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Add team member

add_team_member
Destructive

Add one human teammate to the current company by email. Creates a Command Center approval card (sensitive, every call). On approve: invite email + roster row. Required: email, role (job title, or team / manager). Optional: name. No bulk. No permission designer — team is the default access; pass role=manager for the manager preset. Use when the operator (or CoS) needs to add a person who is not yet on get_team_members.

Routing: Add / invite a human teammate by email → this tool (approval card). For AI agents use interview_for_hire. To see who is already on the company use get_team_members.

[sensitive-tier — EVERY call needs a manager's approval (per-send human rail): each request queues its own approval card and sends exactly once on approve. There is no standing grant for this tool. Call it on the first clear ask; the card is the yes — do not re-ask in chat.]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameNoOptional full name (e.g. "Yuichi Ichi"). If omitted, derived from the email local-part.
roleYesJob title (stored on their profile) or access preset: team / manager. Other strings are titles on the team preset.
emailYesInvitee email. Must be the exact address — never guess.
companyIdYesFreedomOS company id to act within (you must be a member). Required for company-scoped tools.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.7/5.0
Behavior5/5

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

Annotations already declare destructiveHint=true and readOnlyHint=false, and the description adds meaningful behavioral context beyond that: every call creates an approval card, sends exactly once on approve, requires per-call manager approval, and has no standing grant. The 'do not re-ask in chat' note is particularly useful operational guidance.

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 dense but well-structured: the core action is front-loaded, followed by requirements, exclusions, routing, and sensitive-tier guidance. Every sentence adds operational value, and the formatting makes the approval behavior and routing easy to scan.

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?

For a mutation tool with no output schema, this description is remarkably complete: it covers the action, prerequisites, required and optional fields, approval behavior, exactly-once sending, exclusions, and sibling-tool routing. An agent has everything needed to invoke it 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?

The input schema already has 100% coverage, clearly describing email, role, name, and companyId. The description reinforces the required/optional split and role presets ('team / manager'), but does not add significant new parameter-level meaning beyond what the schema already provides. Baseline 3 is 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?

The description clearly states the verb and resource: 'Add one human teammate to the current company by email.' It also differentiates itself from sibling tools by explicitly routing AI agents to interview_for_hire and existing member checks to get_team_members.

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?

The description says exactly when to use this tool ('not yet on get_team_members'), names the alternative for AI agents (interview_for_hire), and gives exclusions such as 'No bulk' and 'No permission designer.' It also explains the approval workflow and when to invoke the tool, leaving no ambiguity about routing.

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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