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Archer: Transform Slack into an AI-Powered Command Center

Archer: Transform Slack into an AI-Powered Command Center

By Mikey Sharma•Aug 29, 2025

Archer: AI Agent for Slack - Comprehensive Documentation

archer Archer: Agentic Slack Assistant An intelligent AI agent that enhances productivity within Slack by performing actions on your behalf

Table of Contents

  1. Overview
  2. Architecture
  3. Features & Capabilities
  4. Security & Authentication
  5. Workflows & Examples
  6. Installation & Setup
  7. Configuration
  8. API Reference
  9. Troubleshooting

Overview

Archer is a sophisticated AI agent built for Slack that leverages the power of Arcade AI to provide seamless integration with multiple services and tools. It transforms Slack into a command center for managing emails, calendars, code repositories, web searches, and more - all through natural language conversations.

Key Benefits

  • Unified Interface: Access multiple services from within Slack
  • Natural Language Processing: Communicate with tools using plain English
  • Secure Authentication: OAuth-based authorization for each service
  • Conversation Memory: Maintains context across interactions
  • Parallel Tool Execution: Handle multiple tasks simultaneously
  • Error Recovery: Robust error handling and retry mechanisms

Architecture

System Architecture

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Agent Workflow Graph

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Event Processing Flow

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Features & Capabilities

Core Toolkits

Archer integrates with the following toolkits by default:

1. GitHub Integration

  • Repository Management: Create, read, update repositories
  • Pull Request Operations: Review, merge, comment on PRs
  • Issue Tracking: Create, update, assign issues
  • Code Analysis: Search code, view file contents
  • Branch Management: Create, delete, merge branches

2. Google Services

  • Gmail Management: Read, compose, send emails
  • Calendar Operations: Schedule meetings, view events
  • Drive Access: Upload, download, share files
  • Docs Integration: Create, edit documents

3. Search & Web Tools

  • Web Search: Google, Bing, DuckDuckGo integration
  • Web Scraping: Extract data from websites
  • Content Analysis: Summarize web pages
  • Link Validation: Check URL accessibility

4. Communication Tools

  • Slack Integration: Send messages, create channels
  • Email Management: Multi-provider email support
  • Notification Systems: Push notifications, alerts

Advanced Features

Conversation Memory

  • Thread-based Context: Maintains conversation history per thread
  • State Persistence: Saves agent state across sessions
  • Context Awareness: Remembers user preferences and past interactions

Parallel Processing

  • Multi-tool Execution: Run multiple tools simultaneously
  • Async Operations: Non-blocking API calls
  • Batch Processing: Handle multiple requests efficiently

Error Handling

  • Graceful Degradation: Continue operation despite tool failures
  • Retry Mechanisms: Automatic retry for transient failures
  • Fallback Strategies: Alternative approaches when primary methods fail

Security & Authentication

Authentication Architecture

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Security Features

1. Request Verification

  • Slack Signature Validation: Verifies requests come from Slack
  • Timestamp Validation: Prevents replay attacks
  • Event Deduplication: Prevents duplicate processing

2. OAuth Integration

  • Service-specific Tokens: Each service has its own OAuth flow
  • Token Encryption: Secure storage of access tokens
  • Scope Management: Minimal required permissions

3. Data Protection

  • Local Storage: User data stored locally, not in cloud
  • Encrypted Communication: All API calls use HTTPS
  • Token Rotation: Automatic token refresh mechanisms

Authorization Workflow

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Workflows & Examples

Example 1: Email Management Workflow

User Request: "Read my last 10 emails and summarize them"

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Example Response:

📧 **Email Summary (Last 10)**

1. **Meeting Reminder** - Team standup tomorrow at 10 AM
2. **Project Update** - Q4 goals review from Sarah
3. **Invoice Received** - Payment confirmation for invoice #1234
4. **Code Review** - PR #567 needs your review
5. **Newsletter** - Weekly tech digest from TechCrunch
6. **Calendar Invite** - Client meeting on Friday
7. **System Alert** - Server maintenance scheduled
8. **Document Share** - New design specs shared by John
9. **Approval Request** - Expense report needs approval
10. **Welcome Email** - New team member onboarding

**Key Actions Needed:**
- Review PR #567
- Approve expense report
- Prepare for client meeting

Example 2: GitHub Development Workflow

User Request: "Show me recent PRs in the arcadeai/arcade-ai repository"

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Example Response:

🔧 **Recent Pull Requests - arcadeai/arcade-ai**

**Open PRs:**
1. **#1234** - Add new authentication flow
   - Author: @john-doe
   - Status: Ready for review
   - Changes: 15 files, +234 -45 lines

