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3d-molecule-ray-tracer

Generate photorealistic rendering scripts for PyMOL and UCSF ChimeraX.

skill-install — Terminal

Install via CLI (Recommended)

clawhub install openclaw/skills/skills/aipoch-ai/3d-molecule-ray-tracer-1
Or

3D Molecule Ray Tracer

Advanced molecular visualization tool that generates professional-grade rendering scripts with cinematic effects for creating publication-quality and cover-worthy molecular images.

When to Use

  • Use this skill when the task is to Generate photorealistic rendering scripts for PyMOL and UCSF ChimeraX.
  • Use this skill for data analysis tasks that require explicit assumptions, bounded scope, and a reproducible output format.
  • Use this skill when you need a documented fallback path for missing inputs, execution errors, or partial evidence.

Key Features

See ## Features above for related details.

  • Scope-focused workflow aligned to: Generate photorealistic rendering scripts for PyMOL and UCSF ChimeraX.
  • Packaged executable path(s): scripts/main.py.
  • Structured execution path designed to keep outputs consistent and reviewable.

Dependencies

Example Usage

See ## Usage above for related details.

cd "20260318/scientific-skills/Data Analytics/3d-molecule-ray-tracer"
python -m py_compile scripts/main.py
python scripts/main.py --help

Example run plan:

  1. Confirm the user input, output path, and any required config values.
  2. Edit the in-file CONFIG block or documented parameters if the script uses fixed settings.
  3. Run python scripts/main.py with the validated inputs.
  4. Review the generated output and return the final artifact with any assumptions called out.

Implementation Details

See ## Workflow above for related details.

  • Execution model: validate the request, choose the packaged workflow, and produce a bounded deliverable.
  • Input controls: confirm the source files, scope limits, output format, and acceptance criteria before running any script.
  • Primary implementation surface: scripts/main.py.
  • Parameters to clarify first: input path, output path, scope filters, thresholds, and any domain-specific constraints.
  • Output discipline: keep results reproducible, identify assumptions explicitly, and avoid undocumented side effects.

Quick Check

Use this command to verify that the packaged script entry point can be parsed before deeper execution.

python -m py_compile scripts/main.py

Audit-Ready Commands

Use these concrete commands for validation. They are intentionally self-contained and avoid placeholder paths.

python -m py_compile scripts/main.py
python scripts/main.py --help

Workflow

  1. Confirm the user objective, required inputs, and non-negotiable constraints before doing detailed work.
  2. Validate that the request matches the documented scope and stop early if the task would require unsupported assumptions.
  3. Use the packaged script path or the documented reasoning path with only the inputs that are actually available.
  4. Return a structured result that separates assumptions, deliverables, risks, and unresolved items.

Metadata

Author@aipoch-ai
Stars4473
Views2
Updated2026-05-01
View Author Profile
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Add to Configuration

Paste this into your clawhub.json to enable this plugin.

{
  "plugins": {
    "official-aipoch-ai-3d-molecule-ray-tracer-1": {
      "enabled": true,
      "auto_update": true
    }
  }
}
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