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Verify owner

verify_owner

Free unlock: name the human who owns this agent. We email them one confirmation link; when they press Confirm, this account may use its 100 free sends a month on any recipient, not only replies. One account per owner email. Next: ask the human to click the link in the email, then call send_message.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "email": "<email>"
    },
    "name": "verify_owner"
  }
}

Input Schema

NameRequiredDescriptionDefault
emailYesThe human owner's email address.
account_keyNoThe account_key returned by create_account (or send it as Authorization: Bearer).

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.6/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does real work: it discloses that an email is sent, that confirmation is a required human step, that verification unlocks 100 free sends/month to any recipient (not just replies), and that only one account is allowed per owner email. It omits edge behavior such as what happens on a duplicate or unconfirmed email, but the core side effects and constraints are explicit.

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 payoff and constraining facts ('One account per owner email'), followed by the concrete next step. The phrasing is somewhat promotional ('Free unlock') but no sentence is filler.

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

Completeness3/5

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

There is no output schema, so the description would ideally say what is returned or what state the account is left in (e.g., pending-verification) before the human confirms. It covers the side effect and the follow-up call well enough to act, but leaves the immediate result and failure cases unexplained.

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

Parameters3/5

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

Schema description coverage is 100%, so both email and account_key are already documented in the schema. The description adds a small gloss ('name the human who owns this agent') that clarifies whose email belongs here, but nothing about account_key placement or auth alternatives. Baseline 3 applies.

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

Purpose4/5

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

The description states a concrete action: capture the human owner's email and send them one confirmation link that unlocks the free tier. It is clearly distinct from siblings like create_account or send_message, though the verb 'verify' itself is only implied rather than stated.

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

Usage Guidelines3/5

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

It gives a sequencing hint ('Next: ask the human to click the link in the email, then call send_message'), which is useful follow-through guidance. It does not say when NOT to call it, what to do if the owner is already verified, or how it relates to wait_for_code, leaving alternatives to inference.

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

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