lammps_d2min

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

With no annotations provided, the description must cover behavioral transparency on its own. It describes the computation's purpose and output interpretation (D²min deviation from affine deformation), which conveys that this is a read-only analysis operation. It does not discuss error handling or input validation, but the 'Compute' framing and scientific context make the behavior reasonably clear.

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, leading with the core purpose, then providing one-sentence background on D²min, and ending with a clear Args list. Every sentence adds value, and the line breaks make it easy to scan.

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 key context: what the tool computes, what the result means, and what all three parameters represent. Since an output schema exists, the description does not need to enumerate return values. It lacks explicit usage alternatives and edge-case guidance, but for a straightforward compute tool, the provided information is sufficient for an agent to select and invoke it.

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 0%, so the description carries the full burden for parameter meaning. It explicitly explains that positions are JSON strings with shape (N, 3) and describes r_cut as 'cutoff radius for neighbor finding,' adding meaning beyond the bare input schema. It omits units for r_cut and does not mention coordinate frame assumptions, but the core semantics are present.

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 'Compute' and identifies the exact resource: 'non-affine displacement D²min for each particle between two frames.' It explains the physical meaning of D²min, clearly distinguishing this tool from sibling analysis tools like lammps_nematic_order or lammps_parse_dump.

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 implies the tool is useful for identifying plastic events ('High D²min = plastic event'), which gives contextual guidance. However, it does not explicitly state when to use this tool versus alternatives such as lammps_identify_plastic_events, nor does it mention any exclusions or complementary tools.

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