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Create a learner

talentlms_create_user
Destructive

WRITE: create a new LEARNER account in the portal (TalentLMS may email the user, depending on the portal's settings). The user type is always the portal's built-in Learner-Type; this tool cannot create administrators, instructors or any other type (the portal's default type is never used, since it may be an admin type). If the portal has no type named Learner-Type, the tool refuses. Returns the new user's id and type. POST /api/v2/users.

Input Schema

NameRequiredDescriptionDefault
nameYesFirst name.
emailYesEmail address.
loginYesUsername (must be unique in the portal).
localeNoLocale, e.g. en-US.
surnameYesLast name.
passwordYesInitial password (the portal's password rules apply).
timezoneNoIANA timezone, e.g. Europe/Athens.
descriptionNoShort bio.
deactivation_dateNoDate the account becomes inactive automatically (YYYY-MM-DD).
email_notificationsNoWhether the user receives email notifications.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.5/5.0
Behavior5/5

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

Goes well beyond the single destructiveHint annotation: discloses the email side effect and that it depends on portal settings, the type-forcing behavior and its rationale, the hard failure mode when Learner-Type is absent, and the return payload (new user's id and type). That is exactly the operational context an agent needs before a write.

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?

Front-loads 'WRITE: create a new LEARNER account', then layers constraints and the refusal case in short clauses. Every sentence carries distinct decision-relevant information; nothing is redundant with the title or schema.

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

Completeness5/5

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 stating what is returned (id and type). With 10 parameters at full schema coverage, side effects, refusal behavior and endpoint all disclosed, an agent has everything needed to call this correctly.

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%, so every one of the 10 parameters is already documented in the schema, including password rules, unique login, and deactivation date format. The description adds no per-parameter meaning, which is acceptable but places it at the baseline.

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 ('create a new LEARNER account') and immediately narrows scope to the built-in Learner-Type only, so it cannot be confused with generic user management or the group/enrollment siblings. It also names the endpoint (POST /api/v2/users), anchoring what resource is written.

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?

Explicitly states when-not to use it: it cannot create administrators, instructors or any other type, and explains why the portal default type is not used. It also gives a concrete refusal condition ('if the portal has no type named Learner-Type'). It stops short of naming a sibling alternative for non-learner creation, so it is clear context but not a full when/when-not/alternatives triad.

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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