2. **#1235** - Fix memory leak in agent
   - Author: @jane-smith  
   - Status: In progress
   - Changes: 3 files, +12 -8 lines

3. **#1236** - Update documentation
   - Author: @mike-wilson
   - Status: Draft
   - Changes: 8 files, +156 -23 lines

**Recently Merged:**
- **#1233** - Performance improvements (merged 2 hours ago)
- **#1232** - Bug fix for edge case (merged 1 day ago)

**Your Action Items:**
- Review PR #1234 (assigned to you)
- Check PR #1235 for potential conflicts

Example 3: Calendar Management Workflow

User Request: "Schedule a meeting with the development team for tomorrow at 2 PM"

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Example Response:

📅 **Meeting Scheduled Successfully**

**Event Details:**
- **Title**: Development Team Meeting
- **Date**: Tomorrow (Tuesday, March 5th)
- **Time**: 2:00 PM - 3:00 PM EST
- **Location**: Google Meet (link generated)
- **Attendees**: 
  - @john-doe (confirmed)
  - @jane-smith (pending)
  - @mike-wilson (pending)

**Calendar Link**: [View in Calendar](https://calendar.google.com/event/...)

**Next Steps:**
- Meeting agenda will be shared 1 hour before
- Recording will be available after the meeting
- Follow-up tasks will be created based on discussion

Example 4: Multi-Service Integration Workflow

User Request: "Find information about the latest React updates and create a summary document"

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Example Response:

🔍 **React Updates Summary**

**Latest React 19 Features:**
- **Concurrent Features**: Improved rendering performance
- **Server Components**: Enhanced server-side rendering
- **New Hooks**: use() hook for data fetching
- **Compiler Improvements**: Better optimization

**Key Changes:**
- Automatic batching for all updates
- Improved error boundaries
- Better TypeScript support
- Enhanced developer tools

**Breaking Changes:**
- Removed legacy context API
- Updated event pooling behavior
- Modified component lifecycle methods

📄 **Summary Document**: [React 19 Updates Summary](https://docs.google.com/document/...)

**Sources:**
- React Blog (official)
- MDN Web Docs
- React GitHub repository
- Community discussions

Installation & Setup

Prerequisites

  • Python: 3.10 or higher
  • Poetry: 1.8.4+ (for dependency management)
  • OpenAI API Key: For language model access
  • Arcade API Key: For tool integrations
  • Slack App: Configured with proper permissions

Step-by-Step Installation

1. Clone and Install

# Clone the repository
git clone https://github.com/arcadeai/archer.git
cd archer

# Install dependencies
make install

2. Environment Configuration

Create a .env file with the following variables:

# Slack Configuration
SLACK_BOT_TOKEN=xoxb-your-bot-token
SLACK_SIGNING_SECRET=your-signing-secret

# AI Services
OPENAI_API_KEY=sk-your-openai-key
ARCADE_API_KEY=your-arcade-key

# Logging
LOG_LEVEL=INFO

# Optional: LangSmith for tracing
LANGSMITH_TRACING=true
LANGSMITH_ENDPOINT=https://api.smith.langchain.com
LANGSMITH_API_KEY=your-langsmith-key
LANGSMITH_PROJECT=archer

3. Slack App Setup

  1. Create Slack App:

  2. Configure Permissions:

    {
  "oauth_config": {
    "scopes": {
      "bot": [
        "chat:write",
        "chat:write.public", 
        "im:history",
        "im:read",
        "im:write",
        "users:read",
        "assistant:write"
      ]
    }
  }
}

  3. Set Event Subscriptions:

    • Enable events for: app_home_opened, message.im, assistant_thread_started
    • Set request URL to your deployment endpoint

4. Deploy to Modal

# Deploy the application
make deploy

# Modal will provide a URL like: https://your-app.modal.run

5. Update Slack Configuration

Replace the placeholder URLs in your Slack app configuration:

  • Event Subscriptions: https://your-app.modal.run/slack/events
  • Interactivity: https://your-app.modal.run/slack/events

Configuration

Agent Configuration

The agent can be configured through the archer/defaults.py file:

# Available Models
MODELS = {
    "gpt-4o": {
        "name": "GPT-4o",
        "provider": "OpenAI", 
        "max_tokens": 128000,
        "parallel_tool_calling": True,
    },
    "gpt-4o-mini": {
        "name": "GPT-4o mini",
        "provider": "OpenAI",
        "max_tokens": 128000,
        "parallel_tool_calling": True,
    }
}

# Available Toolkits
TOOLKITS = ["github", "google", "search", "web"]

System Prompt Customization

SYSTEM_CONTENT = """
You are a versatile AI assistant named Archer. You were created by Arcade AI.
Provide concise, relevant assistance tailored to each request from users.

