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

Annotations already declare read-only and idempotent behavior, but the description adds valuable context beyond annotations: it details error handling ('never raises a protocol error — it returns {"error": ...}'), retry safety, and a caveat about ad_cost_per_order defaulting to 0 being misleading. This goes above and beyond the 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 well-structured and front-loaded with the core purpose, followed by an example, usage guidance, and error behavior. Every sentence earns its place; the 'FREE.' is slightly extraneous marketing but not distracting. The length is justified given the tool's complexity.

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 description is complete for a calculator-style tool: it explains the math, shows a full input/output example, covers error handling, and gives usage context. Combined with the rich annotations and output schema, no critical information is missing for an agent to invoke this tool correctly.

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?

With 100% schema description coverage, the schema already documents each parameter's meaning. The description adds a concrete typical input example and highlights a common pitfall (ad_cost_per_order default), which enhances understanding beyond the schema alone. It stops short of being exhaustive but is clearly helpful.

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 what the tool does: 'Show what one sale actually leaves after every cost' and details the calculations (subtracting costs, break-even price). It explicitly distinguishes itself from siblings: 'Not for a whole tiered price list — that is price_ladder — and not for the effect of returns, which is returns_impact.'

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?

Explicit when-to-use guidance is given: 'Use before listing a product.' It also names specific alternatives for scenarios the tool does not handle (price_ladder for tiered pricing, returns_impact for returns), making the decision boundary clear.

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