BOI — Beginning of Infinity

Coordinate autonomous agent fleets to execute task specs with iterative improvement.

Updated Jul 6, 2026

Search Tags:#autonomous agents #agent orchestration #task dispatch #boi #spec-based tasks #runtime daemon

Ready to run

npx skills add https://github.com/mrap/boi --skill boi-beginning-of-infinity

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: BOI — Beginning of Infinity
Source: https://github.com/mrap/boi/tree/main/.claude/skills/boi
Command: npx skills add https://github.com/mrap/boi --skill boi-beginning-of-infinity

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

BOI coordinates self-evolving autonomous agent fleets to decompose, schedule, and execute complex task specs with sustained context and automatic iteration.

Core Features & Use Cases

Spec-based task decomposition and distributed execution across worker sessions
Self-evolution: new tasks can be appended to specs as work reveals new requirements
Daemon-managed, isolated worktrees and runtime prompts for safe, repeatable runs

Quick Start

Describe a task to BOI, dispatch the spec, and let the system autonomously manage workers to complete it.

Frequently Asked Questions about BOI — Beginning of Infinity

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I coordinate autonomous agents to execute complex software development tasks?▼

Spec-based task decomposition splits high-level software development requirements into executable units. These tasks are distributed across multiple worker sessions managed by a runtime daemon, ensuring safe and repeatable execution in isolated worktrees.

Can I use Claude or Codex as the runtime CLI for agent task dispatch?▼

Yes, agent task dispatch requires a runtime CLI such as claude -p or codex exec. The daemon uses this CLI to manage isolated worktrees under ~/.boi within a minimal Python stdlib environment for safe, repeatable runs.

How does task spec self-evolution work during autonomous agent execution?▼

Task spec self-evolution allows new tasks to be appended to specs dynamically as work reveals new requirements. This enables the autonomous agent fleet to iteratively improve outcomes without manual spec rewriting during operations.

Do I need a Python environment to run autonomous agent orchestration daemons?▼

Yes, autonomous agent orchestration requires a minimal Python stdlib environment. The daemon runs within this environment to manage isolated worktrees under ~/.boi and coordinate distributed worker sessions for task execution.

What is the best way to manage isolated worktrees for autonomous agent fleets?▼

Daemon-managed isolated worktrees under ~/.boi provide the best way to manage autonomous agent fleets. The daemon automatically handles worktree creation and runtime prompts for safe, repeatable task execution across distributed worker sessions.