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extract_contacts

Read-only

Extract unique contacts from recent email headers, sorted by frequency to identify frequent correspondents and build an address book.

Instructions

Extract unique contacts from recent email headers. Returns contacts sorted by frequency (most frequent first). Useful for finding frequent correspondents or building an address book.

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": {
      "account": "<account>"
    },
    "name": "extract_contacts"
  }
}

Input Schema

Name	Required	Description
`limit`	No	Number of recent emails to scan (default: 100, max: 500)
`account`	Yes	Account name from list_accounts
`mailbox`	No	Mailbox to scan (default: INBOX)

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.2.3Aug 1, 2026

TDQS

A4.3/5.0

Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is clear. The description adds useful behavioral context: it processes 'recent email headers', returns 'unique' contacts, and sorts them 'by frequency', which goes beyond the annotations without contradicting them.

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

Conciseness5/5

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

Two sentences, front-loaded with the primary action and result, then a brief use-case statement. Every sentence earns its place with concise, useful information.

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?

The tool is simple, with no output schema. The description explains the output format ('contacts sorted by frequency') and the scanning scope ('recent email headers'). Combined with the schema, this gives an agent everything needed to select and invoke the tool correctly.

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 coverage is 100%, with each parameter (limit, account, mailbox) already described. The description mentions 'recent email headers' and frequency sorting, but does not add material semantic detail about the parameters beyond what the schema provides. Baseline 3 applies.

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?

The description uses a specific verb ('Extract') and resource ('unique contacts from recent email headers'), and clearly states the output ('Return contacts sorted by frequency'). This distinguishes it from sibling tools like 'extract_calendar'.

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

Usage Guidelines4/5

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

The description provides clear use cases ('Useful for finding frequent correspondents or building an address book'), giving context for when to use the tool. It doesn't explicitly mention when not to use it, but no alternative contact-extraction sibling exists, so the context is sufficient.

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