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tiranyx

rupa3d

by tiranyx
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rupa_tekstur_buat

Destructive

Bake Blender procedural materials into image maps (albedo, roughness, normal, occlusion) so glTF export preserves textures instead of flat gray.

Instructions

Bangun material PROSEDURAL di Blender, PANGGANG jadi peta gambar, lalu ganti materialnya dengan yang berbasis gambar supaya bisa diekspor.

Langkah terakhir itu yang paling mudah terlupa dan paling mahal: material prosedural Blender TIDAK BISA diekspor ke glTF sama sekali. Eksportirnya cuma mengerti nilai tetap dan peta gambar, jadi material prosedural yang indah di Blender terbit ke web sebagai ABU-ABU RATA, tanpa satu pun peringatan.

Tiga hal yang menentukan hasilnya: node gambar harus AKTIF sebelum bake (kalau tidak Blender memanggang ke tempat tak tentu dan diam saja); bake DIFFUSE bawaannya menyertakan pencahayaan sehingga bayangan lampu ikut terpanggang ke albedo; dan ruang warna harus disetel SEBELUM disimpan — albedo sRGB, sisanya Non-Color.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
gayaNobatu
jenisNo
objekNoNama mesh; kosong = yang terbesar di adegan.
ruangNoNama ruang kerja; tiap ruang punya adegan.blend sendiri.utama
contohNo
keluarYesDirektori tujuan peta PNG.
ukuranNo
kuat_bumpNoKekuatan relief yang dipanggang ke normal map. Terlalu rendah menghasilkan peta yang praktis RATA — sah, tetapi memakan VRAM penuh tanpa membawa informasi. Terukur: 0,6 memberi jangkauan 125–130 dari 0–255; 2,0 memberi peta yang benar-benar berisi.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.6.2

TDQS

A3.7/5.0
Behavior4/5

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

Annotations declare destructiveHint=true, and the description reinforces this by mentioning replacing materials. It adds valuable behavioral details beyond annotations: the need for an active image node, the lighting inclusion in diffuse bake, and color space requirements. This enriches the agent's understanding of side effects and prerequisites.

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 structured in three clear paragraphs: action, export warning, and key gotchas. It is somewhat long but every sentence contributes valuable information. The critical pitfall is front-loaded in the second sentence, making it immediately visible.

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?

For a tool with 8 parameters, no output schema, and destructive behavior, the description covers the process and pitfalls but omits explanation of several parameters and the output format (beyond the schema's 'PNG' hint). It is adequate for understanding the workflow but not fully complete for parameter selection and expected results.

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 50%, and the description does not add any parameter-specific meaning. It focuses on the process and pitfalls, leaving parameters like gaya, jenis, contoh, and ukuran undocumented both in schema and description. The description does not compensate for the missing schema descriptions.

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 states a specific verb sequence (build procedural material, bake to image maps, replace with image-based material) and the resource (Blender material). It clearly distinguishes this tool from sibling rupa_bake by covering the full pipeline, not just baking. The export motivation is explicit.

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 description implies usage when exporting to glTF and explains the procedural material limitation, but it does not explicitly name alternatives or exclusion conditions. It gives context for when to use this tool but leaves the agent to infer that rupa_bake might be for baking-only scenarios.

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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