SandMail — Disposable Email API for AI Agents

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 describes the core behavior (extracting OTP from the latest email) and includes a fallback mechanism (include_body for raw text if OTP not found), which adds useful context. However, it lacks details on error handling, rate limits, or authentication needs, leaving some behavioral aspects unclear.

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 two concise sentences that are front-loaded with the core purpose and usage guidelines. Every word earns its place, with no redundancy or unnecessary elaboration, making it highly efficient and easy to parse.

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 (2 parameters, no output schema, no annotations), the description is mostly complete. It covers purpose, usage, and some behavioral aspects, but lacks details on output format, error cases, or dependencies on other tools like wait_for_email. This leaves minor gaps in full contextual understanding.

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 both parameters. The description adds no additional parameter semantics beyond what the schema provides, such as clarifying email format or OTP extraction logic. However, with only 2 parameters and high schema coverage, the baseline is 3, and the description's clarity on tool purpose slightly elevates this to 4.

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 ('Extract OTP/verification code') and resource ('from the latest email in an inbox'), distinguishing it from siblings like get_emails (which retrieves emails generally) or wait_for_otp (which waits for OTP arrival). It precisely defines the tool's function without redundancy.

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 explicitly states when to use this tool ('when an email has already arrived and you need to extract the code'), providing clear context. It implicitly distinguishes from alternatives like wait_for_otp (which waits for arrival) and get_emails (which retrieves emails without OTP extraction), though it doesn't name them directly.

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