Skip to main content
Glama

Start Email Test

start_email_test

Use this when the user wants to know how a real email from them actually authenticates — whether a message from Google Workspace, Microsoft 365, a newsletter tool or an app is SPF/DKIM/DMARC aligned, why it lands in spam, or to prove DKIM…

Instructions

Use this when the user wants to know how a real email from them actually authenticates — whether a message from Google Workspace, Microsoft 365, a newsletter tool or an app is SPF/DKIM/DMARC aligned, why it lands in spam, or to prove DKIM signing works before tightening DMARC. Returns a single-use address (valid about an hour, one message) and a test_id. Tell the user to send one email to that address from the sender they want to test, then call get_email_test with the test_id. Each call creates a new address; the daily limit counts only messages that arrive, a few unused addresses may be open at once, and limit says which allowance applied.

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.12.0

TDQS

A4.8/5.0
Behavior5/5

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

Goes well beyond the annotations: single-use address, ~1 hour validity, one message only, each call creates a new address, daily limit counts only arrived messages, unused addresses can coexist, and the response includes a limit field. This is unusually rich operational context for a non-idempotent, non-readOnly tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with the when-to-use clause, then the return contract, then the caller workflow. Dense but nearly every clause carries actionable detail; the daily-limit sentence is slightly packed but still useful.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

No output schema exists, and the description compensates fully by describing the returned single-use address, test_id, and limit, plus the required follow-up call. An agent has everything needed to invoke and continue correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Zero parameters, so the schema has nothing to explain and the baseline is 4. The description correctly implies no inputs are needed and instead documents the returned address/test_id/limit.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource: creates a single-use email test address so the user can see how their real email authenticates (SPF/DKIM/DMARC alignment). It clearly distinguishes itself from the read-side sibling by instructing the agent to follow up with get_email_test.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Opens with an explicit trigger ('Use this when the user wants to know how a real email... authenticates'), enumerates concrete scenarios (spam diagnosis, proving DKIM before tightening DMARC), and names the next step (get_email_test with the test_id). The alternative path is implied clearly by the follow-up routing.

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