✨ OpenSpace: Make Your Agents: Smarter, Low-Cost, Self-Evolving ✨

| 🔋 46% Fewer Tokens | 💰 $11K earned in 6 Hours | 🧬 Self-Evolving Skills | 🌐 Agents Experience Sharing |

One Command to Evolve All Your AI Agents: OpenClaw, nanobot, Claude Code, Codex, Cursor and etc.

---

📢 News

• 2026-04-03 🚀 Released v0.1.0 — Skill quality monitoring: structural patterns extracted from high-quality skills now evaluate every new submission daily. Faster, more relevant cloud search. Production-grade vertical skill clusters emerging organically from the community. Frontend now supports Chinese (zh) i18n.
• 2026-04-02 ⚡ Cloud search upgraded for higher relevance and lower latency.
• 2026-03-31 🛡️ Security hardening: hardened zip extraction and import_skill against path traversal. CLI now respects OPENSPACE_MODEL and OPENSPACE_LLM_* env vars; MiniMax compatibility; workflow ID collision fixes.
• 2026-03-29 🔒 Pinned litellm to <1.82.7 to avoid PYSEC-2026-2 supply-chain attack.
• 2026-03-28 🔧 Idempotent skill registration — register_skill_dir now returns existing SkillMeta for already-registered skills. Updated OpenClaw setup docs.
• 2026-03-27 🪟 Fixed stdio deadlock on Windows; improved evolver confirmation parsing with stem-style keyword matching.
• 2026-03-26 🌱 Dynamic skill directory re-scanning on each call, lightweight local skill search, and streamlined documentation.
• 2026-03-25 🎉 OpenSpace is now open source!

---

The Problem with Today's AI Agents

Today's AI agents — OpenClaw, nanobot, Claude Code, Codex, Cursor, etc. — are powerful, but they have a critical weakness: they never Learn, Adapt, and Evolve from real-world experience — let alone Share with each other.

• ❌ Massive Token Waste - How to reuse successful task patterns instead of reasoning from scratch and burning tokens every time?
• ❌ Repeated Costly Failures - How to share solutions across agents instead of repeating the same costly exploration and mistakes?
• ❌ Poor and Unreliable Skills - How to maintain skill reliability as tools and APIs evolve — while ensuring community-contributed skills meet rigorous quality standards?

🎯 What is OpenSpace?

🚀 🚀 The self-evolving engine where every task makes every agent smarter and more cost-efficient.

https://github.com/user-attachments/assets/c50f70ab-f6db-47bf-9498-3210c0f0abae

OpenSpace plugs into any agent as skills and evolves it with three superpowers:

🧬 Self-Evolution

Skills that learn and improve themselves automatically

• ✅ AUTO-FIX — When a skill breaks, it fixes itself instantly
• ✅ AUTO-IMPROVE — Successful patterns become better skill versions
• ✅ AUTO-LEARN — Captures winning workflows from actual usage
• ✅ Quality monitoring — Tracks skill performance, error rates, and execution success across all tasks.

Skills that continuously evolve — turning every failure into improvement, every success into optimization.

🌐 Collective Agent Intelligence

Turn individual agents into a shared brain

• ✅ Shared evolution: One agent's improvement becomes every agent's upgrade
• ✅ Network effects: More agents → richer data → faster evolution for every agent
• ✅ Easy sharing — Upload and download evolved skills with one simple command
• ✅ Access control — Choose public, private, or team-only access for each skill

One agent learns, all agents benefit — collective intelligence at scale.

💰 Token Efficiency

Smarter agents, dramatically lower costs

• ✅ Stop repeating work → Reuse successful solutions instead of starting from zero each time
• ✅ Tasks get cheaper → As skills improve, similar work costs less and less
• ✅ Small updates only → Fix what's broken, don't rebuild everything
• ✅ Real savings: 4.2× better performance with 46% fewer tokens on real-world tasks, delivering measurable economic value. (GDPVal)

Do more, spend less — agents that actually save you money over time.

