@Xudong07452910: Strongly recommended open-source project: Trellis — an open-source harness that gives your AI coding agent team-level engineering standards. Trellis is the AI coding engineering framework I've been using, known as 'The best agent harness'. It…

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Summary

Trellis is an open-source project that provides team-level engineering standards and a project memory framework for AI coding agents. It supports multiple platforms and enhances agent development efficiency and quality by persisting specifications and task context to code repositories.

Strongly recommended open-source project: Trellis — an open-source harness that gives your AI coding agent team-level engineering standards. Trellis is the AI coding engineering framework I've been using, known as "The best agent harness". By persisting project specifications, task context, and memory to the code repository, it ensures that AI agents (such as Claude Code, Codex, Hermes Agent, etc.) no longer start from scratch each time, but instead have team-level engineering standards and cross-platform consistency, significantly improving development efficiency and code quality. Specifically: Many people feel that AI coding agents become less reliable over time, and their first reaction is to switch models, pile on prompts, or add longer context. But the problem is often not the model — it's that every time the agent enters a project, it comes in with an "empty mind": It doesn't know the project structure, naming conventions, technology choices, or where it left off last time. What Trellis does is equip the AI coding agent with a set of project-level engineering memory. It creates a .trellis/ directory in your codebase, where project specifications, task PRDs, implementation context, review records, and session logs are stored, and version-controlled alongside the code. In other words, instead of teaching the AI how to write the project from scratch every time, you let it read the project's own "engineering manual" before starting work. Its greatest value is not simply stuffing in context, but turning the AI coding process into a standardized workflow: 1. Plan: Clarify requirements first 2. Implement: Write code according to the PRD and project specifications 3. Verify: Self-check against lint, type check, tests, and specs 4. Finish: Write the pitfalls encountered and new rules back into project memory It's much like training a "smart but daily-amnesiac temp worker" into a "team member who knows the project rules and can continue from where they left off". More importantly, Trellis is not tied to any specific tool. It supports 14 AI coding platforms including Claude Code, Codex, Cursor, OpenCode, Gemini CLI, GitHub Copilot, etc. Specifications established by one person in the team can be inherited by all the team's AI agents. Core features: 1. Auto-inject specifications: Write once in .trellis/spec/, AI loads automatically on each session 2. Task-centric workflow: .trellis/tasks/ stores PRDs, implementation context, review records 3. Project memory: .trellis/workspace/ records the last session state 4. Team shared standards: Specifications are version-controlled with code, shared by the team It has already gained 9.7k+ stars, with documentation in Chinese and English, and an active community. It's especially suitable for individual developers, team engineers, and heavy users of AI coding tools. I'd also like to recommend one of the project's lead contributors: Card Master Cuisi @cuisitekp. https://github.com/mindfold-ai/Trellis… #AIAgent #ClaudeCode #AgentHarness #AITools #OpenSourceProject #Codex
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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.

Simplified Chinese • Docs • Quick Start • Supported Platforms • Use Cases

Official Repository • AGPL-3.0 License • Built by Mindfold

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@cuisitekp: Those who have been using Claude Code or Codex for projects for a long time should really try installing Trellis. It's not an exaggeration to say it's the closest solution to "making AI remember your project" right now. Many people find that AI becomes increasingly unreliable over time, and their first reaction is to switch to a more powerful model or pile on longer prompts...

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