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Render Model

render_model

Render CPU preview images from iso, front, right, and top views to inspect a 3D model after generation and verify its geometry before handoff.

Instructions

Render CPU preview images (iso, front, right, top) so you can see the model.

Use this after every generation. A model you have not looked at is a guess.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "path": "<path>"
    },
    "name": "render_model"
  }
}

Input Schema

NameRequiredDescriptionDefault
pathYes
sizeNo
viewsNo

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.6.7

TDQS

A3.6/5.0
Behavior3/5

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

With no annotations provided, the description carries the full burden, and 'CPU' is the one genuinely useful behavioral disclosure, telling the agent these previews are fast/approximate rather than raytraced. It says nothing about what happens on an invalid path, where images land, or what the render cost is, which matters for a tool with zero annotation coverage; the presence of an output schema relieves it of describing return values.

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?

Two sentences, nothing wasted, with the capability statement front-loaded and the call-to-action second. The imperative 'A model you have not looked at is a guess' is persuasive rather than filler.

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?

An output schema exists, so return values and image locations needn't be described here, and the description covers purpose and timing well. The remaining gap is parameter documentation for `path` and `size`, which no other structured field supplies given 0% schema coverage.

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 for all three parameters. It only partially does so: the view names (iso, front, right, top) hint at what `views` accepts, but `path` and `size` receive no explanation at all, leaving the agent without the accepted path format or size units.

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?

The description gives a specific verb ('render') and resource ('CPU preview images') and even enumerates the expected views (iso, front, right, top), so the agent knows exactly what it gets. It falls short of a 5 because it never distinguishes itself from look-alike siblings such as make_viewer, inspect_model, or model_card.

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?

The guidance is explicit about timing: 'Use this after every generation,' with a rationale that reframes the call as mandatory verification. It stops short of naming an alternative or exclusion, so the agent still has to guess whether make_viewer or inspect_model is the better choice in some situations.

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