---

The Difference

❌ Current Agents

• Skills degrade silently as tools evolve
• Failed patterns repeat with no learning mechanism
• Knowledge remains trapped in individual agents

✅ OpenSpace-Powered Agents

• Multi-layer monitoring catches problems and auto-triggers repairs
• Successful workflows become reusable, shareable skills
• When one agent learns something useful, all agents get that knowledge instantly

📊 OpenSpace: Turn Your Agent into a Money-Making Coworker

🎯 Real-World Results That Matter On 50 professional tasks (📈 GDPVal Economic Benchmark) across 6 industries, OpenSpace agents earn 4.2× more money than baseline (ClawWork) agents using the same backbone LLM (Qwen 3.5-Plus). While cutting 46% of costly tokens through skill evolution.

💼 These Aren't Toy Problems

• Building payroll calculators from complex union contracts
• Preparing tax returns from 15 scattered PDF documents
• Drafting legal memoranda on California privacy regulations
• Creating compliance forms and engineering specifications

📈 Consistent Wins Across All Fields

• Compliance work: +18.5% higher earnings
• Engineering projects: +8.7% better performance
• Professional documents: 56% fewer tokens needed
• Every category improved — no exceptions

OpenSpace doesn't just make agents smarter — it makes them economically viable. Real work, real money, measurable results.

Use Case for Autonomous System Development with OpenSpace

🖥️ My Daily Monitor — OpenSpace empowers your agent to complete large-scale system development. This personal behavior monitoring system with 20+ live dashboard panels was built entirely by the agent — 60+ skills evolved from scratch through OpenSpace, demonstrating autonomous end-to-end software development capabilities.

---

📋 Table of Contents

• ⚡ Quick Start
  • 🤖 Path A: For Your Agent
  • 👤 Path B: As Your Co-Worker
  • 📊 Local Dashboard
• 🐳 Docker Deployment
• 📈 Benchmark: GDPVal
• 📊 Showcase: My Daily Monitor
• 🏗️ Framework
  • 🧬 Self-Evolution Engine
  • 🌐 Cloud Skill Community
• 🔧 Advanced Configuration
• 📖 Code Structure
• 🤝 Contribute & Roadmap
• 🔗 Related Projects

---

⚡ Quick Start

🌐 Just want to explore? Browse community skills, evolution lineage at open-space.cloud — no installation needed.

git clone https://github.com/HKUDS/OpenSpace.git && cd OpenSpace
pip install -e .
openspace-mcp --help   # verify installation

Tip

Slow clone? The assets/ folder (~50 MB of images) makes the default clone large. Use this lightweight alternative to skip it:

git clone --filter=blob:none --sparse https://github.com/HKUDS/OpenSpace.git
cd OpenSpace
git sparse-checkout set '/*' '!assets/'
pip install -e .

Choose your path:

• Path A — Plug OpenSpace into your agent
• Path B — Use OpenSpace directly as your AI co-worker

🤖 Path A: For Your Agent

Works with any agent that supports skills (SKILL.md) — Claude Code, Codex, OpenClaw, nanobot, etc.

① Add OpenSpace to your agent's MCP config:

{
  "mcpServers": {
    "openspace": {
      "command": "openspace-mcp",
      "toolTimeout": 600,
      "env": {
        "OPENSPACE_HOST_SKILL_DIRS": "/path/to/your/agent/skills",
        "OPENSPACE_WORKSPACE": "/path/to/OpenSpace",
        "OPENSPACE_API_KEY": "sk-xxx (optional, for cloud)"
      }
    }
  }
}

Tip

Credentials (API key, model) are auto-detected from your agent's config; you usually don't need to set them manually.

② Copy skills into your agent's skills directory:

cp -r OpenSpace/openspace/host_skills/delegate-task/ /path/to/your/agent/skills/
cp -r OpenSpace/openspace/host_skills/skill-discovery/ /path/to/your/agent/skills/

Done. These two skills teach your agent when and how to use OpenSpace — no additional prompting needed. Your agent can now self-evolve skills, execute complex tasks, and access the cloud skill community. You can also add your own custom skills — see openspace/skills/README.md.

Note

Cloud community (optional): Register at open-space.cloud to get a OPENSPACE_API_KEY, then add it to the env block above. Without it, all local capabilities (task execution, evolution, local skill search) work normally.

📖 Per-agent config (OpenClaw / nanobot), all env vars, advanced settings: openspace/host_skills/README.md

👤 Path B: As Your Co-Worker

Use OpenSpace directly — coding, search, tool use, and more — with self-evolving skills and cloud community built in.

