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hydrophobic_surface_view

Idempotent

Colors a PyMOL molecular surface by amino acid hydrophobicity to reveal hydrophobic, polar, and charged regions for protein interaction 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

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

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv1.5.1
    • addedInput schema / properties / obj_name / description
      Added value: +"PyMOL object name (e.g. \"1abc\")"
  2. First observedv1.2.1

TDQS

B3.2/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=false, destructiveHint=false and idempotentHint=true, so the safety profile is covered. The description adds a detailed picture of the resulting scene (surface coloring, white cartoon beneath, ligand sticks with yellow carbons), which is useful, but it does not warn that existing representations may be replaced or that a loaded object is required.

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 primary purpose is front-loaded in one sentence, followed by a structured color legend. The legend is somewhat long but is the most decision-relevant content for a visualization tool, so it largely earns its place.

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

Completeness3/5

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

For a one-parameter view tool with an output schema and full annotation coverage, the definition is adequate but leaves gaps: no routing versus sibling views and no note that it mutates the current scene and requires a preloaded object.

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% for the single obj_name parameter, so the baseline is 3. The description adds no meaning about obj_name or its format beyond the schema's 'PyMOL object name (e.g. "1abc")'.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The first sentence gives a specific verb and resource: colors the molecular surface by amino acid hydrophobicity. It is clearly distinguishable from generic color/cartoon siblings, though it never names which sibling view (e.g. composition_view, electrostatic_view, conservation_view) an agent should choose instead.

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

Usage Guidelines2/5

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

There is no when-to-use guidance, no mention of alternatives among the many *_view siblings, and no prerequisites (the object must already be loaded). Usage is only implied by the semantics of the view itself.

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