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render

Generate a viewable image of the current molecular scene to verify and refine your visualization setup.

Instructions

Renders the current scene and returns the image, so you can see it.

Use this instead of calling ray and png separately — those leave you holding a filename you cannot look at. Call this after setting up a view to check what it actually looks like, and iterate.

Every render is ray-traced, which takes seconds to minutes on a large assembly. ray_trace=False is accepted but ignored: PyMOL's fast unshaded frame grab needs its GUI thread, which this plugin does not run on, so that path wrote blank images. Render smaller to render faster.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
widthNoImage width in pixels. Larger costs render time and context.
heightNoImage height in pixels.
filenameNoOptional path to also keep the PNG at. Without it the render goes to a temporary file that is cleaned up afterwards — except when the image is too large to inline, where the file is kept so you still have the render.
ray_traceNoKept for compatibility and ignored — every render is ray-traced, because PyMOL's unshaded OpenGL capture does not work over this bridge. Use a smaller width/height to render faster.
Behavior5/5

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

No annotations are provided, so the description carries full burden. It discloses ray_trace=False is ignored and why (GUI thread issue, blank images), describes filename cleanup behavior, and warns about ray-tracing performance. This is rich behavioral context beyond any structured metadata.

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?

Adequately sized with front-loaded purpose; all three paragraphs contain necessary information—purpose, usage guidance, and behavioral caveats—with no filler. Every sentence earns its place.

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?

Complete for a complex rendering tool: clarifies purpose, gives usage context, discloses limitations, and addresses parameter semantics. Without an output schema, it still states 'returns the image, so you can see it,' satisfying return-value explanation.

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?

Schema coverage is 100%, but description adds significant meaning: explains ray_trace is a no-op, clarifies filename behavior (temporary vs kept), and links width/height to render speed via 'Render smaller to render faster.' This exceeds the baseline 3.

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 uses a specific verb+resource: 'Renders the current scene and returns the image.' It explicitly distinguishes from siblings by saying 'Use this instead of calling ray and png separately,' making the tool's role unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly provides when to use: 'Call this after setting up a view to check what it actually looks like, and iterate.' It names alternatives (ray, png) and explains why this tool is preferable, fulfilling the when-not and alternative guidance.

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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