atom_properties

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

No annotations are provided, so the description carries the full behavioral burden. It discloses that properties are evaluated by PyMOL per atom and accepts iterate expressions, which is useful operational context. It also hints at a technical limitation ('returns an object that cannot cross the bridge'). However, it does not mention potential cost (e.g., slow for large selections) or details about the result format, though the output schema likely covers the latter.

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 well-structured with a clear lead sentence, a differentiation paragraph, usage examples, and a technical note. It is a bit longer than strictly necessary—some repetition of the 'cannot reach/other route' idea—but every paragraph serves a purpose and the content is front-loaded.

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 moderate complexity, an output schema exists, and no annotations, the description is exceptionally complete. It covers purpose, alternative tools, concrete use cases, and parameter semantics. The only minor gaps are performance/return details, but those are either in the schema or not critical for a read operation. This matches the high end of the calibration examples.

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%, so the baseline is 3. The description adds value by explaining that the 'properties' parameter is a PyMOL iterate expression and provides a list of common properties. It also gives guidance on narrowing the 'selection'. This goes beyond the schema's short field descriptions, especially for 'properties', which could otherwise be ambiguous.

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 opens with a specific verb+resource: 'Reads per-atom properties.' It immediately distinguishes itself from siblings by stating 'nothing else in the tool set can reach' and contrasts with object-level and per-residue tools. This makes the purpose unmistakable.

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 explicitly names alternatives: 'Object-level facts come back through structure_info and list_chains, and per-residue values through get_sequence or the view presets.' It then provides concrete use cases ('partial occupancy...', 'per-atom pLDDT...', 'formal charge...'). This clearly tells the agent when to choose this tool and when other routes are more appropriate.

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