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Get User

get_user
Read-onlyIdempotent

Get one user of a tenant by EMAIL. Arguments: tenantName (the tenant NAME from list_tenants), email (the user, as shown by list_users). Returns the full user record — role, enabled, onboarded, teams, custom params and the tenant it belongs to. Fails with USER_NOT_FOUND when nobody in the tenant has that email, and USER_AMBIGUOUS when more than one record matches.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
appNoId of the Bridge app to act on for this call (see list_apps). Omit to use the current app.
emailYesEmail address of the user, as list_users shows it.
tenantNameYesTenant NAME from list_tenants (a tenant id is accepted as a fallback).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, non-destructive, closed-world behavior, so the safety profile is covered. The description adds genuinely new behavioral detail: the shape of the returned record (role, enabled, onboarded, teams, custom params, tenant) and two named failure modes (USER_NOT_FOUND, USER_AMBIGUOUS), including the ambiguity condition.

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?

Purpose is front-loaded in the first clause, followed by argument sourcing, return contents, and error semantics in tight sequence. No filler sentences and every clause carries information.

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?

With no output schema, the description compensates by naming the returned fields, and it covers the two realistic failure paths. The optional `app` parameter is documented in the schema, so nothing needed to call this tool correctly is missing.

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 all three parameters are already documented, including the id-as-fallback for tenantName. The description restates the two required parameters without adding format or constraint detail beyond the schema, so the baseline 3 applies.

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 precise verb+resource+key ("Get one user of a tenant by EMAIL"), which unambiguously separates it from list_users, get_tenant, and update_user. The scope (single user, scoped to a tenant, keyed by email) is fully specified in the first sentence.

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?

It explains where each required argument comes from ("tenantName ... from list_tenants", "email ... as shown by list_users"), which effectively routes the agent through prerequisite list calls. It stops short of stating when to prefer this over alternatives or any exclusions, so it is clear context rather than full when/when-not guidance.

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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