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pymol

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.

80

Quality

100%

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SKILL.md
Quality
Evals
Security

Quality

Content

100%Weight 40%Scale 1-3

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

A well-structured skill body: concise, fully executable, with a clear validated workflow and appropriate one-level-deep reference files for detail.

DimensionReasoningScore

Conciseness

The body is lean and actionable for a 16-recipe skill: it assumes Claude's competence, explains no basic concepts, and lets each Core Rule and example earn its place rather than padding with tutorial prose.

3 / 3

Actionability

Provides a complete, copy-paste ready minimal script with PEP 0723 header, OSMesa env var, mandatory init boilerplate, and a concrete run command ("uv run render.py"); Core Rules cite specific functions like cmd.png(), cmd.count_atoms(), and cmd.quit().

3 / 3

Workflow Clarity

Sequences the work end-to-end (download structures → Pre-Flight File Check → write script with boilerplate → run via uv → Verify Structure Load via count_atoms → interpret output) with explicit validation checkpoints and an error-recovery path (print error + cmd.quit() when count is 0).

3 / 3

Progressive Disclosure

SKILL.md acts as an overview with clearly signaled, one-level-deep links to references/PYMOL_REFERENCE.md and references/RECIPES.md (both real files), keeping selection syntax and full recipes out of the main file while providing an in-body recipe index for navigation.

3 / 3

Total

12

/

12

Passed

Description

100%Weight 40%Scale 1-3

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

A concise, well-scoped description that names concrete capabilities, supplies explicit use-when and do-not-use-when triggers, and is clearly distinct from adjacent structural-biology skills.

DimensionReasoningScore

Specificity

Lists multiple concrete actions such as "create images of protein structures", "perform structural alignments or superposition", "measure distances or contacts", "color by B-factor/pLDDT", and "analyze protein-ligand interactions" — a comprehensive set of specific capabilities, not vague language.

3 / 3

Completeness

Explicitly answers both what ("Visualize, analyze, and render protein and molecular structures using PyMOL") and when ("Use when the user wants to...") with an explicit trigger clause, plus an anti-trigger ("Do not use for docking, molecular dynamics, or sequence-only analysis").

3 / 3

Trigger Term Quality

Uses natural terms a user would say — "images of protein structures", "structural alignments", "superposition", "binding sites", "B-factor/pLDDT", "protein-ligand interactions" — giving good coverage of common phrasings rather than opaque jargon.

3 / 3

Distinctiveness Conflict Risk

The PyMOL protein-structure niche is distinct and the explicit "Do not use for docking, molecular dynamics, or sequence-only analysis" exclusion sharply reduces the chance of triggering for the wrong skill.

3 / 3

Total

12

/

12

Passed

Validation

100%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
google-deepmind/science-skills
Reviewed

Table of Contents

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