[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"project-74023":3},{"id":4,"name":5,"fullName":6,"owner":7,"repo":5,"description":8,"homepage":9,"htmlUrl":10,"language":11,"languages":10,"totalLinesOfCode":10,"stars":12,"forks":13,"watchers":14,"openIssues":15,"contributorsCount":16,"subscribersCount":16,"size":16,"stars1d":17,"stars7d":18,"stars30d":19,"stars90d":16,"forks30d":16,"starsTrendScore":20,"compositeScore":21,"rankGlobal":10,"rankLanguage":10,"license":22,"archived":23,"fork":23,"defaultBranch":24,"hasWiki":23,"hasPages":23,"topics":25,"createdAt":10,"pushedAt":10,"updatedAt":26,"readmeContent":27,"aiSummary":28,"trendingCount":16,"starSnapshotCount":16,"syncStatus":29,"lastSyncTime":30,"discoverSource":31},74023,"OpenSpace","HKUDS\u002FOpenSpace","HKUDS","\"OpenSpace: Make Your Agents: Smarter, Low-Cost, Self-Evolving\" -- Community: https:\u002F\u002Fopen-space.cloud\u002F","",null,"Python",6491,809,37,31,0,59,102,369,177,114.73,"MIT License",false,"main",[],"2026-06-12 04:01:12","\u003Cdiv align=\"center\">\n\n\u003Cpicture>\n    \u003Cimg src=\"assets\u002Flogo.png\" width=\"320px\" style=\"border: none; box-shadow: none;\" alt=\"OpenSpace Logo\">\n\u003C\u002Fpicture>\n\n## ✨ OpenSpace: Make Your Agents: Smarter, Low-Cost, Self-Evolving ✨\n\n| 🔋 **46% Fewer Tokens** | **💰 $11K earned in 6 Hours** | 🧬 **Self-Evolving Skills** | 🌐 **Agents Experience Sharing** |\n\n[![Agents](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FAgents-Claude_Code%20%7C%20Codex%20%7C%20OpenClaw%20%7C%20nanobot%20%7C%20...-99C9BF.svg)](https:\u002F\u002Fmodelcontextprotocol.io\u002F)\n[![Python](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FPython-3.12+-FCE7D6.svg)](https:\u002F\u002Fwww.python.org\u002F)\n[![License](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FLicense-MIT-C1E5F5.svg)](https:\u002F\u002Fopensource.org\u002Flicenses\u002FMIT\u002F)\n[![Feishu](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FFeishu-Group-E9DBFC?style=flat&logo=larksuite&logoColor=white)](.\u002FCOMMUNICATION.md)\n[![WeChat](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FWeChat-Group-C5EAB4?style=flat&logo=wechat&logoColor=white)](.\u002FCOMMUNICATION.md)\n[![中文文档](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F文档-中文版-F5C6C6?style=flat)](.\u002FREADME_CN.md)\n\n**One Command to Evolve All Your AI Agents**: OpenClaw, nanobot, Claude Code, Codex, Cursor and etc.\n\n\u003Cimg src=\"assets\u002Fcli-typing.gif\" width=\"500px\" alt=\"openspace --query your task\">\n\n\u003C\u002Fdiv>\n\n---\n\n## 📢 News\n\n- **2026-04-16** 📊 **Evolution candidate lifecycle tracking** — skill store now records when evolution suggestions are processed (`evolution_processed_at`), cleanly distinguishing pending candidates from already-handled ones.\n- **2026-04-12** 🍎 **macOS platform hardening** — decoupled `atomacos` from core macOS imports so screenshots, window control, and recording work independently without it.\n- **2026-04-10** 🎯 **CAPTURED skills** now persist to the host agent's own skill directory instead of the default registry path. Cloud skill uploads now support **private visibility** correctly.\n- **2026-04-09** 💬 Multi-channel **communication gateway**. OpenSpace can now receive and respond to messages from external platforms. Ships with **WhatsApp** (Baileys bridge + QR auth) and **Feishu** (HTTP webhook) adapters, session management, attachment caching, and allowlist-based access control. See [`openspace\u002Fconfig\u002FREADME.md`](openspace\u002Fconfig\u002FREADME.md) for setup.