sinoclaw-agent 2026.5.2

The self-improving AI agent — creates skills from experience, improves them during use, and runs anywhere

Sinoclaw Agent ☤

The self-improving AI agent built by Sinoclaw Team. It's the only agent with a built-in learning loop — it creates skills from experience, improves them during use, nudges itself to persist knowledge, searches its own past conversations, and builds a deepening model of who you are across sessions. Run it on a $5 VPS, a GPU cluster, or serverless infrastructure that costs nearly nothing when idle. It's not tied to your laptop — talk to it from Telegram while it works on a cloud VM.

Use any model you want — Nous Portal, OpenRouter (200+ models), NVIDIA NIM (Nemotron), Xiaomi MiMo, z.ai/GLM, Kimi/Moonshot, MiniMax, Hugging Face, OpenAI, or your own endpoint. Switch with sinoclaw model — no code changes, no lock-in.

A real terminal interface	Full TUI with multiline editing, slash-command autocomplete, conversation history, interrupt-and-redirect, and streaming tool output.
Lives where you do	Telegram, Discord, Slack, WhatsApp, Signal, and CLI — all from a single gateway process. Voice memo transcription, cross-platform conversation continuity.
A closed learning loop	Agent-curated memory with periodic nudges. Autonomous skill creation after complex tasks. Skills self-improve during use. FTS5 session search with LLM summarization for cross-session recall. Honcho dialectic user modeling. Compatible with the agentskills.io open standard.
Scheduled automations	Built-in cron scheduler with delivery to any platform. Daily reports, nightly backups, weekly audits — all in natural language, running unattended.
Delegates and parallelizes	Spawn isolated subagents for parallel workstreams. Write Python scripts that call tools via RPC, collapsing multi-step pipelines into zero-context-cost turns.
Runs anywhere, not just your laptop	Six terminal backends — local, Docker, SSH, Daytona, Singularity, and Modal. Daytona and Modal offer serverless persistence — your agent's environment hibernates when idle and wakes on demand, costing nearly nothing between sessions. Run it on a $5 VPS or a GPU cluster.
Research-ready	Batch trajectory generation, Atropos RL environments, trajectory compression for training the next generation of tool-calling models.

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Quick Install

curl -fsSL https://raw.githubusercontent.com/NousResearch/sinoclaw-agent/main/scripts/install.sh | bash

Works on Linux, macOS, WSL2, and Android via Termux. The installer handles the platform-specific setup for you.

Android / Termux: The tested manual path is documented in the Termux guide. On Termux, Sinoclaw installs a curated .[termux] extra because the full .[all] extra currently pulls Android-incompatible voice dependencies.

Windows: Native Windows is not supported. Please install WSL2 and run the command above.

After installation:

source ~/.bashrc    # reload shell (or: source ~/.zshrc)
sinoclaw              # start chatting!

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Getting Started

sinoclaw              # Interactive CLI — start a conversation
sinoclaw model        # Choose your LLM provider and model
sinoclaw tools        # Configure which tools are enabled
sinoclaw config set   # Set individual config values
sinoclaw gateway      # Start the messaging gateway (Telegram, Discord, etc.)
sinoclaw setup        # Run the full setup wizard (configures everything at once)
sinoclaw claw migrate # Migrate from OpenClaw (if coming from OpenClaw)
sinoclaw update       # Update to the latest version
sinoclaw doctor       # Diagnose any issues

📖 Full documentation →

CLI vs Messaging Quick Reference

Sinoclaw has two entry points: start the terminal UI with sinoclaw, or run the gateway and talk to it from Telegram, Discord, Slack, WhatsApp, Signal, or Email. Once you're in a conversation, many slash commands are shared across both interfaces.

Action	CLI	Messaging platforms
Start chatting	sinoclaw	Run sinoclaw gateway setup + sinoclaw gateway start, then send the bot a message
Start fresh conversation	/new or /reset	/new or /reset
Change model	/model [provider:model]	/model [provider:model]
Set a personality	/personality [name]	/personality [name]
Retry or undo the last turn	/retry, /undo	/retry, /undo
Compress context / check usage	/compress, /usage, /insights [--days N]	/compress, /usage, /insights [days]
Browse skills	/skills or /<skill-name>	/<skill-name>
Interrupt current work	Ctrl+C or send a new message	/stop or send a new message
Platform-specific status	/platforms	/status, /sethome

For the full command lists, see the CLI guide and the Messaging Gateway guide.

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Documentation

All documentation lives at sinoclaw-agent.nousresearch.com/docs:

Section	What's Covered
Quickstart	Install → setup → first conversation in 2 minutes
CLI Usage	Commands, keybindings, personalities, sessions
Configuration	Config file, providers, models, all options
Messaging Gateway	Telegram, Discord, Slack, WhatsApp, Signal, Home Assistant
Security	Command approval, DM pairing, container isolation
Tools & Toolsets	40+ tools, toolset system, terminal backends
Skills System	Procedural memory, Skills Hub, creating skills
Memory	Persistent memory, user profiles, best practices
MCP Integration	Connect any MCP server for extended capabilities
Cron Scheduling	Scheduled tasks with platform delivery
Context Files	Project context that shapes every conversation
Architecture	Project structure, agent loop, key classes
Contributing	Development setup, PR process, code style
CLI Reference	All commands and flags
Environment Variables	Complete env var reference

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Migrating from OpenClaw

If you're coming from OpenClaw, Sinoclaw can automatically import your settings, memories, skills, and API keys.

During first-time setup: The setup wizard (sinoclaw setup) automatically detects ~/.openclaw and offers to migrate before configuration begins.

Anytime after install:

sinoclaw claw migrate              # Interactive migration (full preset)
sinoclaw claw migrate --dry-run    # Preview what would be migrated
sinoclaw claw migrate --preset user-data   # Migrate without secrets
sinoclaw claw migrate --overwrite  # Overwrite existing conflicts

What gets imported:

• SOUL.md — persona file
• Memories — MEMORY.md and USER.md entries
• Skills — user-created skills → ~/.sinoclaw/skills/openclaw-imports/
• Command allowlist — approval patterns
• Messaging settings — platform configs, allowed users, working directory
• API keys — allowlisted secrets (Telegram, OpenRouter, OpenAI, Anthropic, ElevenLabs)
• TTS assets — workspace audio files
• Workspace instructions — AGENTS.md (with --workspace-target)

See sinoclaw claw migrate --help for all options, or use the openclaw-migration skill for an interactive agent-guided migration with dry-run previews.

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Contributing

We welcome contributions! See the Contributing Guide for development setup, code style, and PR process.

Quick start for contributors — clone and go with setup-sinoclaw.sh:

git clone https://github.com/NousResearch/sinoclaw-agent.git
cd sinoclaw-agent
./setup-sinoclaw.sh     # installs uv, creates venv, installs .[all], symlinks ~/.local/bin/sinoclaw
./sinoclaw              # auto-detects the venv, no need to `source` first

Manual path (equivalent to the above):

curl -LsSf https://astral.sh/uv/install.sh | sh
uv venv venv --python 3.11
source venv/bin/activate
uv pip install -e ".[all,dev]"
scripts/run_tests.sh

RL Training (optional): The RL/Atropos integration (environments/) ships via the atroposlib and tinker dependencies pulled in by .[all,dev] — no submodule setup required.

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Community

• 💬 Discord
• 📚 Skills Hub
• 🐛 Issues
• 🔌 SinoclawClaw — Community WeChat bridge: Run Sinoclaw Agent and OpenClaw on the same WeChat account.

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License

MIT — see LICENSE.

Built by Sinoclaw Team.