forecast

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

With no annotations, the description carries the full burden and does well on methodology: it discloses the default ARIMA order, how seasonal order is derived from seasonal_period, that exponential smoothing uses additive trend/seasonal components, and that ARIMA intervals are analytic while smoothing intervals are a normal approximation. It does not state what is returned (point forecasts plus interval bounds) or how errors are surfaced, which keeps it short of a 5.

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?

Front-loaded with the core purpose and structured into method-specific details with no filler. Slightly dense in places, but every sentence adds substantive information.

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 6-parameter tool with 0% schema coverage, no annotations, and no output schema, the description should define the remaining parameters and the shape of the result. It covers method mechanics decently but leaves several inputs and the return value unexplained.

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%, so the description must compensate. It clarifies `order` (default [1,0,0]) and `seasonal_period` (drives seasonal order / seasonal component) well, but `steps`, `conf_alpha`, and especially `series` (array-of-numbers vs string) are left entirely undocumented in both schema and description.

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 action (forecast) and resource (univariate series) and enumerates the two supported methods plus their configuration. It is clear on its own, but it never differentiates itself from the sibling `arima` tool, which overlaps heavily with the ARIMA path described here.

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 explicit when-to-use or when-not-to-use guidance. The description explains how the two methods behave but never says when to prefer this tool over `arima`, `time_series_decompose`, or `stationarity_test`, nor what prerequisites (e.g., stationarity) apply.

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