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

The annotations already establish readOnlyHint=true, idempotentHint=true and destructiveHint=false, and the description adds genuinely new context: the tool reads the containers@current dataset, rejects ambiguous input rather than guessing, lists accepted values under `normalized`, and requires quoting provenance.source_line plus passing on the reference-only notice. Those are behavioral obligations the annotations do not convey. It stops short of describing the floor-plan output or any limits on the calculation.

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 purpose is front-loaded in the first sentence in both languages, and the remaining sentences each carry a distinct constraint (dataset read, input format, no-fabrication rule, provenance, disclaimer). The bilingual duplication roughly doubles the length and repeats the disclaimer twice, costing it a point on economy.

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?

For a 21-parameter computation tool with an output schema and full annotation coverage, the description supplies the dataset source, input encoding rules, anti-hallucination policy, and citation requirement, which is what an agent needs to call it safely. The gap is that it never explains how the tool relates to its closest sibling or what the floor-plan result contains, so a small amount of routing information is missing.

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 100%, so the schema already documents all 21 parameters, including the enum meanings for stack, orientation and containerType. The description adds a cross-cutting rule about exact decimal strings and the required-versus-optional handling policy, but nothing specific about how parameters like maxHeight, doorHeight or layerCount combine. 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 names a specific calculation (pallets and cartons per container) and enumerates the inputs that drive it (pallet, carton, height limit, container type) plus the deliverable (floor plan), so an agent can tell it is a pallet-loading simulator rather than a general freight or fee tool. It does not, however, distinguish itself from the sibling container-load tool, which the description never mentions, leaving that boundary for the agent to infer.

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?

Usage is implied by the input enumeration 'fill in pallet, carton, height limit and container type' and by the rule to ask the user for missing required values and skip optional ones, which is concrete operational guidance. There is still no explicit statement of when not to use it or which sibling to pick instead when the question is carton-only loading or freight cost.

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