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Set Agent Onboarding Images

set_agent_onboarding_images

oriiion STAFF ONLY. Turn AI-generated pictures off (or on) for the customer's account (not yours) — when the customer says they do not want AI images, use false and say so in a note. With false, every post is made from their own photos (website, products, listings) and nothing draws a picture for them.

Input Schema

NameRequiredDescriptionDefault
useAiImagesYesfalse: only the customer's own photos, never an AI-generated picture. true: their photos mixed with AI images.
onboardingIdYesThe onboardingId from the routine payload.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already declare it is a non-readOnly, non-destructive write, so the bar is lower; the description still adds real value by disclosing the downstream effect ('every post is made from their own photos... nothing draws a picture for them') and the STAFF ONLY access constraint. It stops short of stating idempotency or reversal behavior explicitly.

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?

The access restriction and target scope are front-loaded, and the sentences are dense with useful content. There is mild redundancy in restating the false-case effect, and the opening token is garbled, but overall it is efficiently sized.

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 2-parameter write tool with full schema coverage and no output schema, the description covers scope, access restriction, and behavioral consequence adequately. It omits only minor operational detail such as whether re-invocation is safe or how failures surface.

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% and both parameters are already documented, so baseline is 3. The description echoes the boolean's meaning and adds a procedural instruction about noting the change, but contributes no syntax or format detail beyond the schema.

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 (set AI-image usage on an agent onboarding) plus an explicit scope qualifier ('for the customer's account (not yours)'). It is distinguishable from neighbors like set_agent_onboarding_brand or set_image_style without opening any schema.

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 gives a concrete trigger condition ('when the customer says they do not want AI images, use false and say so in a note') and a staff-only precondition. It does not name an alternative tool or a when-not-to-call scenario beyond the staff restriction.

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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