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ace-pm b29c12d5e5 refactor(native): rename gsd_parser.rs to forge_parser.rs 
Final rebrand: rename remaining Rust source file to complete the gsd → forge
transition. All parser references already use forge_parser after earlier commits.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-04-15 14:58:21 +02:00
..
configuration refactor(native): rename gsd_parser.rs to forge_parser.rs 2026-04-15 14:58:21 +02:00
core-concepts refactor(native): rename gsd_parser.rs to forge_parser.rs 2026-04-15 14:58:21 +02:00
features refactor(native): rename gsd_parser.rs to forge_parser.rs 2026-04-15 14:58:21 +02:00
getting-started refactor(native): rename gsd_parser.rs to forge_parser.rs 2026-04-15 14:58:21 +02:00
reference refactor(native): rename gsd_parser.rs to forge_parser.rs 2026-04-15 14:58:21 +02:00
README.md refactor(native): rename gsd_parser.rs to forge_parser.rs 2026-04-15 14:58:21 +02:00
SUMMARY.md chore: sync workspace state after rebrand 2026-04-15 14:54:20 +02:00

README.md

What is SF?

SF is an AI-powered development agent that turns project ideas into working software. Describe what you want to build, and SF researches, plans, codes, tests, and commits — with clean git history and full cost tracking.

How It Works

SF breaks your project into manageable pieces and works through them systematically:

You describe your project
    ↓
SF creates a milestone with slices (features)
    ↓
Each slice is decomposed into tasks
    ↓
Tasks are executed one at a time in fresh AI sessions
    ↓
Code is committed, verified, and the next task begins

You can stay hands-on with step mode (reviewing each step) or let SF run autonomously with auto mode while you grab coffee.

Key Features

  • Autonomous execution — /sf auto runs research, planning, coding, testing, and committing without intervention
  • 20+ LLM providers — Anthropic, OpenAI, Google, OpenRouter, GitHub Copilot, Amazon Bedrock, local models, and more
  • Git isolation — Each milestone works in its own worktree branch, merged cleanly when done
  • Cost tracking — Real-time token usage, budget ceilings, and automatic model downgrading
  • Crash recovery — Sessions resume automatically after interruptions
  • Skills system — Domain-specific instruction sets for frameworks, languages, and tools
  • Parallel milestones — Run multiple milestones simultaneously in isolated worktrees
  • Remote questions — Get Discord, Slack, or Telegram notifications when SF needs input
  • Web interface — Browser-based dashboard with real-time progress
  • VS Code extension — Chat participant, sidebar dashboard, and full command palette
  • Headless mode — Run in CI pipelines, cron jobs, and scripted automation

Quick Start

# Install
npm install -g sf-run

# Launch
sf

# Start autonomous mode
/sf auto

See Installation for detailed setup instructions.

Two Ways to Work

Mode Command Best For
Step /sf Staying in the loop, reviewing each step
Auto /sf auto Walking away, overnight builds, batch work

The recommended workflow: run auto mode in one terminal, steer from another. See Step Mode and Auto Mode.

Requirements

  • Node.js 22.0.0 or later (24 LTS recommended)
  • Git installed and configured
  • An API key for at least one LLM provider (or use browser sign-in for Anthropic/GitHub Copilot)