sasa

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

Annotations already establish the safe read-only, idempotent profile, and the description adds real behavioral context beyond them: results are context-dependent because the selection is occluded by its partner, and accuracy is governed by PyMOL's dot_solvent and dot_density settings. It stops short of describing cost or performance for large selections, which would push it to a 5.

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?

Three short paragraphs, front-loaded with the core measurement and followed by the most important caveat (occlusion) and then the settings dependency. Every sentence carries information an agent would otherwise have to discover empirically.

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 two-parameter read tool with an output schema already defining return values, the description covers the one thing that reliably trips up callers — that the value is context-dependent — and points at the sibling that handles the bound/free comparison.

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?

Schema coverage is 100%, with both 'state' and 'selection' documented in the schema itself, so the baseline is 3. The description reinforces that the measured quantity is tied to a selection but adds no syntax, defaults, or format detail beyond what the schema already says.

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?

States a specific verb and resource ('Measures solvent-accessible surface area') with units ('square Angstrom'), and immediately scopes it to a selection within its parent object. An agent can distinguish this from interface_report and contact_report without opening any schema.

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?

Explicitly names the alternative (interface_report) and the condition that selects it ('bound/free bookkeeping'), plus a concrete recipe ('copy the chain to its own object first with create') for the free-area case. This is genuine when/when-not guidance, not implied usage.

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