mutation_view

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

The description details the visual output but does not explicitly state that the tool is non-destructive or read-only. With no annotations, this is adequate for a visualization tool, but lacks explicit safety guarantees.

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 brief purpose sentence followed by detailed visual output, mutation format, and parameter explanations. Every sentence adds value without 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?

The description covers the visual output and parameter meanings thoroughly. It lacks mention of prerequisites (e.g., structure must be loaded) but overall provides sufficient context given the output schema exists.

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 input schema provides no descriptions (0% coverage), so the description carries full burden. It explains 'obj_name' as a PyMOL object name and 'mutations' as a comma-separated list with format examples and optional chain prefix, adding critical meaning.

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 tool's purpose: highlighting mutated residues on a protein structure. It provides specific visual details (magenta sticks, labels, etc.) and distinguishes it from sibling tools like ligand_view or conservation_view by focusing on mutation display.

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?

No guidance is given on when to use this tool versus other visualization tools (e.g., conservation_view, electrostatic_view). The description does not mention prerequisites or exclusions, leaving the agent to infer usage context.

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