mindfold-ai

Trellis

Spec, task and memory layer that lives in your repo: .trellis/ holds conventions, PRDs and journals, auto-injected each session — one workflow across 20 coding-agent platforms.

15,028 872 TypeScript AGPL-3.0updated 27 days ago

coding memory

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Curator's take

Attacks the right problem — agents restart from zero every session — with the boring, durable fix: files in the repo, not a memory service. Team-shared specs are the real moat; one engineer's hard-won rules compound for everyone. It's opinionated though: the 4-phase loop (brainstorm → implement → check → update-spec) only pays if the team actually adopts the process — half-adopted, .trellis/ rots into stale paperwork. AGPL-3.0: fine to use, but check your company's license policy. Skip it for weekend projects; this is process overhead that needs a team to amortize.

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README.md1 min read

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

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 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