Automaton

A contract-based operating system for LLM agents, designed to enforce disciplined engineering workflows.

1. Global Framework Installation (One-time setup)

Before you can use the framework in any project, you must install the core logic into your local environment.

Run these commands in your terminal:

# Clone the framework into the global config directory
git clone http://10.37.0.86:3003/hermes/automaton ~/.automaton

# Enter the directory
cd ~/.automaton

# Make the installation script executable and run it
chmod +x install.sh
./install.sh

Note: This creates the "brain" of the framework (prompts, state machines, and rules) in your home directory.

Updating the Framework

When the framework is updated, you can update your global installation:

cd ~/.automaton
./update.sh

This will:

• Fetch the latest changes from the repository
• Check for uncommitted changes and warn you
• Pull the latest updates

Upgrading existing projects: The framework reads prompts, contracts, and scripts from ~/.automaton/ at runtime. Projects only override .agent.md and .rules.md. This means updating the global framework (git pull) automatically applies to all projects. No per-project upgrade is needed.

If a project was set up under the old model (with copies of framework files), it needs migration first. Tell the agent: "Upgrade automaton for this project" to run the migration.

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2. Project Setup (Per project)

Once the framework is installed globally, you must "onboard" every individual project you work on.

Option A: The Agent-Driven Way (Recommended)

If you want the agent to handle the configuration for you, navigate to your project root and run:

*"Onboard this project into automaton."

The agent will automatically:

1. Detect your project type (New, Existing, or Upgrade).
2. Create the ./.automaton/ directory.
3. Generate your .agent.md and .rules.md files.
4. Initiate the "Exploration Ritual" to understand your codebase.

Option B: The Manual Way

If you prefer to set it up manually, create a .automaton/ directory in your project root and add:

• .agent.md: Project-specific configuration (Mode, rules, etc.).
• .rules.md: Project-specific constraints and past failure modes.

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The Autopilot Workflow

The framework features an Autopilot mode that allows the agent to drive a project to completion with minimal intervention.

Lifecycle of a Task

1. Research: Produce a SPEC.md (Contract). No code allowed. Interactive — agent grills you for requirements and gets sign-off.
2. Decomposition (optional): Break the task into sub-tasks sized for your VRAM. Interactive — agent analyzes the spec and proposes sub-tasks with token budget estimates, gets sign-off. See VRAM Configuration below.
3. Design (optional): Produce a DESIGN.md (Architecture). No code allowed. Interactive — agent grills you for design decisions and gets sign-off.
4. Test Design (optional): Produce a TEST_PLAN.md (Test specification). No code allowed. Interactive — agent grills you for test coverage and edge cases, then presents draft test cases for review and sign-off.
5. Implement: Write code and tests based only on the SPEC.md, DESIGN.md (if present), and TEST_PLAN.md (if present). Follow TDD (Red/Green/Refactor). The TEST_PLAN.md (if present) serves as the test specification the implementer follows.
6. Bug Find: Aggressive search for bugs and spec deviations.
7. Adversarial Bug Find: Deep search for complex logic errors, race conditions, and performance issues.
8. Doc Review: Review documentation against DESIGN.md plan and fix missing docs.
9. Referee: Objective evaluation of all bugs, docs, and the final verdict.

How to use Autopilot

Autopilot mode (default)

The default mode is Autopilot: Enabled. The Orchestrator automatically drives tasks through all phases. Just say:

• Start a new task: "Research add user authentication" (the Orchestrator creates the task and drives it all the way to completion)
• Decompose a task: "Decompose the add-user-auth task" (the Orchestrator breaks it into sub-tasks sized for your VRAM)
• Continue: "orchestrate" or "continue" (the Orchestrator finds the most advanced task and drives it)

VRAM Configuration

For low-VRAM systems (8GB, 16GB), set your VRAM limits in ~/.automaton/config.md:

## VRAM Configuration
- **Auto-detect**: Yes  # Let the agent detect your VRAM automatically
- **Target VRAM context**: 16k tokens  # Override auto-detect if needed
- **Headroom**: 25%
- **Max peak context per sub-task**: 12k tokens

Auto-detection: When Auto-detect: Yes, the Orchestrator runs scripts/vram_detect.py to probe:

• GPU VRAM (via nvidia-smi)
• System RAM (via free)
• Model context window (from config.md or API config files)
• Framework overhead (by counting token load in loaded prompts)

Manual override: When Auto-detect: No, use the manually specified values:

## VRAM Configuration
- **Auto-detect**: No
- **Target VRAM context**: 8k
- **Headroom**: 30%
- **Max peak context per sub-task**: 5.6k

Model Configuration

When using a local LLM or a specific API model, set the model in ~/.automaton/config.md:

## Model Configuration
- **Model**: auto  # Use auto-detection from API config files
- **Override context window**: auto  # Override auto-detection, or specify (e.g., 128k, 200k)

Auto-detection: When Model: auto, the framework detects the model name from API config files (.env, config.yaml, etc.) and looks up its context window.

Manual override: When you know your model name, specify it:

## Model Configuration
- **Model**: gpt-4o
- **Override context window**: 128k

When you run "Decompose the X task", the Orchestrator will:

1. Analyze the task's SPEC.md
2. Detect VRAM limits (auto or manual)
3. Break it into sub-tasks, each sized to fit within your VRAM limit
4. Estimate the token budget for each sub-task
5. Create sub-task folders under tasks/{parent-task}/subtasks/{sub-task}/
6. Propagate VRAM config to each sub-task

Sub-tasks run independently through the full lifecycle. The parent task is complete only when ALL sub-tasks pass.

