poisson_boltzmann_view

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

No annotations are provided, so the description fully covers behavioral traits. It details the computation pipeline (PDB2PQR then APBS), the color range (±20 kT/e), visual elements (white cartoon, semi-transparent surface, stick ligands with yellow carbons), and system requirements. It does not mention side effects like overwriting previous views, but is otherwise transparent.

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

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

The description is concise and well-structured: a purpose sentence, a brief explanation of the method and visual result, prerequisite instructions, and an argument description. Every sentence adds value with no redundancy.

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

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

Given the tool's complexity (external software, multi-step computation) and the existence of an output schema (which the description does not need to cover), the description is adequately complete. It covers purpose, method, visual appearance, prerequisites, and parameter. However, it lacks mention of potential performance impact or that the view is created as a new object.

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

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

The schema provides only type and title for the single parameter 'obj_name', with no description. The tool's 'Args' section adds meaning by stating 'PyMOL object name (e.g. "1abc")', clarifying the parameter's purpose and providing an example. This compensates for the 0% schema coverage.

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

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

The description clearly states the purpose: 'Colors the molecular surface by true Poisson-Boltzmann electrostatic potential.' It specifies the verb 'colors', resource 'molecular surface', and method 'Poisson-Boltzmann', distinguishing from sibling tools like 'electrostatic_view' by emphasizing 'true' PB potential.

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

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

The description mentions a prerequisite (APBS and PDB2PQR installation), which suggests when the tool is usable, but does not explicitly compare to alternatives or state when to use this tool versus other electrostatic views. Usage context is implied but not directly guided.

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