Hands Overview

Autonomous agents that work 24/7 on specialized tasks

What Are Hands?

Hands are specialized autonomous agents in OpenFang designed to run continuously and handle specific workflows. Unlike general-purpose chat agents, Hands are optimized for:

• Continuous operation — Run scheduled tasks 24/7
• Domain expertise — Deep knowledge in specific areas (video editing, research, social media)
• Multi-phase pipelines — Complex workflows broken into manageable steps
• State persistence — Remember progress across sessions
• Tool specialization — Access to specialized tools for their domain

Available Hands

Clip Hand

Turn long videos into viral short clips with captions and thumbnails

Lead Hand

Discover and enrich qualified leads on autopilot

Collector Hand

Monitor any target with continuous intelligence collection

Predictor Hand

Make calibrated predictions and track accuracy over time

Researcher Hand

Conduct exhaustive investigations with fact-checking

Twitter Hand

Autonomous Twitter content creation and engagement

Browser Hand

Navigate websites and complete multi-step web tasks

Custom Hand

Build your own specialized Hand

How Hands Work

Activation

Hands are activated by loading their definition file:

openfang hand activate clip

This creates an agent instance with the Hand’s specialized configuration, tools, and system prompt.

Configuration

Each Hand has settings that control its behavior:

# Example from Clip Hand
[settings]
stt_provider = "groq_whisper"  # Speech-to-text provider
publish_target = "telegram"     # Where to send clips

Settings can be configured through:

• The web dashboard at http://localhost:4200
• Direct TOML editing in ~/.openfang/hands/
• CLI configuration commands

Requirements

Some Hands require external tools or API keys:

Check the requirements section for each Hand before activating. Missing dependencies will prevent the Hand from functioning.

Scheduling

Hands can run on schedules:

// Created automatically by the Hand's initialization
schedule_create({
  frequency: "daily",
  time: "09:00",
  task: "generate_lead_report"
})

Memory & State

Hands persist state between runs:

• Memory store — Key-value storage for metrics and state
• Knowledge graph — Entity and relationship tracking
• File storage — Reports, databases, and artifacts

Hand Architecture

Every Hand follows a consistent multi-phase pipeline:

1. Phase 0: Platform Detection

   Detect OS and load state from previous runs

2. Phase 1: Initialization

   Set up schedules, load configuration, build strategy

3. Phase 2-5: Core Work

   Execute the Hand’s specialized workflow (varies by Hand)

4. Final Phase: Persistence

   Save state, update metrics, generate reports

Dashboard Metrics

All Hands expose metrics through the dashboard:

• Jobs completed — Total tasks finished
• Items processed — Clips generated, leads found, etc.
• Performance data — Success rates, quality metrics
• Last run — When the Hand last executed

Safety Guardrails

Hands include built-in safety features:

• Rate limiting — Respect API and service limits
• Approval modes — Require user confirmation for sensitive actions
• Error recovery — Graceful handling of failures
• Cross-platform compatibility — Works on Windows, macOS, Linux

Choosing the Right Hand

Use Case	Hand	Why
Create social media content from videos	Clip Hand	Automated video processing pipeline
Generate sales leads	Lead Hand	Continuous discovery and enrichment
Track competitors or markets	Collector Hand	Change detection and knowledge graphs
Forecast trends	Predictor Hand	Calibrated predictions with accuracy tracking
Deep dive research	Researcher Hand	Multi-source verification and synthesis
Manage Twitter presence	Twitter Hand	Content generation and engagement
Automate web tasks	Browser Hand	Real browser automation with safety
Custom workflow	Custom Hand	Build your own specialized agent

Next Steps

Explore Hands

Browse the documentation for each Hand

Build Your Own

Learn how to create custom Hands