pipe_sizing_wizard

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

With no annotations provided, the description carries the full burden of behavioral disclosure, and it does so thoroughly. It describes the chaining of velocity and friction-loss computations, the composite scoring (60% velocity closeness + 40% head-loss efficiency), the filters (max head-loss, max pressure-drop), and the detailed output fields (velocity, head loss, Reynolds number, etc.). It even notes preset behaviors. This is far beyond a typical description.

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 dense but every sentence earns its place. It front-loads the core purpose in the first sentence, then logically flows through the chaining mechanism, presets, filters, output details, and usage recommendation. It avoids redundancy and clearly structures information for quick comprehension.

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 complexity (14 parameters, no output schema), the description is extraordinarily complete. It enumerates all output fields, explains the ranking criteria, specifies parameter requirements, and provides usage context. The absence of an output schema is compensated by the detailed output description. An agent has everything needed to decide when and how to invoke this tool correctly.

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?

Although schema description coverage is 100%, the description adds significant meaning beyond the schema. It explains how parameters interact (e.g., roughnessC is required when method is hazen-williams and no preset, roughnessEpsilonMm for darcy-weisbach), how velocityPreset 'custom' uses min/maxVelocity, and how the ranking score weights parameters. This enriches the raw schema definitions, providing context that helps the agent select and configure parameters correctly.

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's purpose: 'End-to-end pipe sizing wizard' that finds standard pipe sizes satisfying velocity and friction-loss constraints and ranks them. It explicitly names the resource (pipe sizes) and the actions (size, validate, rank). It also differentiates itself from siblings by stating it chains recommend_diameter and friction_loss in a single call, making it distinct.

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?

Explicitly states when to use: 'Use this to make a single validated pipe selection without calling recommend_diameter and friction_loss separately.' This names the alternatives (recommend_diameter, friction_loss) and the condition (need for a combined validated selection). It also implies when not to use—if only a diameter recommendation is needed, one would use the simpler tools. This is strong guidance.

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