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Glama

rupa_adegan_aset

Destructive

Register a GLB file into a 3D scene while capturing its file size, bounding box from glTF accessor min/max, and embedded certificate. Detect scale errors early without loading the mesh, preventing issues before publication.

Instructions

Daftarkan GLB ke adegan. Yang dicatat bukan cuma jalurnya: ukuran berkas, KOTAK BATAS (dibaca dari accessor min/max glTF, tanpa memuat mesh), dan SERTIFIKATNYA kalau ada. Kotak batas itu yang membuat kesalahan skala bisa ditangkap sebelum terbit — kesalahan skala tidak muncul di daftar node, tidak menggagalkan apa pun, dan baru ketahuan kalau kebetulan kameranya menghadap ke sana.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kunciYesNama pendek untuk menyebut aset ini di node.
ruangNoNama ruang kerja; tiap ruang punya adegan.blend sendiri.utama
berkasYesJalur absolut .glb

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.6.2

TDQS

A3.9/5.0
Behavior4/5

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

The description adds meaningful non-obvious behavior beyond the annotations: it reads the bounding box from glTF accessor min/max without loading the mesh, records file size and certificate if present, and explains why bounding box matters for catching scale errors. This is valuable context that annotations do not convey. There is no contradiction with the destructiveHint.

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 description is three sentences and efficiently front-loads the core action. The first two sentences deliver the essential behavior, and the third explains the value of the bounding box in a memorable way. It is slightly discursive but not bloated.

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 tool with three simple parameters, no output schema, and destructive annotations, the description covers the core behavior, special recording behavior, and an important use case. It does not describe return values, but that is not critical here. The omission of explicit output details is a minor gap.

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 schema already documents all three parameters. The description adds little parameter-level meaning beyond mentioning 'jalur' and the concept of what gets recorded, but it does not clarify parameter formats or relationships beyond the schema. Baseline 3 is appropriate.

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?

The description opens with a clear, specific action: 'Daftarkan GLB ke adegan' (register GLB into the scene), which names both the verb and the resource. It then distinguishes itself from loading tools by explicitly stating it does not load the mesh, and enumerates what is recorded (file size, bounding box, certificate). This makes the tool's unique role among the many rupa_* siblings clear.

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

Usage Guidelines3/5

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

The intended use is implied by the purpose statement and reinforced by the rationale about catching scale errors before publication. However, the description does not explicitly compare this tool to alternatives like rupa_muat or rupa_proksi, nor does it provide when-not-to-use guidance. It offers context but no direct routing.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.