Pymol
Automate repetitive workflows and reduce manual effort
Example: Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
Learn new skills, understand complex topics, get expert guidance
Example: Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Enhance output quality through reviews, suggestions, and refinements
Example: Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
Time estimate: 15-45 minutes depending on use case complexity
Prerequisites
Submit your Claude Code skill and start earning
epx add google-deepmind/science-skills --skill pymolCompatible with
Supported agents
name: "pymol"
description: "Visualize, analyze, and render protein and molecular structures using PyMOL. Use when the user wants to create images of protein structures, perform structural alignments or superposition, measure dis..."
| name | pymol |
| description | > Visualize, analyze, and render protein and molecular structures using PyMOL. Use when the user wants to create images of protein structures, perform structural alignments or superposition, measure distances or contacts, highlight binding sites or active site residues, color by B-factor/pLDDT, or analyze protein-ligand interactions. Do not use for docking, molecular dynamics, or sequence-only analysis. |
uv: Read the uv skill and follow its Setup instructions to ensure
uv is installed and on PATH.All PyMOL commands run on the host via uv with OSMesa software rendering — no
GPU, display, or X server is needed. Structure files must be downloaded to the
host before running PyMOL.
Do NOT use when:
Ensure that uv is installed on the host system. The PyMOL scripts use PEP 0723
headers to declare their dependencies, and uv run will automatically handle
installing them (including pymol-open-source-whl) when the script is executed.
cmd.png() for output. Never use
cmd.draw() or cmd.ray() with hardware acceleration — OSMesa does not
support it. Set environment variable PYOPENGL_PLATFORM=osmesa for headless
rendering..pse session file alongside any PNG output. This lets
the user open the session in their local PyMOL for further inspection.cmd.quit() at the end of every PyMOL script. Omitting it
causes the process to stop responding.from pymol import cmd must come after
finish_launching(), not before.cmd.load(),
always verify it succeeded by checking cmd.count_atoms("all"). If the
result is 0, print an error to stdout and call cmd.quit() immediately.render.py) with the required init
boilerplate and PEP 0723 header.uv run: bash uv run render.pyrender.py)# /// script
# requires-python = ">=3.10, <3.13"
# dependencies = [
# "pymol-open-source-whl",
# ]
# ///
import os
import sys
# Set environment variable for headless rendering
os.environ["PYOPENGL_PLATFORM"] = "osmesa"
import pymol # pytype: disable=import-error
pymol.pymol_argv = ["pymol", "-cq"]
pymol.finish_launching()
from pymol import cmd # pytype: disable=import-error
cmd.load("AF-P00520-F1-model_v4.cif", "structure")
cmd.show("cartoon")
cmd.color("green", "ss h")
cmd.color("yellow", "ss s")
cmd.color("gray", "ss l+''")
cmd.orient()
cmd.set("ray_opaque_background", 1)
cmd.png("output/render.png", width=1200, height=900, dpi=150)
cmd.save("output/session.pse")
cmd.quit()
See references/RECIPES.md for complete, copy-paste ready recipes. Available recipes:
.pse fileoutput/ directory contains PNG images and a .pse session file..pse file in their local PyMOL to further
explore, rotate, or modify the visualization..pse in a new script and
re-run.--max_output_mb limit (default
500 MB). Increase it with --max_output_mb=1000 if needed.AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionpymolExecute the skills CLI command in your project's root directory to begin installation:
epx add google-deepmind/science-skills --skill pymolFetches pymol from google-deepmind/science-skills and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
.cursor/skills/pymol
Restart Cursor to activate pymol. Access via /pymolin your agent's command palette.
Learn more:View source on GitHubSkills CLI docsAbout CursorWhat are agent skills?
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid when
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
latex-posters
K-Dense-AI/scientific-agent-skills · Science · 2 shared tags
hypothesis-generation
K-Dense-AI/scientific-agent-skills · Science · 2 shared tags
citation-management
K-Dense-AI/scientific-agent-skills · Science · 2 shared tags
transformers
K-Dense-AI/scientific-agent-skills · Science · 2 shared tags
exploratory-data-analysis
K-Dense-AI/scientific-agent-skills · Science · 2 shared tags
pytorch-lightning
K-Dense-AI/scientific-agent-skills · Science · 2 shared tags
Useful defaults in pymol — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
Keeps context tight: pymol is the kind of skill you can hand to a new teammate without a long onboarding doc.
pymol reduced setup friction for our internal harness; good balance of opinion and flexibility.
We added pymol from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
Solid pick for teams standardizing on skills: pymol is focused, and the summary matches what you get after install.
pymol is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
pymol has been reliable in day-to-day use. Documentation quality is above average for community skills.
Keeps context tight: pymol is the kind of skill you can hand to a new teammate without a long onboarding doc.
pymol reduced setup friction for our internal harness; good balance of opinion and flexibility.
I recommend pymol for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
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