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Create Test User

create_test_user

Create a test user to prove sign-in works: a generated email and password, in its own workspace named "[test] …" and marked as a test fixture (no plan, no emails sent). Returns the email and the generated password; pass them to verify_login. Test-user sign-ins never count as real ones. On a production Bridge environment, or when the app's Stripe keys are live, the call is refused unless confirm repeats the app's exact name — ask the user first. Same as bridge test-user create. Before writing app code that signs users in, call get_integration_guide with topic=auth and the framework the app uses.

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.
confirmNoOnly needed on production or with live Stripe keys: the app's exact name, repeated after the user agreed. Do not supply it on your own initiative.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.8/5.0
Behavior5/5

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

Goes well beyond the annotations (readOnlyHint=false, destructiveHint=false, idempotentHint=false): it discloses that no plan is attached, no emails are sent, test sign-ins never count as real ones, and that the call is refused on production/live Stripe unless confirm repeats the exact app name. This is rich, non-obvious behavioral context.

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?

Purpose and return values are front-loaded, and each sentence adds distinct value (return payload, test-fixture semantics, production guard, CLI equivalence, auth-guide routing). It runs long at five sentences, but none is disposable filler, so the length is largely earned.

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?

Given no output schema, the description supplies the return values (email and generated password) and their downstream use. It covers the mutation's side effects, the refusal guard, and follow-up calls, leaving nothing an agent needs in order to invoke it correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so both parameters are already documented. The description nonetheless adds meaning: it explains the confirm-trigger condition (production or live Stripe keys) and that confirm is the app's exact name repeated only after user agreement, reinforcing the schema's 'do not supply on your own initiative' note.

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 (create) and resource (test user) with exact scope: a generated email/password, its own '[test] …' workspace, marked as a test fixture. This is clearly distinguishable from siblings like invite_user, create_tenant, and get_user, which create or fetch real users/workspaces.

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?

Explicitly routes to alternatives: 'pass them to verify_login' after creation, and 'Before writing app code that signs users in, call get_integration_guide with topic=auth.' It also names the refusal condition on production/live-Stripe and instructs the agent to ask the user first, covering when-not-to-invoke without prompt.

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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