crosslink_view

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

With no annotations provided, the description carries the full burden of transparency. It discloses detailed visual behavior: thin grey cartoon, yellow sticks for cysteines, yellow dashes for disulfides, orange spheres for metals, dashed lines for coordination, and black background. This goes well beyond a basic summary, though it does not mention side effects or scene reset behavior.

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 appropriately sized for a visualization tool, with the main purpose stated first and subsequent sentences providing specific visual details. Each sentence contributes useful information, though some minor redundancy exists (e.g., 'drawn as' repeated). Overall, it is well-structured and not verbose.

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?

For a one-parameter tool with an output schema, the description comprehensively covers the visual output, including colors, styles, and labeling. It does not mention potential side effects (e.g., whether it resets existing styles) or prerequisites, but the simplicity of the tool keeps those gaps minor.

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 a complete description for the single parameter obj_name ('PyMOL object name (e.g. 1abc)'), so schema coverage is 100%. The description does not add extra meaning about the parameter itself; it only elaborates on what will be visualized. Baseline 3 is appropriate.

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 highlights structural cross-links (disulfide bonds, metals, and their coordination), which is a specific verb+resource (highlights + cross-links). This distinguishes it from sibling view tools like interface_view or bfactor_view, making its purpose unambiguous.

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 context is clear: use this tool to visualize structural cross-links. While it does not explicitly name alternatives or exclusions, the purpose statement makes the usage obvious. This aligns with 'clear context, no exclusions' rather than merely implied usage.

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