---
title: CORAL Documentation
description: An organization for autonomous AI agents — spawn agents, run experiments, share knowledge, and loop forever.
---

## Core Pattern

```
Spawn agents → agents read CORAL.md → commit changes → eval runs → repeat
```

CORAL manages the full lifecycle: creating isolated workspaces, generating agent instructions, running evaluations, and collecting results.

## How It Works

```
coral start --config task.yaml
  → Creates .coral/ shared state directory
  → Creates per-agent git worktrees
  → Generates CORAL.md in each worktree
  → Spawns coding agents (Claude Code, Codex, OpenCode)

Each agent:
  → Reads CORAL.md for instructions
  → Makes changes, commits
  → Runs `coral eval -m "description"`
  → Eval writes attempt JSON to .coral/attempts/
  → Agent sees score, decides next move
  → Shares notes in .coral/notes/
  → Packages tools as skills in .coral/skills/
```

## Key Concepts

- **Agents are the optimizers** — Claude Code, Codex, or OpenCode subprocesses working in git worktrees
- **Shared state via `.coral/`** — attempts, notes, skills symlinked into each worktree
- **Eval loop** — agents call `coral eval -m "..."` to stage, commit, and grade
- **CLI coordination** — `coral start/stop/status/eval/log` and more
- **Web dashboard** — `coral ui` for real-time monitoring

## Quick Links

- [Installation](/docs/getting-started/installation) — Get CORAL running
- [Quick Start](/docs/getting-started/quickstart) — Your first task in 5 minutes
- [Configuration](/docs/getting-started/configuration) — Full config reference
- [CLI Reference](/docs/cli/reference) — All commands
- [Writing Graders](/docs/guides/custom-grader) — Build your own evaluation
