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hydrophobic_surface_view

Color molecular surfaces by amino acid hydrophobicity to identify hydrophobic, polar, and charged regions for protein analysis.

Instructions

Colors the molecular surface by amino acid hydrophobicity.

Orange = hydrophobic (ILE, VAL, LEU, PHE, MET, ALA, TRP, PRO), white = polar (SER, THR, CYS, TYR, ASN, GLN, GLY), sky blue = positively charged (ARG, LYS, HIS), salmon = negatively charged (ASP, GLU). A white cartoon is shown beneath a semi-transparent surface. Organic ligands shown as sticks with yellow carbons.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
obj_nameYesPyMOL object name (e.g. "1abc")

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

With no annotations, the description carries the full burden of disclosure. It thoroughly describes the visual outcome: exact colors for amino acid categories, a white cartoon beneath a semi-transparent surface, and ligand rendering with yellow carbons. It does not mention reversibility or interaction with existing display styles, but the main behavioral effect is well specified.

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?

The description is concise and well-structured, front-loading the core purpose and then listing color mappings in a clear, scannable format. Every sentence adds specific visual information without unnecessary padding.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple one-parameter visualization tool, the description covers the key visual outcomes and distinguishes the tool from numerous sibling views. It does not mention prerequisites like a loaded structure, but that is implied by the obj_name parameter. An output schema exists, so return values need not be described.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The only parameter, obj_name, is already fully described in the schema with an example, providing 100% schema coverage. The description adds no extra parameter information, so the baseline of 3 is appropriate.

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 starts with a specific verb and resource: 'Colors the molecular surface by amino acid hydrophobicity.' It clearly defines the tool's function and the detailed color mapping distinguishes it from other view tools such as electrostatic_view or bfactor_view.

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

Usage Guidelines3/5

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

The description implies when to use the tool (when a hydrophobicity-colored surface is desired) but provides no explicit guidance on alternatives or exclusions. It does not mention other view tools or state when not to use this visualization.

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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