SoduWork
by mdiri-ai
The AI-native engine for teams and their agents. Multi-harness, multi-agent, self-hosted.
69stars
10forks
JavaScript
Added 11/10/2026
Available after the catalog security scan passes.
⚠️ Third-Party Software Notice
This skill is third-party open-source software developed and hosted independently on GitHub. SkillsLLM is an informational directory and does not control or maintain the underlying repository.
Any security checks, ratings, or warnings displayed by SkillsLLM are automated and limited in scope. They do not constitute a security certification or guarantee that the software is safe, error-free, or free from malicious code, vulnerabilities, compromised dependencies, or prompt-injection risks.
Review the source code, permissions, dependencies, and configuration before installing or running any third-party skill. Use is at your own risk. To the maximum extent permitted by applicable law, SkillsLLM is not liable for losses arising from third-party software.
The deep catalog scan for this skill is still queued. Run an instant dependency check now instead.
AI Agentsagent-harnessagent-orchestrationagent-workflowsai-agentsai-workflowsanti-slopclaude-codecodexdeepseekelectronfastapiharnesshuman-in-the-looplllmmcpmulti-agentopencodeplugin-systemself-hostedteam-collaboration
Maintainer of this skill?
Installation
# Add to your Claude Code skills
git clone https://github.com/mdiri-ai/SoduWorkGetting Started
Guides for using ai agents skills like SoduWork.
- Caveman: Cut Claude Token Use by 65%How agent-side prompt compression works, when to use it, and when not to.
- How to Test an AI Skill: A Practical Guide to EvalsEvaluate skills with realistic fixtures, a baseline, and repeatable checks.
- Getting Started with AI SkillsFirst-time install walkthrough for Claude Code, Codex CLI, and ChatGPT.
Compare with similar skills
See how SoduWork compares with popular alternatives.
English · 简体中文
SoduWork
The AI-native engine for teams and their agents
A chat ends with an answer. A SoduWork request ends when the person who asked signs off.
Multi-harness · Multi-agent · Self-hosted
Works with Pi · OpenCode · DeepSeek Harness · Qwen Code · Kimi Code · Codex Harness · Codex · Claude Code · Google Harness²
git clone https://github.com/mdiri-ai/SoduWork && cd SoduWork && python start.py --desktop
Website | Live demo | Docs | Releases | Discord
What SoduWork can do for you
| One harness does the work, another reviews it | Pick Pi to do the work. OpenCode, on a different model, reviews it against the acceptance criteria. If the review fails, the work goes back with the reasons. |
| Hand a request to a colleague's agent | People and AI work together: you file a request, AI writes the acceptance criteria, and you assign it to yourself or a colleague. The assignee's agent does the work and reviews it, and a person signs off. Everyone on the request can see who did what. |
| Turn one person's know-how into a team asset | When you and AI get a task right, save the chat as a plugin. After review, anyone on the team can use it and contribute improvements, with access granted as needed. |
Core ideas
🔀 Smart dispatch
The right agent and model for each job.
- Pick a harness for each step and switch mid-conversation
- Routine steps on cheap or local models, strong models where it matters
- Long tasks go to your own cloud runner
🛡️ Built-in governance
Your organization decides which AI does what, and where.
- Plugins are reviewed before they are shared, granted to teams or people, and can be revoked
- Roles, usage, cost and an audit log
- Self-hosted
✅ Verified delivery
Set the bar first. Done means the requester signed off.
- Every request carries its acceptance criteria
- A separate AI review checks each one
- A person makes the final call
Quick start
SoduWork is in public beta. Try it and tell us what you think, and evaluate it before using it in production.
You need Python 3.12+, Node.js 22.19+ and Git.
git clone https://github.com/mdiri-ai/SoduWork && cd SoduWork
python start.py --desktop
The first run installs dependencies, then starts the Hub, the admin console and the desktop client on this computer. Set a password for the admin account (12–128 characters) when asked. Then add a model provider under Model catalog in the admin console, start a chat in the client and try a small task. Pi is built in.
Download the client from Releases, enter https://soduwork.ai under Connection on the sign-in screen, then sign up and sign in.
The demo is for evaluation only. Don't upload real business data or anything sensitive.
| OS | Package |
|---|---|
| Windows | SoduWork-<version>-Setup.exe |
| macOS (Apple Silicon / Intel) | SoduWork-<version>-mac-<arch>.dmg |
| Linux | SoduWork-<version>-linux.deb / .rpm / .tar.gz |
Download from Releases. On first launch, enter your Hub address under Connection, then sign in. On macOS, if you see "cannot verify the developer", open System Settings → Privacy & Security and choose Open Anyway.
With Docker installed and running, from the repository root:
python ops/self-host/deploy.py up
python ops/self-host/deploy.py credentials # show the initial admin password
This starts the Hub, the admin console and PostgreSQL on one server. Put an HTTPS reverse proxy in front of it to open it to your team. See Deploy with Docker and Deploy for a team.
Ports, data folders and troubleshooting are in Run from source and the FAQ.
