lammps_nematic_order

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

No annotations are present, so the description carries the full burden of behavioral disclosure. It explains the meaning of S values and gives an example, but it does not state whether the operation is read-only, how invalid or non-normalized quaternions are handled, or the exact output format (though the output schema exists). This is adequate but not rich.

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: a brief purpose statement, a short explanation of the output meaning, and a parameter section with an example. Every sentence contributes valuable information, and there is no wasteful repetition 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 single-parameter compute tool with an output schema, the description is nearly complete. It covers the input format, example, and interpretation of the result. The main missing pieces are edge-case behavior and normalization requirements, but these are not critical given the simplicity and available schema.

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 schema only lists a parameter named quaternions_json with type string and no description. The description compensates fully by specifying the shape (N,4), the quaternion order [w,x,y,z], and providing a concrete example. This gives the agent exactly what it needs to construct a valid parameter value.

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 that the tool computes the scalar nematic order parameter S from quaternion data. The verb 'compute' and the specific resource 'scalar nematic order parameter' make the purpose unambiguous. Though it doesn't explicitly contrast with siblings like lammps_nematic_vs_z, the 'scalar' and 'from quaternion data' distinguish it sufficiently.

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 provides no guidance on when to choose this tool over alternatives like lammps_nematic_vs_z or lammps_nematic_vs_time. It never mentions that this is for a single global order parameter versus spatially or temporally resolved ones, leaving the selection criteria entirely implicit.

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