Agent Templates
Outbound Prospecting Agent

Outbound prospecting agents that act on-behalf-of your users

Connect three real services, delegate OAuth to your users, and ship a working agent in minutes. Clone the sample, swap in your tools, and go from zero to multi-connector in a single afternoon.

Outbound Prospecting Agent
Sample Agent for Acme
May 22 · 10:00 AM ·
47s
Find 10 VP Engineering prospects and draft outreach
J
Searching Apollo for ICP matches
Search contacts by ICP
apollo_search_contacts
Draft personalized email
gmail_create_draft
Log to Google Sheets
sheets_append_row
Prospecting run: VP Engineering
Top match (score: 94)
"Sarah Lin, VP Eng, Fintech (280 employees)"
Draft saved to her Gmail: personalized for infra scaling pain
Result
8 of 10 prospects qualified (score ≥ 70)
8 drafts saved to rep's Gmail, 10 rows logged to Sheets
Message Claude...
Trusted by teams shipping agents to production
Outbound Prospecting Agent
Sample Agent for Acme
May 22 · 10:00 AM ·
47s
Find 10 VP Engineering prospects and draft outreach
J
Searching Apollo for ICP matches
Search contacts by ICP
apollo_search_contacts
Draft personalized email
gmail_create_draft
Log to Google Sheets
sheets_append_row
Prospecting run: VP Engineering
Top match (score: 94)
"Sarah Lin, VP Eng, Fintech (280 employees)"
Draft saved to her Gmail: personalized for infra scaling pain
Result
8 of 10 prospects qualified (score ≥ 70)
8 drafts saved to rep's Gmail, 10 rows logged to Sheets
Message Claude...

How the agent finds, scores, and emails prospects in four steps

A real working agent you can deploy

This repo uses a single SCALEKIT_USER_ID env var to simulate one user. In production, pass each user's real ID as the identifier on every Scalekit call, and send them an authorization link whenever their connector status is not ACTIVE.

01
Authorize, then orchestrate
main.py
Every connection is authorized once via a one-time link. Scalekit refreshes tokens for you across all three connectors. main.py verifies each connector is ACTIVE before running: a connector that has lost authorization surfaces a new link rather than failing mid-pipeline.
main.py
import os
from scalekit import ScalekitClient
from langchain.agents import create_tool_calling_agent

client = ScalekitClient(
    env_url=os.environ["SCALEKIT_ENV_URL"],
    client_id=os.environ["SCALEKIT_CLIENT_ID"],
    client_secret=os.environ["SCALEKIT_CLIENT_SECRET"],
)

# LangChain-compatible tools scoped to this user
tools = client.actions.langchain.get_tools(
    identifier="user@example.com",
    connection_names=["apollo", "gmail", "googlesheets"],
)

agent = create_tool_calling_agent(llm, tools, prompt)
02
Search and score prospects in Apollo
search_apollo.py
03
Draft personalized cold emails
draft_emails.py
04
Log prospects to Google Sheets
log_sheets.py
Why choose Scalekit

Delegated identity. Not service accounts.

Credentials never touch agent code or LLM context. The agent acts as the user, not as a shared bot.
Delegated OAuth - Agent reads your calendar, your inbox — scoped to the authorizing identity, not org-wide.
Credentials outside agent runtime  -  Tokens never touch agent code or LLM context. Both failure modes covered.
Token lifecycle automatic  -  Refresh, expiry, rotation across all connectors. One SDK call. Zero management code.
200+ prebuilt connectors  -  Google, Slack, HubSpot, GitHub, Jira, Notion, Salesforce — same auth pattern everywhere.

Agents that prospect outbound, without the auth plumbing

Three things you'd otherwise build: Apollo OAuth, per-rep Gmail credential storage, Sheets API auth. Handled.

OAuth flow per connector
One SDK call returns a delegated token for any connector. Google, HubSpot, Slack, same pattern across all 200+ connectors
tools = client.actions.langchain.get_tools(
    identifier=user_id,
    connection_names=["apollo", "gmail", "googlesheets"],
)
agent = create_tool_calling_agent(llm, tools, prompt)
Secure token vault  
Scalekit stores OAuth credentials outside agent code and outside LLM context. Both are separate failure modes. Both covered
client = ScalekitClient(
    env_url=os.environ["SCALEKIT_ENV_URL"],
    client_id=os.environ["SCALEKIT_CLIENT_ID"],
    client_secret=os.environ["SCALEKIT_CLIENT_SECRET"],
)
# Credentials never in agent code or LLM context
Token refresh logic
Token lifecycle handled automatically — expiry, rotation, re-auth — across every connector. Agent runs in 6 months. Same call works
# Day 1 or day 180 — same call works
tools = client.actions.langchain.get_tools(
    identifier=user_id,
    connection_names=["apollo", "gmail", "googlesheets"],
)
Try other Agent Templates

Prebuilt agents you can ship today

Each one runs on delegated identity, scoped per user.

SALES
Sales call prep agent
Pull Granola notes and Attio contact history to draft a pre-call brief before every sales meeting. Zero rep input.
GTM
CRM AI agent
Log calls, update opportunity stages, and surface stalled deals across HubSpot or Salesforce. No manual data entry.
SALES
Deal intelligence agent
Combine Gong, Attio, and Slack signals to surface deal risks and next-best actions. Updated after every call.
SUPPORT
Support triage agent
Read Zendesk tickets, fetch runbooks from Notion, and route to the right Slack channel with a drafted response.
OPS
Email-to-calendar scheduling agent
Parse scheduling intent from Gmail threads and create Google Calendar events with the right attendees and timezone.
SUPPORT
Freshdesk CSAT follow-up agent
Google ADK agent that watches low CSAT scores in Freshdesk and drafts personalised follow-ups for support leads.
Customize the sample

Clone it and own it with connectors you choose

Don't sweat the integration. Point a coding agent at the repo. It clones, swaps in your connectors, and adds new steps for you.

1
Install a coding agent
terminal

claude "Set up an outbound prospecting agent using Apollo, Gmail, and Google Sheets via Scalekit"

terminal

codex "Set up an outbound prospecting agent using Apollo, Gmail, and Google Sheets via Scalekit"

terminal

gh copilot suggest "Set up an outbound prospecting agent using Apollo, Gmail, and Google Sheets via Scalekit"

terminal

Open Cursor Composer (Cmd+Shift+I) Paste the prompt from the Prompt tab

terminal

npx skills add scalekit-inc/skills --skill setup-scalekit

2
Give it this prompt

Clone github.com/scalekit-inc/python-connect-demos/langchain. Set connection_names = ["apollo", "gmail", "google_sheets"]. Build a prospecting pipeline: search Apollo for ICP-matching leads, check Gmail for prior outreach history, score leads with the LLM, write qualified leads to Google Sheets. Set SCALEKIT_ENV_URL, SCALEKIT_CLIENT_ID, SCALEKIT_CLIENT_SECRET in .env. Each rep authorizes once via Scalekit magic link.

Build your own
multi-connector agent

Add connectors. Change the LLM. Same delegated auth pattern.