lammps_estimate_viscosity

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

With no annotations, the description carries the burden of behavioral disclosure. It explains the power-law fitting model, defines the meaning of n (Newtonian, shear-thinning, shear-thickening), and clearly specifies the input data. It does not disclose the exact return format or fitting algorithm, but for a pure computation tool with no side effects, this is adequate transparency.

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 front-loaded: the first sentence states the purpose, followed by an optional model explanation, and then parameter definitions. Every sentence contributes 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?

Given the tool's simplicity (2 string parameters, no nested objects, output schema present), the description adequately covers purpose, model, and parameter semantics. It does not describe return values, but the presence of an output schema means the description need not explain them. It also does not mention edge cases (e.g., equal array lengths, numeric formats), but these are minor gaps.

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 provides only parameter names and types (string) with no descriptions, so the description fully compensates. It explicitly defines shear_rates_json as a JSON array of shear rates and shear_stresses_json as a JSON array of corresponding shear stresses, adding meaning beyond the structured schema.

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 estimates viscosity from shear rate vs shear stress data. It uses a specific verb ('estimate') and resource ('viscosity from shear rate vs shear stress data'), and distinguishes itself from sibling tools like lammps_parse_thermo or lammps_shear_sweep by its unique modeling focus.

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 clear context for when to use the tool—when you have shear rate and shear stress data and need to fit a power-law model. It does not explicitly name alternatives or exclusions, but the niche purpose and model explanation imply its usage. Given sibling tools are primarily parsing/generation tools, the intended scenario is evident.

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