refund-decide

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes the core behavior (checking eligibility and returning one of three statuses) and mentions the decision basis ('vendor's refund policy window'). However, it lacks details about error handling, rate limits, authentication needs, or whether this is a read-only operation, which would be valuable for a tool with no 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 a single, well-structured sentence that efficiently conveys the tool's purpose, scope, and output. Every word earns its place, with no redundancy or unnecessary elaboration, making it easy to parse and understand quickly.

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 moderate complexity (4 required parameters, no output schema, no annotations), the description provides a solid foundation by explaining what it does and what it returns. However, it could be more complete by addressing potential edge cases (e.g., invalid inputs, vendor-specific nuances) or clarifying the 'UNKNOWN' status, which would help in a production context.

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 schema description coverage is 100%, so the schema already documents all parameters thoroughly. The description doesn't add any parameter-specific semantics beyond what's in the schema (e.g., it doesn't explain how 'days_since_purchase' interacts with policy windows). This meets the baseline of 3 when the schema does the heavy lifting.

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 specific action ('Check if... is eligible for a refund'), resource ('US consumer subscription purchase'), and outcome ('Returns ALLOWED, DENIED, or UNKNOWN'). It distinguishes the tool's purpose by specifying it's based on 'the vendor's refund policy window,' which provides meaningful differentiation even without sibling tools.

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 usage context through 'US consumer subscription purchase' and 'based on the vendor's refund policy window,' suggesting it should be used for refund eligibility checks. However, there are no explicit guidelines about when not to use it, prerequisites, or alternatives, leaving some gaps in usage guidance.

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