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.

Quality

94%

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Securityby

Passed

No findings from the security scan

Quality

Content

92%Weight 40%Scale 1-5

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 with an executable example, explicit validation/feedback checkpoints for risky load and batch operations, and clean one-level-deep progressive disclosure into real reference files. Minor conciseness gains are available but overall quality is high.

Dimension	Reasoning	Score
Conciseness	Mostly efficient bullet directives and a lean minimal example, but a few explanatory prose lines ('This lets the user open the session in their local PyMOL for further inspection') could be trimmed; not a 5 due to minor over-explanation.	4 / 5
Actionability	Provides a fully executable, copy-paste-ready minimal script with PEP 0723 header, env setup, init boilerplate, and concrete commands, plus a named catalogue of recipes in RECIPES.md covering the common cases.	5 / 5
Workflow Clarity	Explicit validation checkpoints with feedback loops — Pre-Flight File Check, Verify Structure Load (count_atoms==0 → print error and cmd.quit()), and Auto-detect Alpha-Carbon Trace with conditional recipe — plus a clear Quick Start sequence.	5 / 5
Progressive Disclosure	Body is a concise overview with well-signaled one-level-deep references to references/PYMOL_REFERENCE.md and references/RECIPES.md (both verified to exist), and an inline recipe list serving as navigation; content appropriately split.	5 / 5
	Total	19 / 20 Passed

Description

92%Weight 40%Scale 1-5

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 strong, well-scoped description that concretely enumerates capabilities, provides explicit 'Use when' triggers, and includes negative boundary guidance. Only minor gap is the absence of file-extension synonyms (.pdb/.cif).

Dimension	Reasoning	Score
Specificity	Names the domain (PyMOL, protein/molecular structures) and lists multiple concrete actions — 'create images of protein structures', 'structural alignments or superposition', 'measure distances or contacts', 'highlight binding sites or active site residues', 'color by B-factor/pLDDT', 'analyze protein-ligand interactions' — giving comprehensive coverage.	5 / 5
Completeness	Explicitly answers both 'what' ('Visualize, analyze, and render protein and molecular structures using PyMOL') and 'when' ('Use when the user wants to...') with concrete trigger phrases plus negative boundary guidance.	5 / 5
Trigger Term Quality	Good natural-term coverage including 'images of protein structures', 'superposition', 'binding sites', 'B-factor/pLDDT', 'protein-ligand interactions', but missing common synonyms and file extensions (.pdb, .cif) that would lift it to 5.	4 / 5
Distinctiveness Conflict Risk	Clear niche (PyMOL molecular visualization) with distinct triggers and an explicit 'Do not use for docking, molecular dynamics, or sequence-only analysis' boundary minimizing conflict risk.	5 / 5
	Total	19 / 20 Passed

Validation

100%

Warnings & errors only

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

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository: google-deepmind/science-skills
Path: skills/pymol/SKILL.md
Commit: 6883275

Reviewed: 21 days ago

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