y_plus_from_height

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. The description does disclose the key behavioral output (y+ value and region classification), which is valuable. However, it doesn't disclose the underlying formula/assumptions (e.g., flat-plate boundary layer correlation, whether it uses density and kinematic viscosity as provided), the bounds of validity, or what happens with invalid inputs. For a predictive/tool with no annotations, this is a moderate gap.

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 a tight single sentence that front-loads the core operation ('predict the y+ that a given first-cell height will produce') and then appends the classification output. No wasted words. Could arguably add more detail, but the structure is efficient.

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 tool has 5 parameters, 0% schema coverage, no output schema, and no annotations, making the description the sole documentation. It covers the core purpose and the classification output but fails to document 2 parameters, the formula/assumptions, and the return format. For a reasonably simple predictive tool, the description is adequate for basic use but incomplete for an agent that needs to know the physical model and parameter roles.

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%, meaning the schema provides no descriptions for any of the 5 parameters. The description mentions only two physical quantities (first-cell height, velocity), and implies length, but does not explain the roles of `density` and `kinematic_viscosity` or which are required vs. optional. With 0% schema coverage, the description must compensate, and it fails to explain 2 of the 5 parameters entirely and doesn't clarify why some have defaults. This is a significant gap.

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 states a specific verb ('predict'), a clear resource (y+ from first-cell height), and the output (y+ value and region classification: viscous sublayer, buffer layer, log-law). It clearly distinguishes itself from its sibling `first_cell_height`, which is the inverse operation. The description is clear but doesn't explicitly name the sibling tool as an alternative.

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 clear context for when to use the tool (when you have a first-cell height and want to know the resulting y+), but provides no explicit guidance on when NOT to use it or which sibling to choose instead. The inverse relationship with `first_cell_height` is implied but not stated. There's no mention of prerequisites or typical CFD workflow context (e.g., 'use this after mesh generation').

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