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

With no annotations, the description carries the full burden of disclosing behavior. It does well by explaining that cargo `type` drives realism (hex-nesting, top-loading big bags), that omitting `equipmentCode` triggers auto right-sizing to the cheapest container, and that the production key uses the PackingSolver optimizer while the demo key uses an offline preview packer. It does not disclose potential side effects or limitations, but for a computation tool this is adequate.

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 single, well-structured paragraph that uses colons and semicolons to pack multiple related details. It is not overly long, and every sentence adds meaningful information. While it is slightly more than two sentences, the density and organization make it concise and front-loaded.

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 high complexity, the rich input schema, and the absence of an output schema, the description does a good job of covering the main behaviors and expected outputs. It lists the return values (containers used, utilization, CoG, violations, checklist) and touches on edge behaviors like cargo type handling and auto right-sizing. It could mention mode handling or more details about the difference between production and preview, but overall it is reasonably 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?

The schema already has 100% coverage, so the baseline is 3. The description adds valuable semantic context beyond the schema: it explains that cargo `type` drives realism (e.g., drums hex-nest, big bags load on top and are never crushed) and that omitting `equipmentCode` triggers auto right-sizing. This helps the agent understand the intent of these parameters, justifying a 4.

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 what the tool does with a specific verb and resource: 'Compute a 3D load plan for cargo into a container or truck.' It enumerates concrete outputs (containers used, utilization percentages, centre of gravity, crush-protection violations, securing checklist), which distinguishes it from sibling tools like list_equipment or suggest_containers. The scope is unambiguous.

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 (to compute a load plan) and provides important usage nuances, such as omitting `equipmentCode` to auto right-size and the distinction between a production API key and demo key. However, it does not explicitly compare against alternative sibling tools or state conditions when one should choose a different tool, so it falls short of a 5.

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