seasonality_decomposition

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

Annotations indicate readOnlyHint=true, destructiveHint=false, idempotentHint=true. The description adds context: it uses additive decomposition and returns specific outputs. No contradiction. It provides more behavioral detail than annotations alone, but does not address potential limitations or assumptions.

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 one sentence with a pipe separator, front-loading the core action and equation. It is concise and efficient, though the structure could be slightly improved with clearer breaks between purpose, usage, and output.

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 tool's complexity and lack of output schema, the description covers the method, usage context, and output format. However, it omits parameter details, edge cases, and assumptions (e.g., no missing data). More completeness would improve usability.

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 only 25% (only 'period' has a description). The description hints at period options ('monthly or quarterly') but does not explain 'indicator', 'entity', or 'time'. Parameters are largely left unexplained, and the description fails to compensate for the low schema coverage.

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 performs additive decomposition (Y = trend + seasonal + residual) with the purpose of stripping the seasonal cycle to reveal underlying trends. It also specifies output: per-timepoint components and summary amplitude. This distinguishes it from sibling tools like 'correlate' or 'regression'.

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 advises when to use the tool ('strip the seasonal cycle', 'reveal the underlying trend') and gives example data types ('monthly or quarterly data, retail sales, unemployment'). However, it does not mention when not to use it or alternative tools from the sibling list.

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