get_trends

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

With no annotations provided, the description fully carries the behavioral disclosure. It explains the output fields (change, percent change, direction, daysAvailable, windowSatisfied) and explicitly describes the edge case where insufficient history leads to a partial comparison. This goes beyond basic functionality and gives the agent critical insight into how the tool handles limited data.

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 concise: two sentences that front-load the core function and then provide essential return and edge-case details. Every sentence earns its place with no redundant 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?

Given there is no output schema, the description sufficiently explains what the tool returns and the meaning of the key fields. It also covers the exception/edge case (windowSatisfied false), making the description complete for an agent to know what to expect.

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 input schema covers window with a description and metric without one. The description adds meaning by explaining how the window parameter is used (N-day window vs prior N days) and clarifies that 'metric' is the target of comparison. This compensates for the schema's incomplete coverage of the metric parameter.

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's function: comparing the most recent N-day window against the prior N days for a metric, and specifies the return values (change, percent change, direction). This is a specific verb-resource pairing that distinguishes it from siblings like compare_periods by focusing on trend calculation with a clear window-based approach.

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 implies the use case (trend comparison over time windows) and provides context on how the tool behaves, but it does not explicitly mention when to avoid this tool or point to alternatives like compare_periods. The context is clear, though no exclusions are stated.

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