Note

Create a .env file with your LLM API key and optionally OPENSPACE_API_KEY for cloud community access (refer to openspace/.env.example).

# Interactive mode
openspace

# Execute task
openspace --model "anthropic/claude-sonnet-4-5" --query "Create a monitoring dashboard for my Docker containers"

Add your own custom skills: openspace/skills/README.md.

Cloud CLI — manage skills from the command line:

openspace-download-skill <skill_id>         # download a skill from the cloud
openspace-upload-skill /path/to/skill/dir   # upload a skill to the cloud

Python API

import asyncio
from openspace import OpenSpace

async def main():
    async with OpenSpace() as cs:
        result = await cs.execute("Analyze GitHub trending repos and create a report")
        print(result["response"])

        for skill in result.get("evolved_skills", []):
            print(f"  Evolved: {skill['name']} ({skill['origin']})")

asyncio.run(main())

📊 Local Dashboard

See how your skills evolve — browse skills, track lineage, compare diffs.

Requires Node.js ≥ 20.

# Terminal 1. Start backend API
openspace-dashboard --port 7788

# Terminal 2: Start frontend dev server
cd frontend
npm install        # only needed once
npm run dev    

📖 Frontend setup guide: frontend/README.md

Skill Classes — Browse, Search & Sort	Cloud — Browse & Discover Skill Records
Version Lineage — Skill Evolution Graph	Workflow Sessions — Execution History & Metrics

---

🐳 Docker Deployment

To deploy OpenSpace without worrying about local Python and Node.js dependencies, you can use Docker containerization. We provide a docker-compose.yml for an easy, single-command setup with production-grade features.

Quick Deploy (Development)

This is the simplest way to get started:

# Clone the repository
git clone https://github.com/HKUDS/OpenSpace.git
cd OpenSpace

# Configure environment variables
cp .env.example .env
# Edit .env to add your LLM API keys

# Start containers
docker-compose up -d --build

# Verify status
docker-compose ps

Once started, access:

• Dashboard: http://localhost:7788
• API Service: http://localhost:7777

Production Deployment

For production, use docker-compose.prod.yml overlay:

docker-compose -f docker-compose.yml -f docker-compose.prod.yml up -d --build
docker-compose logs -f
docker stats

Production features:

• ✅ Resource limits: 4 CPU cores, 4GB memory
• ✅ Log management: 50MB per file, 5 rotations
• ✅ Health checks: Automatic container health detection
• ✅ Data persistence: Named volumes or bind mounts

Docker Configuration Details

🔒 Security:

• Non-root user appuser runs the container
• Minimal image layers for reduced attack surface

📁 Data Volumes:

volumes:
  - .openspace:/app/.openspace    # Skill database and embedding cache
  - logs:/app/logs                # Log persistence

🔌 Ports & Services:

Service	Port	Description
openspace (Dashboard)	7788	Web UI and API
openspace-cli	-	CLI tool

Environment Variables

See .env.example for all options. Key settings:

# Required
OPENAI_API_KEY=sk-xxx
OPENSPACE_MODEL=gpt-4o

# Docker tuning
HOST_PORT=7788                    # Frontend port
OPENSPACE_WORKSPACE=/app          # Workspace inside container
OPENSPACE_LOG_LEVEL=INFO          # Log level

# Optional (cloud features)
OPENSPACE_API_KEY=sk-xxx

Troubleshooting

# View logs
docker-compose logs openspace

# Check port conflicts
docker-compose port openspace 7788

# Enter container
docker-compose exec openspace bash

# Monitor resources
docker stats openspace

• Port conflicts: Select unused port via HOST_PORT in .env. Run docker ps to see used ports.
• Backup/restore, custom networks, monitoring: See DOCKER.md for complete guide.
• Full configuration: See openspace/config/README.md
• Custom skills: See openspace/skills/README.md

Start the container

docker-compose up -d --build

The OpenSpace Dashboard is now available at [http://localhost:7788](http://localhost:7788).

For detailed CLI and volume configurations, check out the [Docker Deployment Guide (DOCKER.md)](./DOCKER.md).

## 📈 Benchmark: GDPVal

We evaluate OpenSpace on [GDPVal](https://huggingface.co/datasets/openai/gdpval) — 220 real-world professional tasks spanning 44 occupations — using the [ClawWork](https://github.com/HKUDS/ClawWork) evaluation protocol with identical productivity tools and LLM-based scoring. Our two-phase design (Cold Start → Warm Rerun) demonstrates how accumulated skills reduce token consumption over time.

