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Trellis

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The best agent harness.

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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.

<a href="./README_CN.md">简体中文</a> •
<a href="https://docs.trytrellis.app/">Docs</a> •
<a href="https://docs.trytrellis.app/start/install-and-first-task">Quick Start</a> •
<a href="https://docs.trytrellis.app/advanced/multi-platform">Supported Platforms</a> •
<a href="https://docs.trytrellis.app/start/real-world-scenarios">Use Cases</a>

## 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 22 AI coding platforms instead of rebuilding your workflow per tool. |

## Prerequisites:

- **Node.js** >= 18
- **Python** >= 3.9

## Quick Start

```bash
# 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 actually use
trellis init --cursor --opencode --codex -u your-name
```

See the [Quick Start](https://docs.trytrellis.app/start/install-and-first-task) and [Supported Platforms](https://docs.trytrellis.app/advanced/multi-platform) guides for setup details.

## How to Use

The workflow is simple:

1. **Describe what you want** in natural language.
2. **Brainstorm** with the AI one question at a time until the PRD is clear, then implementation begins.
3. **Let it run** — the AI calls Trellis Implement and auto-checks the result against specs, lint, type-check, and tests.
4. **Type `/trellis:finish-work`** when the work is done or the session context fills up. Trellis archives the task and updates journals.

## How It Works

Trellis runs a 4-phase loop with auto-invoked skills and sub-agents:

1. **Plan** — `trellis-brainstorm` walks through requirements one question at a time and writes `prd.md`. Research-heavy items go to a `trellis-research` sub-agent. The result is curated specs + research files referenced from `implement.jsonl` / `check.jsonl`.
2. **Implement** — a `trellis-implement` sub-agent writes code from the PRD with the curated context auto-injected, no git commit.
3. **Verify** — a `trellis-check` sub-agent reviews the diff against specs and runs lint, type-check, and tests, self-fixing where it can.
4. **Finish** — a final check runs, then `trellis-update-spec` promotes new learnings back into `.trellis/spec/` so the next session starts smarter.

## Resources

| Need                            | Link                                                                           |
| ------------------------------- | ------------------------------------------------------------------------------ |
| Install Trellis in a repo       | [Quick Start](https://docs.trytrellis.app/start/install-and-first-task)        |
| Understand platform differences | [Supported Platforms](https://docs.trytrellis.app/advanced/multi-platform)     |
| See the workflow in practice    | [Real-World Scenarios](https://docs.trytrellis.app/start/real-world-scenarios) |
| Start from spec templates       | [Spec Templates](https://docs.trytrellis.app/templates/specs-index)            |
| Track releases                  | [Changelog](https://docs.trytrellis.app/changelog)                             |

## FAQ

<details>
<summary>How is Trellis different from <code>CLAUDE.md</code>, <code>AGENTS.md</code>, or <code>.cursorrules</code>?</summary>

Those files are useful entry points, but they tend to become monolithic. Trellis adds scoped specs, task PRDs, workflow gates, workspace memory, and platform-aware generated files around them.

</details>

<details>
<summary>Is Trellis only for Claude Code?</summary>

No. Trellis is a project layer that works across multiple coding agents and IDEs.

</details>

<details>
<summary>Is Trellis for solo developers or teams?</summary>

Both. Solo developers use it for memory and repeatable workflow. Teams get the larger benefit: shared standards, task boundaries, reviewable context, and platform portability.

</details>

<details>
<summary>Do I have to write every spec file manually?</summary>

No. Many teams start by letting AI draft specs from existing code and then tighten the important parts by hand. Trellis works best when you keep the high-signal rules explicit and versioned.

</details>

<details>
<summary>Can teams use this without constant conflicts?</summary>

Yes. Personal workspace journals stay separate per developer, while shared specs and tasks stay in the repo where they can be reviewed and improved like any other project artifact.

</details>

## Star History

[![Star History Chart](https://api.star-history.com/svg?repos=mindfold-ai/Trellis&type=Date)](https://star-history.com/#mindfold-ai/Trellis&Date)

## Community & Resources

- [Official Docs](https://docs.trytrellis.app/)
- [GitHub Issues](https://github.com/mindfold-ai/Trellis/issues)
- [Discord](https://discord.com/invite/tWcCZ3aRHc)
- [Tech Blog](https://docs.trytrellis.app/blog)

<a href="https://github.com/mindfold-ai/Trellis">Official Repository</a> •
<a href="https://github.com/mindfold-ai/Trellis/blob/main/LICENSE">AGPL-3.0 License</a> •
Built by <a href="https://github.com/mindfold-ai">Mindfold</a>

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