Key capabilities:
- Email management and composition
- Calendar scheduling and management  
- GitHub repository operations
- Web search and content extraction
- Document creation and editing

Be professional, friendly, and efficient in your responses.
"""

Storage Configuration

Archer uses file-based storage by default. Configure storage options:

# File storage configuration
STORAGE_CONFIG = {
    "type": "file",
    "base_dir": "./data",
    "users_dir": "./data/users",
    "states_dir": "./data/states"
}

API Reference

Event Handlers

Message Events

@app.event("message")
def handle_message_events(message, say, logger, context, client):
    """
    Handle regular text messages in DMs and channels.
    
    Args:
        message: The message object from Slack
        say: Function to send messages
        logger: Logger instance
        context: Bolt context with channel info
        client: Slack Web API client
    """

Assistant Events

@assistant.user_message
def respond_in_assistant_thread(payload, logger, context, set_status, say, client):
    """
    Handle messages in Slack's AI assistant threads.
    
    Args:
        payload: Message payload
        logger: Logger instance
        context: Bolt context
        set_status: Function to set assistant status
        say: Function to send messages
        client: Slack Web API client
    """

Agent API

Invoke Agent

from archer.agent import invoke_agent

response = invoke_agent(
    user_id="U1234567890",
    prompt="Read my emails",
    context=conversation_history,
    thread_id="unique-thread-id"
)

Agent State Management

# Save agent state
agent.save_state(thread_id, state_data)

# Retrieve agent state  
state = agent.get_state(thread_id)

Storage API

User Management

from archer.storage import get_storage

storage = get_storage()

# Save user identity
storage.set_state({
    "user_id": "U1234567890",
    "provider": "openai",
    "model": "gpt-4o"
})

# Get user state
user_state = storage.get_state("U1234567890")

Troubleshooting

Common Issues

1. Authentication Errors

Problem: "Authorization required for tools"

Solution:

# Check Arcade API key
echo $ARCADE_API_KEY

# Verify Slack tokens
curl -H "Authorization: Bearer $SLACK_BOT_TOKEN" \
     https://slack.com/api/auth.test

2. Event Processing Issues

Problem: Events not being processed

Solution:

# Check event deduplication
# Events are deduplicated to prevent double processing
# Check logs for "Duplicate event detected" messages

3. Tool Execution Failures

Problem: Tools failing to execute

Solution:

# Check tool configuration
from archer.defaults import get_available_toolkits
print(get_available_toolkits())

# Verify Arcade tool availability
from langchain_arcade import ArcadeToolManager
manager = ArcadeToolManager()
tools = manager.get_tools()

4. Memory Issues

Problem: Agent losing context

Solution:

# Check storage configuration
# Ensure data directory is writable
ls -la ./data/

# Verify thread_id consistency
# Each conversation should have a unique thread_id

Debug Mode

Enable debug logging:

# Set environment variable
export LOG_LEVEL=DEBUG

# Or in .env file
LOG_LEVEL=DEBUG

Performance Optimization

1. Model Selection

# Use faster models for simple tasks
MODELS = {
    "gpt-4o-mini": {
        "name": "GPT-4o mini",
        "provider": "OpenAI",
        "max_tokens": 128000,
        "parallel_tool_calling": True,
    }
}

2. Tool Optimization

# Limit toolkits to essential ones
TOOLKITS = ["github", "google"]  # Remove unused toolkits

3. Memory Management

# Configure memory limits
MEMORY_CONFIG = {
    "max_events": 1000,
    "cleanup_interval": 3600  # Cleanup every hour
}

Contributing

Development Setup

# Clone repository
git clone https://github.com/arcadeai/archer.git
cd archer

# Install development dependencies
poetry install --with dev

# Run tests
make test

# Run linting
make lint

Code Structure

archer/
├── agent/           # Agent implementation
├── listeners/       # Event handlers
├── storage/         # Data persistence
├── utils/           # Utility functions
├── defaults.py      # Configuration
├── env.py          # Environment variables
└── server.py       # FastAPI server

Testing

# Run unit tests
pytest tests/

# Run integration tests
pytest tests/integration/

# Run with coverage
pytest --cov=archer tests/

License

This project is licensed under the MIT License - see the LICENSE file for details.

Support

Built with ❤️ by the Arcade AI team and edited by Mikey Sharma

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