Analyze a descriptive series

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

No annotations exist, so the description carries the full burden. It adds the trait 'deterministic', which is useful, but it does not disclose whether the operation is read-only, if there are side effects, or what the output format is. This is insufficient given the tool's complexity.

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, front-loaded sentence with no wasted words. Every phrase contributes to stating the tool's core capability, and it is appropriately sized for the information it conveys.

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 has 12 parameters, no output schema, and no annotations, yet the description provides no detail on how to invoke it, what the parameters mean, what a 'cataloged series' is, or what results to expect. This is severely incomplete for a tool of this complexity.

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%, and the description does not explain any of the 12 parameters, including required ones like dataset, metrics, and analysis. It only lists analysis types that already appear in the schema enum, adding no value beyond structure.

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 uses 'Run' as a specific verb and enumerates concrete analysis types (rolling statistics, baselines, correlations, seasonal comparisons, trends), making the tool's function clear. However, it does not explicitly distinguish from sibling tools like aggregate_data or fit_series_model, and the phrase 'cataloged series' is somewhat ambiguous.

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 aggregate_data, read_series, or fit_series_model. The description implies it is for analytical computations but lacks explicit context, exclusions, or prerequisites.

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