.

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 coverage is 100%, so the schema already documents all four parameters including the `fields` merge semantics. The description's PascalCase examples duplicate the `fields` schema description rather than adding new meaning, making the baseline 3 appropriate.

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 ('adds a new user to your account'), names the concrete API endpoint (POST /v1/account/users), and distinguishes itself from update_account_user by being the create operation. An agent can tell what this does without opening the schema.

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

Usage Guidelines3/5

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

Provides a useful precondition ('a master user can do this') but gives no routing guidance relative to alternatives like update_account_user or textemall_request for existing users. Usage is implied by the resource rather than explicitly bounded.

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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