Spend & Performance Forecast

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

The description adds significant behavioral context beyond the annotations (readOnlyHint, idempotentHint). It discloses the methodology (moving-average extrapolation), output fields (projected metrics, confidence_level, warnings), and limitations (confidence drops with volatile data or paused campaigns). No contradiction with annotations.

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 (three sentences) and well-structured. It front-loads the purpose and input, then explains the methodology and output structure. Every sentence adds value with no redundancy.

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 absence of an output schema, the description provides a comprehensive summary of the return value structure (period_days, platform, projected metrics, confidence_level, warnings). It also covers confidence degradation conditions, making it complete for an agent to understand the tool's behavior.

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 elaborates on the parameters by restating the period_days options and noting platform is optional. While the schema covers 50% of parameter descriptions, the description adds clarity by explicitly listing the platform filter. It does not fully compensate for undocumented parameters but adds meaningful context.

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 purpose: projecting future ad spend and performance based on historical trends. It uses a specific verb ('Project') and resource ('ad spend and performance'), and distinguishes itself from siblings like budget_analyze by focusing on forecasting.

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 provides clear context for when to use the tool, including input parameters (period_days and platform). It implies usage for forecasting but does not explicitly state when not to use it or mention alternatives, though the context is adequate given sibling tools serve different purposes.

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