Manual mode (opt-in)

Set Autopilot: Disabled in your project's .automaton/.agent.md if you prefer to manually run each phase. The Orchestrator reports the current state and tells you the next command. Then run phases by saying things like:

• "Research add user authentication" — starts a new task
• "Decompose the add-user-auth task" — breaks into VRAM-sized sub-tasks (optional)
• "Design the add-user-auth task" — designs the architecture (optional)
• "Design tests for the add-user-auth task" — designs test cases (optional)
• "Implement the add-user-auth task" — implements the task with tests
• "Find bugs in the add-user-auth task" — finds bugs
• "Perform adversarial bug find for add-user-auth" — deep bug search
• "Review docs for the add-user-auth task" — reviews documentation
• "Review the add-user-auth task" — referee evaluates
• "orchestrate" — asks the Orchestrator what to do next

Sub-Task Management

When a task is decomposed, the Orchestrator creates sub-tasks under tasks/{parent-task}/subtasks/. Each sub-task:

• Has its own full lifecycle (Research → Decomposition → Design → ... → Complete)
• Starts at the Research phase with an empty folder
• Receives a PARENT_SPEC.md with the parent task's context
• Receives a VRAM_CONFIG.md with the VRAM constraints
• Runs independently — sub-tasks in the same wave can run in parallel
• The parent task is NOT complete until ALL sub-tasks pass

Key Components

• .agent.md: Project-specific agent behavior (Autopilot mode, routing rules, optional Agent Configuration for multi-agent).
• config.md: Global framework settings (VRAM, model, system requirements, version).
• .rules.md: Living document of project constraints and past failure modes.
• prompts/: Specialized system prompts for each phase with ALLOWED/FORBIDDEN sections and approval gates.
• workflow.md: The state machine governing the task lifecycle, with .state file as canonical phase indicator.
• scripts/status.py: Enforcement script — task status, phase transitions, approval gates, folder validation, audits, multi-agent claiming.
• scripts/vram_detect.py: Auto-detects GPU VRAM, RAM, model context window, and framework overhead.
• contracts/vram_config.md: Contract for VRAM-aware task decomposition.

State Enforcement (v2.0)

Automaton v2.0 enforces the state machine computationally, not just via prompts:

• .state file: Each task has a .state file that is the single source of truth for its current phase
• status.py --transition: All phase transitions must go through this command; illegal transitions are refused
• Approval gates: Research, Design, Decomposition, and Test Design phases require explicit user approval before proceeding
• status.py --validate-folder: Detects out-of-order artifacts (phase skipping)
• status.py --audit: Comprehensive audit across all tasks for violations
• status.py --create-task: The only valid way to create task folders
• FORBIDDEN actions in prompts: Each phase prompt explicitly lists what agents cannot do

Quick Reference

# Create a new task
python ~/.automaton/scripts/status.py --create-task add-user-auth

# Check task status
python ~/.automaton/scripts/status.py --task add-user-auth

# List all tasks
python ~/.automaton/scripts/status.py --list

# Transition to next phase
python ~/.automaton/scripts/status.py --transition research --task add-user-auth
python ~/.automaton/scripts/status.py --transition research:awaiting_approval --task add-user-auth

# Approve a phase (after user sign-off)
python ~/.automaton/scripts/status.py --approve --task add-user-auth

# Validate task folder
python ~/.automaton/scripts/status.py --validate-folder --task add-user-auth

# Audit all tasks
python ~/.automaton/scripts/status.py --audit

# Check if code edits are allowed
python ~/.automaton/scripts/status.py --can-edit --task add-user-auth

Multi-Agent (Optional)

Add an Agent Configuration section to .agent.md to enable multi-agent mode:

## Agent Configuration
Mode: multi-agent
Agents:
  - id: researcher
    phases: [research, decomposition, design, test_design]
  - id: implementer
    phases: [implement]
  - id: bug-hunter
    phases: [bug_find, adversarial_bug_find]
  - id: referee
    phases: [referee]
  - id: orchestrator
    phases: [new, complete, human_intervention]
    role: coordinator
Lock timeout: 30m

In multi-agent mode, agents claim tasks and discover work via status.py --claim and --next-available. In single-agent mode (the default), these commands are no-ops.

Layered File System

The framework uses a layered approach to file management, with a clear precedence:

1. Project overrides (highest precedence): {project}/.automaton/ — contains project-specific customizations
2. Global framework (default): ~/.automaton/ — contains the base framework files

Precedence rule: If a file exists in the project's .automaton/ directory, the Orchestrator reads it from there. If it doesn't exist, the Orchestrator reads it from the global ~/.automaton/ directory.

What files belong in each layer?

• Project's .automaton/: .agent.md (project-specific settings like Autopilot mode, rules override), .rules.md (project-specific constraints), extensions/ (optional additive overrides)
• Global ~/.automaton/: All prompt files, contracts, scripts, config.md, workflow.md

Upgrading

The framework reads all base files from ~/.automaton/ at runtime. To update the framework:

cd ~/.automaton && git pull

This automatically applies changes to all projects — no per-project upgrade needed.

If a project has stale framework file copies (from the old model), tell the agent:

"Upgrade automaton for this project."

The agent will run migrate-project.sh to clean up stale files and move customizations to extensions/.

Dashboard

The dashboard provides a web-based Kanban board, statistics, and timeline views for monitoring task progress.

# Start from any project root or ~/.automaton/
python -m automaton.dashboard

# Or use the convenience wrapper
bash ~/.automaton/scripts/dashboard.sh

See automaton/dashboard/README.md for full documentation on views, keyboard shortcuts, configuration, and scope detection.

Contact & Support

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