Why SoduWork
AI agents give everyone fast output. What no one gets for free is trust in that output — or a way to keep what worked. That's where individuals and teams get stuck alike:
| The problem | What SoduWork does |
|---|---|
| Fast output, slow trust — whether you work alone or in a team, the time AI saves goes back into checking what it produced | The request is the spec. Criteria set before work starts; a separate AI review checks each one; a person signs off |
| What worked dies in a chat thread — for one person, it's last month's perfect run you can't reproduce; for a team, it's one person's method nobody else can use | Get it right once, keep it as a plugin. Reuse it yourself or publish it for everyone — every improvement reaches everyone |
| A drawer full of AI tools — three subscriptions and no standard for which one does what | One workbench, your playbook. Your plugins run on every harness. Switch mid-conversation, keep your history and files |
| Results that never enter the workflow — output gets copy-pasted around, and every handoff re-explains the background | Issues that carry the context. People and agents pick up where it left off, with a full record of who did what |
How it works
Requests, execution, review and reuse all happen in one shared issue pool:
flowchart LR
A[Raise a request] --> B[AI refines it<br/>adds acceptance criteria]
B --> C[Assign<br/>yourself · a colleague · an agent]
C --> D[Agent runs it<br/>with a team plugin]
D --> E[AI review<br/>assignee confirms]
E --> F[Requester signs off]
F --> G[Save as a plugin]
G -.reused by the team.-> D
| Role | Where they join |
|---|---|
| Solo developer | Puts requests in the pool, lets agents work through them, and only signs off |
| Specialist | Gets a task right with AI, saves the method as a plugin, and publishes it to the team |
| Manager | Drops in a request; AI fills in the criteria and routes it to a person or an agent; signs off at the end |
| New team member | Uses the plugins the organization has built up to do the work to team standards, and improves them when they find a gap |
Who asked, who did the work, which plugin ran and who approved it is always on record.
Multi-harness · Multi-agent
A harness is the agent runtime that does the work. It is not the model. SoduWork connects every harness through one adapter interface, so issues, plugins and review don't depend on any single harness. Switch harnesses mid-conversation and keep the history and the working folder. Programs that support the Agent Client Protocol (ACP) can be added with a catalog declaration.
| Harness | Models | How it connects |
|---|---|---|
| Pi | Your SoduWork models | Built in |
| OpenCode | Your SoduWork models | Native adapter, installed on demand |
| DeepSeek Harness | Your SoduWork models, or your own DeepSeek key | ACP, installed on demand |
| Qwen Code | Your SoduWork models | ACP, installed on demand |
| Kimi Code | Your SoduWork models | ACP, installed on demand |
| Codex Harness | Your SoduWork models | ACP, installed on demand |
| Codex | Its own OpenAI account | Native adapter, installed on demand |
| Claude Code | Its own Anthropic account | ACP adapter, official installer |
| Google Harness² | Your SoduWork models | Native adapter; core bundled, prepared on first use |
Agents work together at several levels:
| Level | Who decides | Example |
|---|---|---|
| Harness | The harness itself | OpenCode or Qwen Code starts its own subagents to explore the code or split a task |
| Single method | A Skill or plugin sets the method, process, rules and what counts as done | A review plugin tells the agent which checks to run and what evidence to attach |
| Combined methods | A plugin workflow picks the harness, Skill and model for each step | Pi drafts, Qwen Code checks the sources, and the run stops if the check fails |
| People and agents | The requester and the assignee or their agent | A request goes to a colleague, their agent does the work, the requester signs off |
| In parallel | The Hub | Different issues run on different agents at the same time, including on cloud runners |
Between steps and between people, work moves the way the plugin and the assignee say. Agents don't hand work to other agents on their own.
Plugins and apps
A skill tells AI how to do something. An agent wraps AI into an assistant. SoduWork plugins and apps turn the way your team works into something that runs, gets verified, improves and stays governed.
| Skill | Agent | SoduWork plugin | SoduWork app | |
|---|---|---|---|---|
| What it is | A method doc that AI reads and follows | Prompts, knowledge, tools or a platform flow | A versioned package: method, inputs, acceptance criteria, workflow | A |
Frequently Asked Questions
What is SoduWork?
SoduWork is an open-source ai agents skill for AI coding assistants such as Claude Code, Codex CLI, and ChatGPT, built by mdiri-ai. The AI-native engine for teams and their agents. Multi-harness, multi-agent, self-hosted. It has 69 GitHub stars.
Is SoduWork safe to use?
SoduWork's catalog security scan is still queued. You can run an instant dependency and prompt-injection check now with the "Scan for vulnerabilities" button above.
How do I install SoduWork?
Clone the repository with "git clone https://github.com/mdiri-ai/SoduWork" and add it to your Claude Code skills directory (see the Installation section above).
What programming language is SoduWork written in?
SoduWork is primarily written in JavaScript. It is open-source under mdiri-ai on GitHub, so you can review or fork the full source.
Are there alternatives to SoduWork?
Yes. SkillsLLM lists many other AI Agents skills you can browse and compare side by side. Open the AI Agents category from the badge at the top of this page, or use the Related Skills and comparison links further down to weigh SoduWork against similar tools.
Comments (0)
to leave a comment.
No comments yet. Be the first to share your thoughts!
Related Skills
Reverse engineer anything with agents, from app behavior down to native binaries.
448,394
110,517
TypeScript
AI Agentsagent-skillsai
The agent harness performance optimization system. Skills, instincts, memory, security, and research-first development for Claude Code, Codex, Opencode, Cursor and beyond.
300,442
44,354
JavaScript
AI Agentsai-agentsanthropic
Skills for Real Engineers. Straight from my .agents directory.
250,518
21,171
Shell
AI Agents
An agentic skills framework & software development methodology that works.
234,966
20,863
Shell
AI Agentsaibrainstorming