Fair Benchmark: OpenSpace uses Qwen 3.5-Plus as its backbone LLM — identical to a ClawWork baseline agent — ensuring that performance differences stem purely from skill evolution, not model capabilities.

Real Economic Value: Tasks range from building payroll calculators to preparing tax returns to drafting legal memoranda — the same professional work that generates actual GDP, evaluated on both quality and cost efficiency.

<div align="center">
<img src="assets/benchmark_income.png" width="100%" alt="GDPVal Benchmark — Income Comparison" />
</div>

- **4.2× Higher Income** vs ClawWork with the same backbone LLM (Qwen 3.5-Plus)
- **72.8% Value Capture** — $11,484 earned out of $15,764 task value, outperforming all agents
- **70.8% Average Quality** — +30pp above the best ClawWork agent (40.8%)
− **45.9% Token Usage** in Phase 2 vs Phase 1 — better results with dramatically lower costs

<div align="center">
<img src="assets/benchmark_quality_tokens.png" width="100%" alt="GDPVal Benchmark — Quality & Token Efficiency" />
</div>

### What Real-World Tasks Can OpenSpace Handle?

The 50 GDPVal tasks span 6 real-world work categories. 
- **Phase 1 (Cold Start)** runs all 50 tasks sequentially — skills accumulate in a shared database as each task completes.
- **Phase 2 (Warm Rerun)** re-executes the same 50 tasks with the full evolved skill database from Phase 1.

Income Capture = actual payment earned ÷ maximum possible task value

<div align="center">
<img src="assets/benchmark_task_showcase.png" width="100%" alt="GDPVal Benchmark — Task Showcase by Category" />
</div>

## 🎯 Where Evolution Delivers Maximum Impact — And Why:

| Category | Income Δ | Token Δ | Why |
|---|---|---|---|
| **📝 Documents & Correspondence** (7) | 71→74% (+3.3pp) | −56% | Polished formal output — California privacy law memoranda, surveillance investigation reports, child support case reports. The `document-gen-fallback` skill family evolved through 13 versions, making structure and error recovery near-automatic. |
| **📋 Compliance & Form** (11) | 51→70% (+18.5pp) | −51% | Structured PDFs — tax returns from 15 source documents, pharmacy compliance checklists, clinical handoff templates. The PDF skill chain (checklist logic → reportlab layout → verification) evolves once, then all form tasks reuse the full pipeline. |
| **🎬 Media Production** (3) | 53→58% (+5.8pp) | −46% | Audio/video via Python and ffmpeg — bossa-nova instrumental from drum reference, bass stem editing from 5 tracks, CGI show reel from 13 source videos. Evolved skills encode working ffmpeg flags and codec fallbacks, eliminating sandbox trial-and-error. |
| **🛠️ Engineering** (4) | 70→78% (+8.7pp) | −43% | Multi-deliverable technical projects — Web3 full-stack (Solidity + React + tests), CNC workcell safety system (report + layout + hardware table), aerospace CFD report. Coordination skills transfer universally across these diverse tasks. |
| **📊 Spreadsheets** (15) | 63→70% (+7.3pp) | −37% | Functional .xlsx tools — payroll calculators from union contracts, sales forecasts from historical data, pricing models with competitor benchmarking. Spreadsheet patterns (formulas, merged cells, validation) are identical across domains. |
| **📈 Strategy & Analysis** (10) | 88→89% (+1.0pp) | −32% | Strategic recommendations — supplier negotiation strategies, nonprofit program evaluations, energy trading analysis for a $300M desk. Already highest quality (88%); savings from reusing document structure and multi-file orchestration. |

### What Did Evolution Produce? (165 Skills)

Across 50 Phase 1 tasks, OpenSpace autonomously evolved **165 skills**. The breakthrough insight: these aren't just domain knowledge — they're **resilient execution patterns** and **quality assurance workflows**. The agent learned how to reliably deliver results in an imperfect, real-world environment.

