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poisson_boltzmann_view

Color molecular surfaces by Poisson-Boltzmann electrostatic potential: runs PDB2PQR and APBS to compute the map and displays red-white-blue over ±20 kT/e.

Instructions

Colors the molecular surface by true Poisson-Boltzmann electrostatic potential.

Runs PDB2PQR (AMBER force field, pH 7.0) then APBS to compute the full electrostatic potential map. Surface is colored red→white→blue over the range ±20 kT/e. A white cartoon is shown beneath a semi-transparent surface. Organic ligands shown as sticks with yellow carbons.

Requires APBS and PDB2PQR to be installed on the system: brew install brewsci/bio/apbs pip install pdb2pqr

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. It discloses the pipeline (PDB2PQR then APBS), coloring range (±20 kT/e), visual representation (white cartoon, semi-transparent surface, yellow ligands), and external dependencies. It does not mention computational cost or prerequisites beyond installation, but covers the key side effects well.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured and front-loaded with the main purpose, followed by pipeline details and installation commands. It is appropriately sized for a complex tool; no sentences are wasted, though the installation block could arguably be trimmed.

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?

Given the tool's complexity (external tools, specialized view) and minimal schema, the description covers the pipeline, visual output, and dependencies. It omits edge cases like non-protein objects or error states, but the output schema handles return values, making it largely complete.

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 schema has 100% coverage for the single parameter 'obj_name' with a clear description. The tool description does not add parameter-specific meaning, but the schema already provides sufficient information, so the baseline 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 clearly states the tool 'Colors the molecular surface by true Poisson-Boltzmann electrostatic potential', which is a specific verb+resource+scope. It distinguishes itself from generic electrostatic views by mentioning 'true PB' and the PDB2PQR/APBS pipeline.

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?

Usage is implied: use this when you need accurate PB electrostatics. However, there is no explicit comparison to alternatives like 'electrostatic_view' or any when-not-to-use guidance. The installation prerequisites are helpful but do not substitute for direct usage guidelines.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

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