stationarity

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

With no annotations, the description carries the full burden. It mentions the tests but does not explain what the verdict looks like, side effects, or interpretation. The existence of an output schema is noted but not detailed in the description.

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 a single sentence with no wasted words, front-loading the core purpose efficiently.

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 complexity of combining two statistical tests and the presence of many sibling tools, the description lacks context about stationarity, test names, and verdict interpretation. An agent needs more information to decide appropriately.

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?

The description adds no meaning to the single parameter 'series_id' beyond the schema. Schema coverage is 0% and the parameter is just a string without clarification of valid values or source.

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 it runs ADF and KPSS tests together and provides a combined stationarity verdict, using a specific verb ('run') and resource ('stationarity test'). It distinguishes from sibling tools like trend_test or autocorrelation by specifying the tests used.

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?

No guidance is provided on when to use this tool versus alternatives such as trend_test or decompose. There is no mention of prerequisites or context for its use.

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