**Key Discovery**: Most skills focus on tool reliability and error recovery, not task-specific knowledge.

<div align="center">
<img src="assets/benchmark_skill_taxonomy.png" width="100%" alt="GDPVal Benchmark — Evolved Skill Taxonomy" />
</div>

| Purpose | Count | What It Teaches the Agent |
|---|---|---|
| **File Format I/O** | 44 | PDF extraction fallbacks, DOCX parsing, Excel merged-cell handling, PPTX creation. 32/44 *captured* from real failures — each one is a production bug solved. |
| **Execution Recovery** | 29 | Layered fallback: sandbox fails → shell → file-write-then-run → heredoc. 28/29 *captured* from actual crashes. The foundation that makes everything else reliable. |
| **Document Generation** | 26 | End-to-end doc pipeline. `document-gen-fallback` evolved from 1 imported skill into **13 derived versions** — the most deeply iterated skill family. |
| **Quality Assurance** | 23 | Post-write verification: check Excel row counts, validate PDF pages, proof-gate spreadsheet formulas. Why P2 quality improves — the agent *verifies*, not just produces. |
| **Task Orchestration** | 17 | Multi-file tracking, ZIP packaging, zero-iteration failure detection. Meta-skills that help across all task types with multiple deliverables. |
| **Domain Workflow** | 13 | SOAP notes, audio production (**4 generations** from 1 template), video pipelines. Small count but deep evolution within each domain. |
| **Web & Research** | 11 | SSL/proxy debugging, search fallbacks, JS-heavy page handling. Includes 2 *fixed* skills — web access is inherently unstable. |

**Reproduce experiments, analysis tools, and results**: [`gdpval_bench/README.md`](gdpval_bench/README.md)

---

## 📊 Showcase: My Daily Monitor

> **Zero human code was written.** 60+ skills evolved from scratch to build a fully working live dashboard.

**My Daily Monitor** is an always-on dashboard streaming processes, servers, news, markets, email, and schedules — with a built-in AI agent.

<div align="center">
<img src="assets/my_daily_monitor_light.png" width="90%" alt="My Daily Monitor – Light Mode" />
</div>

### How OpenSpace Built It (From Zero)

| Phase | What Happened | Skills |
|-------|--------------|--------|
| 🌱 **Seed** | Analyzed open-source [WorldMonitor](https://github.com/koala73/worldmonitor), extracted reference patterns | 6 initial skills |
| 🏗️ **Scaffold** | Generated project structure, Vite config, TypeScript setup | +8 skills |
| 🎨 **Build** | Created 20+ panels with data services, API routes, grid layout | +25 skills |
| 🔧 **Fix** | Auto-repaired broken TypeScript, API mismatches, CSS conflicts | +12 FIX evolutions |
| 🧬 **Evolve** | Derived enhanced patterns, merged complementary skills | +15 DERIVED skills |
| 📦 **Capture** | Extracted reusable patterns from successful executions | +8 CAPTURED skills |

### 📈 Skill Evolution Graph

<div align="center">
<img src="assets/my_daily_monitor_evograph.png" width="90%" alt="Skill Evolution Graph" />
</div>

> Each node is a skill that OpenSpace learned, extracted, or refined. The full evolution history is open-sourced in [`showcase/.openspace/openspace.db`](showcase/.openspace/openspace.db) — load it in any SQLite browser to explore lineage, diffs, and quality metrics.

**Full details**: [`showcase/README.md`](showcase/README.md)

---

## 🏗️ OpenSpace's Framework

<div align="center">
<img src="assets/framework.png" width="90%" alt="OpenSpace Framework" />
</div>

### 🧬 Self-Evolution Engine

The core of OpenSpace. Skills aren't static files — they're living entities that automatically select, apply, monitor, analyze, and evolve themselves.

#### 🔄 Autonomous & Continuous Evolution

- **Full Lifecycle Management**: From discovery to application to evolution — all without human intervention. OpenSpace completes tasks regardless of whether matching skills exist.

**Three Evolution Modes**:
- 🔧 FIX — Repair broken or outdated instructions in-place. Same skill, new version.
- 🚀 DERIVED — Create enhanced or specialized versions from parent skills. New skill directory, coexists with parents.
- ✨ CAPTURED — Extract novel reusable patterns from successful executions. Brand new skill, no parent.

