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Get AI settings

get_ai
Read-only

GET ONLY the 'AI' field of TitlePublicConfigurationModel. InApp AI generation features of the title - what a PLAYER can generate at runtime through the engine (text/NPC chat, images, video, speech, music, 3D). Enabled is the master switch; Features maps a stable FeatureKey (no '.' or '$') to one feature: its Modality, a Model = the id of a MODE (Text: an AI Coder mode such as "standard") or a TIER (media: an asset generation tier such as "image-balanced") - list the usable ones, with what the publisher's plan allows, with the dashboard action GetInAppAIModels (Text features that AllowImages need a mode that AcceptsImages), Behavior defaults per modality (no platform caps: MaxTokens is bounded only by what the mode's model can produce), Safety prompt checks, an audience Gate (SegmentGate), a Schedule (ScheduleSpec), per-player Limits (LimitSpec) and the in-game PriceOptions the PLAYER pays (in-game resources and/or ONE store purchase per generation - a Purchase entry in the option's base price; never inside PremiumTiers, never two per option). Each generation is charged to the PUBLISHER's credits by the engine at the model's price; per-title spend caps (in credits) live in the PRIVATE config (InAppAIBudget), not here. Server-only section: never sent to the game client or the CDN.

Input Schema

NameRequiredDescriptionDefault
title_idYesTitleID, для которого читаются данные.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, but the description adds real context: the section is server-only and 'never sent to the game client or the CDN', generation is charged to the publisher's credits, and spend caps live in the private config, not here. That goes well beyond what the annotations provide.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The purpose is front-loaded in the first clause, but the remainder is a single sprawling sentence with dense nested parentheses covering modes, tiers, pricing, gates, schedules and limits. Much is necessary detail given no output schema, but the structure is hard to parse.

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?

With no output schema, the description carries the burden of explaining the returned structure and largely does so: Enabled as master switch, Features keyed by FeatureKey, Modality, Model, Behavior, Safety, Gate, Schedule, Limits and PriceOptions. Minor gaps remain (no pagination/format notes), but it is substantially complete for a read tool.

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 the single title_id parameter is already documented, and the description adds no syntax, format, or constraint detail beyond it. Baseline 3 is appropriate when the schema does the work.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource: 'GET ONLY the AI field of TitlePublicConfigurationModel', and clarifies it is the in-app AI generation configuration. This distinguishes it from the broader save_ai and get_title_data siblings, though it never names an alternative explicitly.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no 'use this when/when not' guidance, nor any routing to siblings such as save_ai (write) or list_ai_tiers (enumeration) despite them being obvious alternatives. Usage is only implied by the verb 'GET'.

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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