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scene_get_client_ui

Read-only

Reads a saved client interface or control template in full, returning every control and script in the exact structure needed to edit and write it back with replacement.

Instructions

Read a client interface (ui: its name) or a template of client controls (template: its name) back out of a save, whole: every control with its kind, rectangle (and where it differs on a phone or a console), switches, text, picture and colour, grid layout, button states, the scripts on it and the values it gives their variables, where the stick of a gamepad goes. What comes back under interface (or template) is exactly what scene_add_client_ui (scene_add_client_template) takes, so changing an interface is: read it, change what is to change, write it with replace: true. An interface made by hand in the editor is read the same way (the saves configured by hand that the tests keep are read and written back byte for byte). ids gives the id of every control by its path. Read-only.

Input Schema

NameRequiredDescriptionDefault
uiNo
mapPathNo
templateNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.8/5.0
Behavior4/5

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

Beyond the readOnlyHint annotation, it describes the detailed output shape (controls, rectangles, scripts, variable values, etc.), that the output matches what the add tools expect, and that editor‑saved interfaces round‑trip byte‑for‑byte. It doesn't cover edge cases like missing ui/template, but adds substantial 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.

Conciseness3/5

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

The purpose is front‑loaded, but the description is a dense paragraph with a parenthetical about tests that doesn't help an agent decide or call the tool. It could be tightened and structured more clearly.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The output contents and workflow are well described, but the tool has three parameters with zero schema coverage; the absence of any mention of mapPath and the unclear 'ids' statement leave gaps for an agent trying to invoke it correctly.

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

Parameters2/5

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

Schema description coverage is 0%, so the description must compensate. It clarifies ui and template as the two alternative read modes, but completely omits the mapPath parameter, leaving one of three parameters with no semantic explanation.

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 (Read) and resource (client interface / template of client controls), and scopes it as 'whole'. It explicitly links to the write counterparts (scene_add_client_ui, scene_add_client_template), making the read-vs-write distinction clear.

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?

Provides a clear read‑modify‑write workflow ('read it, change what is to change, write it with replace: true') and notes that hand‑made editor interfaces are read the same way. It doesn't mention when to use this vs. scene_list_interface, but the context is strong.

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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