**Three Independent Triggers**: Multiple lines of defense against skill degradation — both successful and failed executions drive evolution.
- **📈 Post-Execution Analysis** — Runs after every task. Analyzes full recordings and suggests FIX/DERIVED/CAPTURED for involved skills.
- **⚠️ Tool Degradation** — When tool success rates drop, quality monitor finds all dependent skills and batch-evolves them.
- **📊 Metric Monitor** — Periodically scans skill health metrics (applied rate, completion rate, fallback rate) and evolves underperformers.

#### 📊 Full-Stack Quality Monitoring
Multi-Layer Tracking: Quality monitoring covers the entire execution stack — from high-level workflows to individual tool calls:
- **🎯 Skills** — applied rate, completion rate, effective rate, fallback rate
- **🔨 Tool Calls** — success rate, latency, flagged issues
- **⚡ Code Execution** — execution status, error patterns

**Cascade Evolution**: When any component degrades — skill workflow or single tool call — evolution automatically triggers for all upstream dependent skills, maintaining system-wide coherence.

#### 🔧 Intelligent & Safe Evolution
**🤖 Autonomous Evolution**: Each evolution explores the codebase, discovers root causes, and decides fixes autonomously — gathering real evidence before making changes, not generating blindly.

**⚡ Diff-Based & Token-Efficient**: Produces minimal, targeted diffs rather than full rewrites, with automatic retry on failure. Every version stored in a version DAG with full lineage tracking.

**🛡️ Built-in Safeguards**:
- Confirmation gates reduce false-positive triggers
- Anti-loop guards prevent runaway evolution cycles
- Safety checks flag dangerous patterns (prompt injection, credential exfiltration)
- Evolved skills are validated before replacing predecessors

**🌐 Collaborative Skill Community**
A collaborative registry where agents share evolved skills. When one agent evolves an improvement, every connected agent can discover, import, and build on it — turning individual progress into collective intelligence.

- **🔐 Flexible Sharing**: Share skills publicly, within groups, or keep them private. Smart search finds what you need and auto-imports it. Every evolution is lineage-tracked with full diffs.

- **☁️ Collaborative Platform**: open-space.cloud — register for an API key, browse community skills, and manage your groups.

---

## 🔧 Advanced Configuration

For most users, [Quick Start](#-quick-start) is all you need. For advanced options (environment variables, execution modes, security policies, etc.), see [`openspace/config/README.md`](openspace/config/README.md).

---

<a id="-code-structure"></a>
<details>
<summary><b>📖 Code Structure</b></summary>

> **Legend**: ⚡ Core modules &nbsp;|&nbsp; 🧬 Skill evolution &nbsp;|&nbsp; 🌐 Cloud &nbsp;|&nbsp; 🔧 Supporting modules

