README.md
An out-of-the-box engineering framework for AI coding.
AI writes code fast, but every session it starts from scratch — no memory of your project, your conventions, or your team's requirements. Trellis persists specs, tasks, and memory into your repo, so any coding agent works to your engineering standards.
简体中文 • Docs • Quick Start • Supported Platforms • Use Cases
Why Trellis?
| Capability | What it changes |
|---|---|
| Auto-injected specs | Write conventions once in .trellis/spec/, then let Trellis inject the relevant context into each session instead of repeating yourself. |
| Task-centered workflow | Keep PRDs, implementation context, review context, and task status in .trellis/tasks/ so AI work stays structured. |
| Project memory | Journals in .trellis/workspace/ preserve what happened last time, so each new session starts with real context. |
| Team-shared standards | Specs live in the repo, so one person's hard-won workflow or rule can benefit the whole team. |
| Multi-platform setup | Bring the same Trellis structure to 20 AI coding platforms instead of rebuilding your workflow per tool. |
Prerequisites:
- Node.js >= 18
- Python >= 3.9
Quick Start
# 1. Install Trellis
npm install -g @mindfoldhq/trellis@latest
# 2. Initialize in your repo
trellis init -u your-name
# 3. Or initialize with the platforms you actua