Trellis README

The project's README from github.com/mindfold-ai/Trellis. As one markdown file: README.md.

Trellis Logo

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

npm version npm downloads license stars docs Discord open issues open PRs Ask DeepWiki Ask ChatGPT

Trellis workflow demo

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:

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 actually use
trellis init --cursor --opencode --codex -u your-name

See the Quick Start and Supported Platforms 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
Understand platform differences Supported Platforms
See the workflow in practice Real-World Scenarios
Start from spec templates Spec Templates
Track releases Changelog

FAQ

How is Trellis different from CLAUDE.md, AGENTS.md, or .cursorrules?

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.

Is Trellis only for Claude Code?

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

Is Trellis for solo developers or teams?

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

Do I have to write every spec file manually?

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.

Can teams use this without constant conflicts?

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.

Can I temporarily compare a project with and without Trellis?

Yes. trellis ablate temporarily removes all supported project-owned Trellis surfaces after creating a verified recovery transaction outside the project. Start a fresh agent session for the comparison, then run trellis restore to recover the exact prior state. Use --dry-run to preview either operation. The private recovery transaction includes exact .trellis task, spec, and workspace bytes, which may contain user-authored sensitive text, and is kept until restore verifies successfully.

This is different from trellis uninstall (permanent removal) and TRELLIS_HOOKS=0 (hooks only). Ablation does not launch agents, manage worktrees, hide Git changes, or remove the global CLI, channel logs, or host transcripts. If a managed path changes while ablated, restore refuses all writes until the conflict is resolved.

Star History

Star History Chart

Community & Resources

Official Repository • AGPL-3.0 License • Built by Mindfold

Trellis (mindfold-ai/Trellis)

agentic-coding
Searching Database…

15K ·GitHub
Trellis
What is this?Trellis is an out-of-the-box engineering framework for AI coding. It persists specs, tasks, and project memory in your repo, so any coding agent works to your conventions instead of starting every session from scratch.
Is Trellis its own AI coding agent, or do I use it with the agent I already have?It is a project layer on top of your existing agents and IDEs, not a model or agent itself. The same Trellis structure works across 22 AI coding platforms, so you are not locked to Claude Code or Codex.
How do I set it up for my project?You need Node.js >= 18 and Python >= 3.9, then follow the Quick Start guide to install Trellis into your repo. It brings a trellis CLI plus a .trellis/ directory holding specs, tasks, and workspace journals.
What if I want to try my project without Trellis, or remove it later?trellis ablate temporarily strips Trellis surfaces and trellis restore brings back the exact prior state (use --dry-run to preview); trellis uninstall is permanent. Note that restore refuses writes if a managed path changed while ablated.
Is Trellis meant for solo developers or teams?Both. Solo developers get memory and a repeatable workflow; teams get shared standards, task boundaries, and reviewable context. Personal workspace journals stay separate per developer, while shared specs and tasks live in the repo.
What does a typical work session look like?Describe what you want in natural language and brainstorm with the AI one question at a time until the PRD is clear. Implementation then runs with auto-checks against specs, lint, type-check, and tests; type /trellis:finish-work to archive the task and update journals.
What happens under the hood during a task?A 4-phase loop: trellis-brainstorm writes prd.md (research-heavy items go to a trellis-research sub-agent), trellis-implement codes from the PRD with no git commit, trellis-check reviews the diff and runs lint, type-check, and tests with self-fixing, and trellis-update-spec promotes new learnings back into specs.
Where does Trellis keep everything?In your repo under .trellis/: spec/ for conventions auto-injected into each session, tasks/ for PRDs plus implementation and review context, and workspace/ for journals so each new session starts with real context.
Do I have to write all the spec files by hand?No. Many teams let the AI draft specs from existing code, then tighten the important parts by hand. Trellis works best when the high-signal rules stay explicit and versioned.
What are similar projects?superpowers-zh, gsd-core, operator-memory, autoprompt-skill, pstack-claude, oar, openrig, ECC
Which topics is it in?claudecode, spec-driven-development, subagents, agentic-coding, agent-harness, context-engineering, code-review, ai-coding, collaboration, harness, agent-memory, workflow
Creator
mindfold-ai
Size
238.9 MB
Stars
15K
Updated
CommitSep 29
Age
8mo
Commits · 90 Days