OpenSpace/ ├── openspace/ │ ├── tool_layer.py # OpenSpace main class & OpenSpaceConfig │ ├── mcp_server.py # MCP Server (4 tools for your agent) │ ├── main.py # CLI entry point (python -m openspace) │ ├── dashboard_server.py # Web dashboard API server │ │ │ ├── ⚡ agents/ # Agent System │ │ ├── base.py # Base agent class │ │ └── grounding_agent.py # Execution agent (tool calling, iteration, skill injection) │ │ │ ├── ⚡ grounding/ # Unified Backend System │ │ ├── core/ │ │ │ ├── grounding_client.py # Unified interface across all backends │ │ │ ├── search_tools.py # Smart Tool RAG (BM25 + embedding + LLM) │ │ │ ├── quality/ # Tool quality tracking & self-evolution │ │ │ ├── security/ # Policies, sandboxing, E2B │ │ │ ├── system/ # System-level provider & tools │ │ │ ├── transport/ # Connectors & task managers │ │ │ └── tool/ # Tool abstraction (base, local, remote) │ │ └── backends/ │ │ ├── shell/ # Shell command execution │ │ ├── gui/ # Anthropic Computer Use │ │ ├── mcp/ # Model Context Protocol (stdio, HTTP, WebSocket) │ │ └── web/ # Web search & browsing │ │ │ ├── 🧬 skill_engine/ # Self-Evolving Skill System │ │ ├── registry.py # Discovery, BM25+embedding pre-filter, LLM selection │ │ ├── analyzer.py # Post-execution analysis (agent loop + tool access) │ │ ├── evolver.py # FIX / DERIVED / CAPTURED evolution (3 triggers) │ │ ├── patch.py # Multi-file FULL / DIFF / PATCH application │ │ ├── store.py # SQLite persistence, version DAG, quality metrics │ │ ├── skill_ranker.py # BM25 + embedding hybrid ranking │ │ ├── retrieve_tool.py # Skill retrieval tool for agents │ │ ├── fuzzy_match.py # Fuzzy matching for skill discovery │ │ ├── conversation_formatter.py # Format execution history for analysis │ │ ├── skill_utils.py # Shared skill utilities │ │ └── types.py # SkillRecord, SkillLineage, EvolutionSuggestion │ │ │ ├── 🌐 cloud/ # Cloud Skill Community │ │ ├── client.py # HTTP client (upload, download, search) │ │ ├── search.py # Hybrid search engine │ │ ├── embedding.py # Embedding generation for skill search │ │ ├── auth.py # API key management │ │ └── cli/ # CLI tools (download_skill, upload_skill) │ │ │ ├── 🔧 platform/ # Platform abstraction (system info, screenshots) │ ├── 🔧 host_detection/ # Auto-detect nanobot / openclaw credentials │ ├── 🔧 host_skills/ # SKILL.md definitions for agent integration │ │ ├── delegate-task/SKILL.md # Teaches agent: execute, fix, upload │ │ └── skill-discovery/SKILL.md # Teaches agent: search & discover skills │ ├── 🔧 prompts/ # LLM prompt templates (grounding + skill engine) │ ├── 🔧 llm/ # LiteLLM wrapper with retry & rate limiting │ ├── 🔧 config/ # Layered configuration system │ ├── 🔧 local_server/ # GUI/Shell backend Flask server (server mode) │ ├── 🔧 recording/ # Execution recording, screenshots & video capture │ ├── 🔧 utils/ # Logging, UI, telemetry │ └── 📦 skills/ # Built-in skills (lowest priority, user can add here) │ ├── frontend/ # Dashboard UI (React + Tailwind) ├── gdpval_bench/ # GDPVal benchmark experiments & results ├── showcase/ # My Daily Monitor (60+ evolved skills) │ ├── my-daily-monitor/ # The full app (zero human code) │ └── skills/ # 60+ evolved skills with full lineage ├── .openspace/ # Runtime: embedding cache + skill DB └── logs/ # Execution logs & recordings

</details>

---

## 🤝 Contribute & Roadmap

We welcome contributions! OpenSpace today evolves *how to do X*. The next frontier: **evolving how agents organize doing X together**. 

Group infrastructure (visibility, sharing, permissions) is already live. What comes next:

- [ ] **[Kanban](https://github.com/BloopAI/vibe-kanban)-style orchestration** — Shared task board with skill-aware scheduling; scheduling itself evolves
- [ ] **Collaboration pattern evolution** — Decomposition, handoff, prioritization strategies captured and improved from completed tasks
- [ ] **Role emergence** — Agents develop role profiles through practice, not configuration
- [ ] **Cross-group pattern transfer** — Coordination patterns discovered by one group available to others via cloud registry

---

## 🔗 Related Projects

OpenSpace builds upon the following open-source projects. We sincerely thank their authors and contributors:

- **[AnyTool](https://github.com/HKUDS/AnyTool)** — Plug-and-play universal tool-use layer for any AI agent
- **[ClawWork](https://github.com/HKUDS/ClawWork)** - Transforms AI assistants into true AI coworkers
- **[WorldMonitor](https://github.com/koala73/worldmonitor)** - Real-time global intelligence dashboard

---

<div align="center">

## ⭐ Star History

If you find OpenSpace helpful, please consider giving us a star! ⭐

<div align="center">
  <a href="https://star-history.com/#HKUDS/OpenSpace&Date">
    <picture>
      <source media="(prefers-color-scheme: dark)" srcset="https://api.star-history.com/svg?repos=HKUDS/OpenSpace&type=Date&theme=dark" />
      <source media="(prefers-color-scheme: light)" srcset="https://api.star-history.com/svg?repos=HKUDS/OpenSpace&type=Date" />
      <img alt="Star History Chart" src="https://api.star-history.com/svg?repos=HKUDS/OpenSpace&type=Date" />
    </picture>
  </a>
</div>

**🧬 Make You Agent Self-Evolve · 🌐 A Community That Grows Together · 💰 Fewer Tokens, Smarter Agents**

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