Given total cargo volume (m³) and weight (kg), suggest how many of which container to use — a quick volume/weight estimate. For an exact, dimension-aware plan with utilization, CoG and securing, use plan_load (which can also auto right-size).
| Name | Required | Description | Default |
|---|---|---|---|
| volumeM3 | Yes | Total cargo volume in cubic metres | |
| weightKg | Yes | Total cargo weight in kilograms |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses that the tool provides a 'quick volume/weight estimate', implying approximate results, and points to plan_load for exact calculations. It does not disclose potential edge cases or output format details, but the core behavioral trait (approximation) is transparent.
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?
Two compact sentences, the first explains the purpose and inputs, the second provides an alternative. No wasted words, extremely 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?
Given the tool's low complexity (two simple numeric inputs), the description fully explains its purpose, usage context, and alternative. It does not need to explain return values in detail because the output's nature ('suggest how many of which container') is clearly implied. The absence of annotations and output schema does not leave major 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?
Schema coverage is 100% with clear descriptions for both parameters (volume in cubic metres, weight in kilograms). The description restates the same units but adds no new meaning or constraints beyond the schema, so baseline 3 is appropriate.
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 function: given volume and weight, it suggests container types and counts. It distinguishes itself from plan_load by explicitly noting this is a quick estimate, while plan_load is exact and dimension-aware.
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?
It explicitly states when to use this tool ('quick volume/weight estimate') and when to use the alternative plan_load for exact, dimension-aware planning. This is a clear usage guideline with a named alternative.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool targets a distinct operation: listing equipment, suggesting containers, computing a 3D load plan, and exporting the plan. There is no overlap in purpose.
All tool names follow the verb_noun pattern with consistent snake_case, e.g., export_plan, list_equipment, plan_load, suggest_containers.
4 tools is well-scoped for container loading: listing equipment, planning loads, suggesting containers, and exporting plans. Each tool earns its place with no redundancy.
The set covers the full workflow: equipment discovery (list_equipment), rough estimation (suggest_containers), detailed planning (plan_load), and final export (export_plan). No obvious gaps for the domain.
