explain_forecast_inputs

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

With no annotations, the description carries the full behavioral burden, yet it only hints at read-only intent via 'auditable'. It says nothing about whether the call is safe, what form the explanation takes, or how errors (e.g. unknown SKU) are surfaced.

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?

A single short clause with no filler, and the most distinctive content ('exact history window') is front-loaded. It is underspecified rather than padded, but it is not a complete sentence.

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?

The tool is simple (one required string, no nesting, no annotations) and the description usefully enumerates the return content since there is no output schema. However, the parameter itself and the read-only guarantee are left undocumented, which is a real gap for a one-parameter tool.

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 0% and the sole parameter 'sku' has no description in the schema. The description only alludes to 'a SKU forecast', which gives no guidance on identifier format, case sensitivity, or what happens with an invalid SKU.

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 fragment names the content it surfaces (history window, formula names, caveats) and ties it to a SKU forecast, but never states a verb such as 'returns' or 'explains', so the operation is inferred from the tool name rather than the description. It implicitly distinguishes itself from get_sku_forecast by promising the underlying inputs rather than the forecast itself, though that contrast is never made explicit.

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?

There is no statement of when to call this instead of get_sku_forecast or the other siblings, and no prerequisites or preconditions are given. The agent must guess the selection rule from the tool name alone.

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