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pzfreo

build123d-mcp

render_view

Read-only

Render build123d models in 3D or 2D, auto-detecting shape type. Supports PNG, SVG, DXF outputs with adjustable camera angles, object coloring, and clipping for visual inspection.

Instructions

Render model. Auto-detects 3D vs 2D: solids use the VTK tessellation path; 2D shapes (Sketches, edge Compounds, dimensioned drawings) use the ezdxf+matplotlib raster path — review dimensioned drawings the same way as 3D parts. Renders confirm appearance, not geometry — verify booleans with measure() first. format: 'png' (raster, default), 'svg' (HLR line drawing, works without a display), 'dxf' (HLR projection as parseable polylines for downstream 2D CAD), or 'both' (PNG + SVG together). If the PNG path fails (headless host), falls back to SVG automatically. direction: top, front, side, iso. azimuth/elevation: camera rotation in degrees applied after the direction preset. objects: comma-separated names or name:color pairs e.g. 'u_frame:blue,roller:red' (default: all, auto-coloured). quality: standard, high. clip_plane: x, y, z to slice; clip_at: absolute world coordinate along that axis (default: each mesh's midpoint). save_to: optional file path; for format='both' writes .png and .svg. mode: 'auto' (default; no solids + flat in Z = 2D), or '2d'/'3d' to force a pipeline when auto-detection picks wrong (e.g. a Compound mixing a Sketch and a solid routes to 3D); the path used is reported as 'Rendered via pipeline.' colors: optional dict mapping object names and special layer keys (_dims, _labels) to colour names or '#aabbcc'; overrides name:color syntax and the default dimension colour (2D PNG/SVG only; ignored for 3D and DXF). label_objects: when true, each named object is labelled at its centroid in the PNG. highlights: optional list of entities to label, e.g. [{"object": "bracket", "type": "edge", "index": 5, "label": "hinge_edge"}]; type is 'face', 'edge', or 'vertex', index matches shape.faces()/edges()/vertices(); the object must be registered with show() and in the rendered set. Labels are PNG-only.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modeNoauto
colorsNo
formatNopng
azimuthNo
clip_atNo
objectsNo
qualityNostandard
save_toNo
directionNoiso
elevationNo
clip_planeNo
highlightsNo
label_objectsNo
Behavior5/5

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

The description discloses auto-detection logic, fallback behavior, format specifics, object coloring, clip plane operation, and highlight limitations (PNG-only), adding significant context beyond the readOnlyHint annotation.

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 long but well-organized, starting with purpose then detailing parameters, though slightly verbose for some users.

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

Completeness5/5

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

Given 13 parameters and no output schema, the description covers all parameter behaviors, auto-detection, fallback, and limitations, providing complete guidance for effective use.

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

Parameters5/5

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

With 0% schema coverage, the description thoroughly explains all 13 parameters including format values, object syntax, clip plane axis, and highlights structure, effectively compensating for the schema gap.

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 starts with 'Render model' and details auto-detection of 3D vs 2D, formats, and parameters, clearly distinguishing from siblings like 'render_drawing' by its scope.

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 description advises using measure() for geometry verification and explains when to force mode if auto-detection is wrong, but lacks explicit comparison with sibling tools.

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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