sasa

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

With no annotations provided, the description carries the burden of disclosing behavior. It reveals that SASA is computed in the context of the parent object, which is not obvious from the schema, and notes accuracy dependence on PyMOL settings dot_solvent and dot_density. Missing explicit statement about read-only nature, but the description provides substantial behavioral context for a measurement tool.

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 compact and front-loaded, stating the core function first, then the key nuance, the alternative, and the accuracy dependencies. Each of the four sentences adds value with no redundancy or filler.

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 simple measurement tool with an output schema and only two well-documented parameters, the description covers the essential aspects: purpose, contextual behavior, alternatives, and dependencies. It is complete for an agent to decide when and how to invoke the tool, and the output schema covers return values.

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 description coverage is 100%, so the baseline is 3. The description adds meaning by explaining that the selection is measured in the context of its parent object, which clarifies the selection parameter's semantics beyond the schema. It does not elaborate on the state parameter further, but the schema already covers it.

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 measures solvent-accessible surface area in square Angstroms, with a specific verb and resource. It also distinguishes itself from the sibling tool interface_report by explaining the context-dependence of the measurement.

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 gives explicit guidance on when to use this tool vs alternatives: for unbound measurements, it advises using create or interface_report. It clearly states the scenario where sasa is appropriate (measuring in context of the object) and when to choose an alternative.

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