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electrostatic_view

Colors a molecular surface by approximate residue-based electrostatics with a red-white-blue spectrum. Choose atomic or residue charge assignment to display charged regions.

Instructions

Colors the molecular surface by approximate residue-based electrostatics.

Surface is colored red→white→blue via a B-factor spectrum. A white cartoon is shown beneath a semi-transparent surface. Organic ligands shown as sticks with yellow carbons.

For a more accurate Poisson-Boltzmann electrostatic surface, use poisson_boltzmann_view (requires APBS and PDB2PQR to be installed).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modeNoCharge assignment strategy. "atomic" (default) — charges assigned only to terminal charged atoms (e.g. ARG NH1/NH2/NE, LYS NZ, ASP OD1/OD2, GLU OE1/OE2, HIS ND1/NE2). Produces localized color at charge centers with natural falloff to white. "residue" — charges assigned uniformly to all atoms in each charged residue. Produces saturated patches; useful for quickly locating charged regions.atomic
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. It discloses visual behaviors (B-factor spectrum, semi-transparent surface, cartoon beneath, sticks with yellow carbons) and the approximate nature of the electrostatics. It doesn't mention whether the coloring permanently alters the session or any prerequisites, but overall it provides substantial transparency.

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 compact, with a front-loaded purpose and only three short paragraphs. Each sentence adds value: the main function, the visual rendering details, and an alternative tool. No wasted words.

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?

The description covers the tool's purpose, visual output, and alternative, which is sufficient for a 2-parameter tool with a schema. It lacks explicit statements about state changes or limitations, but the behavioral details compensate for the absence of annotations.

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?

Schema description coverage is 100%, with both mode and obj_name described in the input schema. The description does not add parameter-specific details beyond what the schema already provides, so the baseline score of 3 applies.

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 states a specific action ('Colors the molecular surface') with a defined method ('approximate residue-based electrostatics') and resource ('molecular surface'). It also differentiates from the sibling tool poisson_boltzmann_view by noting it is more accurate and requires additional software.

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

Usage Guidelines4/5

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

The description explicitly names poisson_boltzmann_view as a more accurate alternative, providing a clear when-not scenario. However, it does not address relationships to other view tools such as bfactor_view or hydrophobic_surface_view, so guidance is partial.

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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