Required specs and workflows auto-inject into every conversation. Write once, apply forever
Auto-updated Spec Library
Best practices live in auto-updated spec files. The more you use it, the better it gets
Parallel Sessions
Run multiple agents in tandem - each in its own worktree
Team Sync
Share specs across your team. One person's best practice benefits everyone
Session Persistence
Work traces persist in your repo. AI remembers project context across sessions
Quick Start
# 1. Install globally
npm install -g @mindfoldhq/trellis@latest
# 2. Initialize in your project directory
trellis init -u your-name
# Or include iFlow CLI support
trellis init --iflow -u your-name
# Or include Codex skills support
trellis init --codex -u your-name
# Or include Kilo CLI support
trellis init --kilo -u your-name
# Or include Kiro Code skills support
trellis init --kiro -u your-name
# Or include Gemini CLI support
trellis init --gemini -u your-name
# Or include Antigravity workflow support
trellis init --antigravity -u your-name
# 3. Start Claude Code and begin working
your-name becomes your identifier and creates a personal workspace at .trellis/workspace/your-name/
Use Cases
Educating Your AI
Write your specs in Markdown. Trellis injects them into every AI session — no more repeating yourself.
Define your component guidelines, file structure rules, and patterns once. AI automatically applies them when creating new code — using TypeScript with Props interface, following PascalCase naming, building functional components with hooks.
Ship in Parallel
Spawn multiple Claude sessions in isolated worktrees with /trellis:parallel. Work on several features at once, merge when ready.
While coding, each worker runs in its own worktree (physically isolated directory), no blocking, no interference. Review and merge completed features while others are still in progress.
Custom Workflows
Define custom skills & commands that prepare Claude for specific tasks and contexts.
Create commands like /trellis:before-frontend-dev that load component guidelines, check recent changes, pull in test patterns, and review shared hooks—all with a single slash.
Stronger Session Continuity — Autosave session-wide history
Visual Parallel Sessions — Real-time progress for each agent
FAQ
Why Trellis instead of Skills?
Skills are optional — AI may skip them, leading to inconsistent quality. Trellis enforces specs via Hook injection: not "can use" but "always applied". This turns randomness into determinism, so quality doesn't degrade over time.
Do I write spec files manually or let AI create them?
Most of the time, AI handles it — just say "We use Zustand, no Redux" and it creates the spec file automatically. But when you have architectural insights AI can't figure out on its own, that's where you step in. Teaching AI your team's hard-won lessons — that's why you won't lose your job to AI.
How is this different from CLAUDE.md / AGENTS.md / .cursorrules?
Those are all-in-one files — AI reads everything every time. Trellis uses layered architecture with context compression: only loads relevant specs for current task. Engineering standards should be elegantly layered, not monolithic.
Will multiple people conflict?
No. Each person has their own space at .trellis/workspace/{name}/.
How does AI remember previous conversations?
Use /trellis:record-session at the end of each conversation. AI writes a session summary to .trellis/workspace/{name}/journal-N.md and indexes it in index.md. Next time you /trellis:start, AI automatically reads recent journals and git info to restore context. In theory, you could just submit your daily journal files as your work report 🤣.
Star History
Community
Documentation — Full guides, API reference & tutorials
AI capabilities grow like ivy — Trellis provides the structure to guide them along a disciplined path
The npm package @mindfoldhq/trellis receives a total of 1,391 weekly downloads. As such, @mindfoldhq/trellis popularity was classified as popular.
We found that @mindfoldhq/trellis demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago.It has 1 open source maintainer collaborating on the project.
Package last updated on 03 Mar 2026
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