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Glama

rupa_cad_ubah

Destructive

Transform a CAD shape by moving, rotating, scaling, or mirroring it, then verify its volume against expected mathematical changes to detect incorrect transformation matrices.

Instructions

Geser, putar, skala, atau cermin sebuah bentuk. Volumenya diperiksa terhadap yang DIHARAPKAN secara matematis: geser dan putar tidak boleh mengubahnya sama sekali, skala mengubahnya pangkat tiga. Transformasi yang menggeser volume adalah gejala matriks yang salah, dan itu tidak terlihat sampai ada yang mengukur.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
keNoNama bentuk di ruang CAD; satu segmen, tanpa pemisah jalur.
namaYesNama bentuk di ruang CAD; satu segmen, tanpa pemisah jalur.
geserNo
ruangNoNama ruang kerja; tiap ruang punya adegan.blend sendiri.utama
skalaNo
putar_sudutNoDerajat.
putar_sumbuNo
putar_titikNo
cermin_normalNo

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?

Beyond the destructiveHint annotation, the description reveals a volume-check behavior: it verifies that the transformation matches mathematical expectations (e.g., scale changes volume cubed). It also warns that volume shifts indicate a faulty matrix, providing valuable diagnostic context that the annotations do not cover.

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

Conciseness5/5

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

The description is two sentences, front-loading the core action and following with a concise behavioral note. There is no extraneous information; every sentence contributes meaning and the structure is efficient.

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 nine parameters and no output schema, the description is minimal. It does not clarify whether multiple transformations can be combined in one call or whether they are exclusive, which is a notable gap given the schema permits all parameters. It also omits any mention of error conditions or prerequisites beyond the volume check.

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?

The schema description coverage is 44%, and the tool description lists the operations but does not map them to specific parameters (e.g., 'geser' for translation, 'putar_sudut' and 'putar_sumbu' for rotation). The description adds general context about operations but does not compensate for the missing parameter-level details, leaving some ambiguity about how each parameter is used.

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 clearly states the verb (translate, rotate, scale, mirror) and the object (a shape) in the first sentence. It distinguishes the tool as a transformation operation, which is distinct from creation, measurement, or other sibling tools. The operations are specific and unambiguous.

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?

The description does not specify when to use this tool versus alternatives like shape creation or boolean operations. It mentions no prerequisites, conditions, or when-not-to-use guidance, leaving the agent to infer the appropriate context from the operation names alone.

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