get_wagon_by_load_capacity

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

With no annotations, the description carries full behavioral burden. It discloses the data cutoff date, the filtering rule (positive stock only), the default return of all 27 classes, and a field-name spacing caution. It lacks details on error handling or output format, but for a read tool with an output schema, this is strong coverage.

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 structured with a summary line followed by parameter details and a caveat. It is direct and each sentence adds value, though it is slightly longer than the bare minimum. Front-loading the purpose and then refining with specifics is effective.

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 read-only query with an output schema, the description covers everything an agent needs to invoke it correctly: the filtering semantics, defaults, parameter formats, and a field-name pitfall. No critical gaps remain for successful use.

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 0%, so the description must fully compensate. It explains wagon_type with concrete examples, min_load and max_load with example values, and clarifies that all are optional with a default result set. This adds real semantic meaning beyond the schema's bare property definitions.

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 queries wagon load-capacity stock by 27 load classes as of a specific date, listing the exact wagon types counted. It distinguishes itself implicitly from get_wagon_by_weight_class by focusing on load capacity rather than weight, giving the agent a precise picture of what it does.

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 explains parameter usage and default behavior (returns all 27 rows when inputs are omitted, only rows with stock > 0), but it does not explicitly state when to choose this tool over siblings like get_wagon_by_weight_class. Context is clear, but exclusions and alternative selection are absent.

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