List Received Emails

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

Annotations already declare readOnlyHint=true, so the safety profile is known. The description adds valuable context by stating the return scope ('Paginated metadata: from, to, subject, message_id, received time') and that full content requires a different tool. This goes beyond the annotation without contradicting it.

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 tightly structured into three sections (Purpose, NOT for, Returns) with no redundant wording. Every sentence earns its place, and the most critical information is front-loaded. It is concise yet information-dense.

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?

For a simple list tool with full schema coverage and readOnly annotation, the description covers all essential aspects: purpose, exclusions with alternatives, return content, and a pointer to the content-retrieval tool. No output schema exists, so the description compensates by listing the returned fields. It is complete for an AI agent to select and invoke 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?

Schema description coverage is 100%: all three parameters (after, limit, before) are fully described in the input schema, including constraints and mutual exclusivity. The description adds no extra parameter semantics, but the schema already does the heavy lifting, so a baseline of 3 is appropriate.

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 opens with a specific verb+resource combination: 'List emails received (inbox) by your Resend receiving address.' It clearly distinguishes from sibling tools by explicitly stating what it is NOT for (sent emails and broadcasts) and names the correct alternatives (list-emails, list-broadcasts). This leaves no ambiguity about the tool's function.

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?

Provides explicit use-case examples ('show my inbox', 'what emails did I get?') and explicit exclusions with alternative tools ('NOT for: Listing emails you sent (use list-emails)...'). It also mentions using get-received-email for full content, giving a clear path for follow-up actions. This is model usage guidance.

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