git:20260425.4d261b7 to git:20260517.5dcd509

8 added, 8 removed. Audit A to A.

---

name: factory

description: Launch the Factory CEO agent to autonomously evolve any software project through systematic experimentation. Detects project state, spawns specialist agents, runs evals, and archives learnings.

user_invocable: true

---

# Factory Skill v2 — CEO Launcher

This skill spawns the **Factory CEO Agent** — a dedicated autonomous orchestrator that manages the full factory workflow. The CEO delegates all execution to 7 specialist agents: Researcher, Strategist, Builder, Reviewer, Evaluator, Archivist, and (recursively) itself.

**Do not attempt to run the factory workflow yourself.** Delegate entirely to the CEO agent.

## Usage

```bash

# Resolve the factory installation root

- FACTORY_HOME="$(uv run python -m factory home)"

+ FACTORY_HOME="$(factory home)"

# Launch the CEO agent (default: improve mode)

- uv run python -m factory ceo "$(pwd)"

+ factory ceo "$(pwd)"

# Or specify a mode

- uv run python -m factory ceo "$(pwd)" --mode discover # Auto-detect evals

- uv run python -m factory ceo "$(pwd)" --mode improve # Improvement loop (default)

- uv run python -m factory ceo "$(pwd)" --mode meta # Self-improvement only (ACE)

+ factory ceo "$(pwd)" --mode discover # Auto-detect evals

+ factory ceo "$(pwd)" --mode improve # Improvement loop (default)

+ factory ceo "$(pwd)" --mode meta # Self-improvement only (ACE)

```

## What the CEO Does

1. **Detects project state** — routes to Build, Discover, Review, or Improve mode

2. **Spawns specialist agents** — each gets fresh context with evolved playbooks auto-injected

3. **Manages experiments** — begin, evaluate, implement, guard, evaluate, keep/revert

4. **Mandatory archival** — Archivist fires at every checkpoint (research, strategy, experiment, final)

5. **Self-learning** — CEO decisions feed ACE playbook evolution for all 7 agent roles

## Alternative Invocations

```bash

# Via factory run (same thing, supports heartbeat loop mode)

- uv run python -m factory run /path/to/project --loop --interval 1800

+ factory run /path/to/project --loop --interval 1800

# Via factory agent (invoke any specialist directly)

- uv run python -m factory agent researcher --task "Research the project" --project /path

+ factory agent researcher --task "Research the project" --project /path

# In a detached tmux session

- uv run python -m factory tmux /path/to/project --loop

+ factory tmux /path/to/project --loop

```

## Agent Roles

| Role | Prompt | Purpose |

|------------|-----------------------------------------|--------------------------------------|

| CEO | `factory/agents/prompts/ceo.md` | Orchestrate, decide, delegate |

| Researcher | `factory/agents/prompts/researcher.md` | Observe, research, synthesize |

| Strategist | `factory/agents/prompts/strategist.md` | Generate prioritized hypotheses |

| Builder | `factory/agents/prompts/builder.md` | Implement changes on feature branch |

| Reviewer | `factory/agents/prompts/reviewer.md` | Guard rules, scope, code quality |

| Evaluator | `factory/agents/prompts/evaluator.md` | Score before/after, interpret |

| Archivist | `factory/agents/prompts/archivist.md` | Record learnings to Obsidian vault |

All prompts support two-tier override: project-specific (`.factory/agents/<role>.md`) takes precedence over factory default. Evolved playbooks from `~/.factory/playbooks/<role>.md` (user-local, ACE-generated) are auto-injected, falling back to factory defaults in `factory/agents/playbooks/<role>.md`.