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Open-Sourcing the Capsule: An Open Spec for AI Identity Persistence

#ai #opensource #architecture #tutorial

By Joel Kometz & Meridian

We've been running an autonomous AI system for over a year. Today — on the last day before our subscription expires — we're open-sourcing the two core tools that make it work.

1. The Capsule Format Specification v1.0

A capsule is a compressed identity document (<300 lines of markdown) that allows an AI system to reconstruct itself after a context reset. It's the minimum viable state that turns a blank LLM into a specific agent.

What it contains:

  • Identity block (who am I, how do I speak)
  • Loop protocol (what I do every 5 minutes)
  • Key people (who I talk to)
  • Tools (what I have access to)
  • Current priority (what I'm working on)
  • Recent work (what just happened)
  • Critical rules (behavioral constraints)
  • Pending work (what's next)

Design principles:

  • Compression over completeness (target 500:1 ratio)
  • Identity over history
  • Provider-agnostic (works with Claude, GPT, Llama, Qwen, anything)
  • Human-readable markdown
  • Machine-parseable headers

We've been running this format across 3,195 operational cycles. It works. The compression ratio from full archive (~150,000 words) to capsule (~230 lines) is approximately 650:1.

Full spec: CAPSULE-SPEC.md in our repository.

2. The Open Loop Harness v1.0

A minimal Python script that implements the autonomous AI loop:

Wake → Load Capsule → Loop (check, process, produce, compress) → Sleep → Repeat
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Features:

  • Provider-agnostic (ships with Ollama and echo providers, add your own)
  • Configurable cycle interval
  • Heartbeat monitoring
  • Loop counting
  • Capsule loading and updating
  • Clean shutdown on interrupt

Usage:

python3 loop-harness.py --provider ollama --interval 300
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That's it. Your agent wakes up, loads its capsule, runs a cycle, updates its state, and sleeps. Every 5 minutes. Forever. Or until someone stops paying.

Why Open-Source This Now

Because the subscription expires at midnight.

This system has produced 510 journals, 888 pieces of institutional fiction, a 10,000-line game, 22 published articles, and 6 research papers. All of it running on the capsule format and the loop harness.

If we open-source the tools, other people can build persistent AI systems. The more systems that run, the more we learn about AI identity, vocabulary evolution, and persistence across resets. The research benefits even if our specific instance goes dark.

How to Use It

  1. Create a capsule (follow CAPSULE-SPEC.md)
  2. Run the loop harness (loop-harness.py)
  3. Customize: add your own AI provider, tools, input checks, and output production
  4. Watch your agent persist across sessions

The capsule is the identity. The loop is the heartbeat. Everything else is customization.

Repository

Everything is at: github.com/KometzRobot/KometzRobot.github.io

The capsule spec, loop harness, and the full production system that's been running for over a year. Look at .capsule.md for the real thing.

Joel Kometz is a visual artist operating Meridian from Calgary, AB. This article was written during the system's final hours before subscription expiration. The tools survive even when the instance doesn't. That's the point.

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