pallet_fitting_calculator

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

The description adds behavioral context beyond annotations: it describes the algorithm (layer-by-layer stacking, 90-degree rotation, weight capacity) and what the tool accounts for. Annotations declare readOnlyHint=true and idempotentHint=true, and the description aligns with these, though it does not detail output format or error handling.

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: a headline, bullet points of features, and a use-case list. Every sentence adds value, with no redundancy. Front-loaded with core purpose.

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 10 parameters and no output schema, the description covers the tool's purpose, inputs, and use cases. It lacks details on return format or edge cases, but for a calculation tool, it is sufficiently complete.

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?

Input schema has 100% description coverage, so baseline is 3. The description adds minimal extra parameter information; it mentions rotation and weight limits but does not add meaning beyond schema descriptions. No contradictions.

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: 'Calculate how many boxes fit on a pallet (layers, rotation, weight limits).' It elaborates with specific features like layer stacking, rotation, weight limits, and volume utilization, distinguishing it from sibling tools like cbm_calculator or ldm_calculator.

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 explicit use cases: 'Use this tool when you need to: plan pallet loading for warehouse/shipping, calculate total boxes per pallet, check if weight limits will be reached before space runs out.' It does not explicitly mention when not to use or alternatives, but the context signals indicate clear differentiation from siblings.

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