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Glama
akontadakis
by akontadakis

preview_scene

Generate a matplotlib PNG preview of a room scene with sensor overlays and configurable rendering options, using the provided OBJ file and optional material map.

Instructions

matplotlib PNG preview of a room with sensor overlays (plan + 3D).

render: 'grid' (grid, plan+3d), 'observers' (plan), 'observers_3d' (3d), or 'all' (all layers, plan+3d). Point layers are given as .pts paths OR inline [x,y,z,dx,dy,dz] rows in the post-north frame; layers left None are simply omitted. Diagnostic overlays only — not a photometric render. material_map OR sidecar required.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
unitsNo
renderNoall
sidecarNo
up_axisNo
grid_ptsNo
obj_pathYes
work_dirNo
material_mapNo
observer_ptsNo
write_prefixNopreview
north_angle_degNo
photosensor_ptsNo
luminaire_groupsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.1/5.0
Behavior4/5

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

No annotations are provided, so the description must carry the full burden. It discloses that it's diagnostic only, that material_map or sidecar is required, that layers left None are omitted, and that point layers can be .pts paths or inline rows. It does not mention potential side effects like file writes, but for a preview tool this is acceptable and the required precondition is clear.

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 dense but front-loaded with the core purpose, then explains key parameters in compact phrasing. Every sentence adds value, and there is no fluff. It is appropriately sized for the complexity, though it could benefit from a clearer breakdown of parameters.

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?

Given 13 parameters and 0% schema coverage, the description covers the most critical aspects: render modes, point layer formats, and the material_map/sidecar requirement. It leaves some parameters (units, north_angle_deg) unexplained, but the tool's core usage is clear. An agent can likely invoke it correctly for basic previews.

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 0%, so the description must compensate. It explains render options, point layers (grid_pts, observer_pts, photosensor_pts), and the material_map/sidecar requirement. However, it does not explain units, up_axis, north_angle_deg, work_dir, write_prefix, or luminaire_groups, leaving those parameters ambiguous.

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 a specific verb (preview) and resource (room with sensor overlays) and specifies the output (matplotlib PNG, plan + 3D). It also distinguishes itself from photometric renders by explicitly saying 'not a photometric render', which helps differentiate from rendering tools like run_image and run_grid.

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 provides clear context for when to use it: it's a diagnostic preview, not a final render, and it requires material_map OR sidecar. It does not name specific alternative tools, but the purpose is distinct enough and the 'not a photometric render' note implies it should not be used for final rendering.

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