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lauren-frameworklauren-framework/lauren-ai/skills/email-notification-tool/SKILL.md

email-notification-tool

Skill0 starsChanged 6 months agoMITView on GitHub

Implements an agent tool for dispatching email notifications with a swappable backend. Use when building agents that send emails or notifications, with an in-memory backend for testing and a pluggable abstract backend for production SMTP or API-based senders.

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SKILL.md

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Email / Notification Dispatch Tool

Critical rule — tool annotations must resolve

from __future__ import annotations is supported, but every type used by @tool() must resolve when schema generation runs.


Overview

EmailDispatchTool is a class-form @tool() that wraps an EmailBackend protocol. InMemoryEmailBackend is used in tests; production code provides an SMTP or transactional-email-API implementation.


Implementation

# tools/email_tool.py — future annotations are allowed; keep tool types importable
from abc import ABC, abstractmethod
from dataclasses import dataclass
from lauren_ai import tool, ToolContext

@dataclass
class EmailPayload:
    to: list[str]
    subject: str
    body: str
    from_addr: str = "agent@example.com"

class EmailBackend(ABC):
    @abstractmethod
    async def send(self, email: EmailPayload) -> bool: ...

class InMemoryEmailBackend(EmailBackend):
    def __init__(self):
        self.sent: list[EmailPayload] = []

    async def send(self, email: EmailPayload) -> bool:
        self.sent.append(email)
        return True

@tool()
class EmailDispatchTool:
    """Send an email notification.

    Args:
        to: Comma-separated recipient email addresses.
        subject: Email subject.
        body: Email body text.
    """

    def __init__(self, backend: EmailBackend | None = None):
        self._backend = backend or InMemoryEmailBackend()

    async def run(
        self, ctx: ToolContext, to: str, subject: str, body: str
    ) -> dict:
        recipients = [addr.strip() for addr in to.split(",") if addr.strip()]
        if not recipients:
            return {"error": "No valid recipients"}
        email = EmailPayload(to=recipients, subject=subject, body=body)
        success = await self._backend.send(email)
        return {"sent": success, "recipients": recipients}

Injecting a custom backend

To use a real SMTP backend, subclass EmailBackend and pass an instance to the EmailDispatchTool constructor or supply it through DI:

class SMTPBackend(EmailBackend):
    async def send(self, email: EmailPayload) -> bool:
        # call smtplib or aiosmtplib here
        ...
        return True

tool_instance = EmailDispatchTool(backend=SMTPBackend(...))

AgentRunner test pattern

Pass a pre-built InMemoryEmailBackend instance to EmailDispatchTool so tests can inspect the sent list after the run.

import json
from lauren_ai._agents import AgentContext, agent, use_tools
from lauren_ai._tools import ToolResult
from lauren_ai._transport import Completion, TokenUsage
from lauren_ai.testing import TestClient


class _Capture:
    def __init__(self):
        self.captured: list[ToolResult] = []

    async def on_tool_result(self, result: ToolResult, ctx: AgentContext) -> ToolResult | None:
        self.captured.append(result)
        return None


def _make_agent(backend=None):
    email_tool = EmailDispatchTool(backend=backend)

    @agent(model=None, system="Email assistant")
    @use_tools(email_tool)
    class EmailTestAgent(_Capture):
        def __init__(self):
            _Capture.__init__(self)

    return EmailTestAgent()


def _c(text):
    return Completion(id="c1", model="mock", content=text, tool_calls=[],
                      stop_reason="end_turn", usage=TokenUsage(10, 5))


def test_send_email():
    backend = InMemoryEmailBackend()
    agent_inst = _make_agent(backend)
    client = TestClient(agent_inst)
    client.mock.queue_tool_use(
        "email_dispatch_tool",
        {"to": "alice@example.com", "subject": "Hi", "body": "Hello Alice"},
    )
    client.mock.queue_response(_c("Email sent."))
    client.run("Send email to Alice")

    out = json.loads(agent_inst.captured[0].content)
    assert out["sent"] is True
    assert len(backend.sent) == 1
    assert backend.sent[0].subject == "Hi"

Attaching to an agent

# agents.py — from __future__ import annotations is safe here
from __future__ import annotations
from lauren_ai import agent, use_tools
from .tools.email_tool import EmailDispatchTool

@agent(model="claude-opus-4-6", system="You are a notification assistant.")
@use_tools(EmailDispatchTool)
class NotificationAgent: ...

Reference files

FileContents
src/lauren_ai/_tools/__init__.py@tool(), ToolContext
src/lauren_ai/_tools/_executor.pyToolExecutor dispatch

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