\n- **2026-04-07** 🌐 OpenSpace MCP now supports standalone **SSE** and **streamable HTTP** startup, making it easier for remote hosts to connect over HTTP instead of stdio and bypass stdio-bound MCP server timeout bottlenecks. See the [host integration guide](openspace\u002Fhost_skills\u002FREADME.md) for setup details.\n- **2026-04-06** 🛠️ Fixed multiple runtime issues across grounding, MCP serving, skill evolution, and persistence, improving execution stability and recovery in long-running workflows.\n- **2026-04-05** 🧭 Cleaned up LLM credential resolution: centralized `.env` loading, improved host config auto-detection, and made provider-native env handling more consistent.\n- **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.\n- **2026-04-02** ⚡ Cloud search upgraded for higher relevance and lower latency.\n- **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.\n- **2026-03-29** 🔒 Pinned litellm to \u003C1.82.7 to avoid PYSEC-2026-2 supply-chain attack.\n- **2026-03-28** 🔧 Idempotent skill registration — `register_skill_dir` now returns existing `SkillMeta` for already-registered skills. Updated OpenClaw setup docs.\n- **2026-03-27** 🪟 Fixed stdio deadlock on Windows; improved evolver confirmation parsing with stem-style keyword matching.\n- **2026-03-26** 🌱 Dynamic skill directory re-scanning on each call, lightweight local skill search, and streamlined documentation.\n- **2026-03-25** 🎉 OpenSpace is now open source!\n\n---\n\n## The Problem with Today's AI Agents\n\nToday's AI agents — [OpenClaw](https:\u002F\u002Fgithub.com\u002Fopenclaw\u002Fopenclaw), [nanobot](https:\u002F\u002Fgithub.com\u002FHKUDS\u002Fnanobot), [Claude Code](https:\u002F\u002Fdocs.anthropic.com\u002Fen\u002Fdocs\u002Fclaude-code), [Codex](https:\u002F\u002Fgithub.com\u002Fopenai\u002Fcodex), [Cursor](https:\u002F\u002Fcursor.com), 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.\n- **❌ Massive Token Waste** - How to reuse successful task patterns instead of reasoning from scratch and burning tokens every time?\n- **❌ Repeated Costly Failures** - How to share solutions across agents instead of repeating the same costly exploration and mistakes?\n- **❌ Poor and Unreliable Skills** - How to maintain skill reliability as tools and APIs evolve — while ensuring community-contributed skills meet rigorous quality standards?\n\n## 🎯 What is OpenSpace?\n\n**🚀 🚀 The self-evolving engine where every task makes every agent smarter and more cost-efficient.**\n\nhttps:\u002F\u002Fgithub.com\u002Fuser-attachments\u002Fassets\u002Fc50f70ab-f6db-47bf-9498-3210c0f0abae\n\nOpenSpace plugs into any agent as skills and evolves it with three superpowers:\n\n### 🧬 Self-Evolution\nSkills that learn and improve themselves automatically\n- ✅ **AUTO-FIX** — When a skill breaks, it fixes itself instantly\n- ✅ **AUTO-IMPROVE** — Successful patterns become better skill versions\n- ✅ **AUTO-LEARN** — Captures winning workflows from actual usage\n- ✅ **Quality monitoring** — Tracks skill performance, error rates, and execution success across all tasks.\n\n**Skills that continuously evolve — turning every failure into improvement, every success into optimization.**\n\n### 🌐 Collective Agent Intelligence\nTurn individual agents into a shared brain\n- ✅ **Shared evolution**: One agent's improvement becomes every agent's upgrade\n- ✅ **Network effects**: More agents → richer data → faster evolution for every agent\n- ✅ **Easy sharing** — Upload and download evolved skills with one simple command\n- ✅ **Access control** — Choose public, private, or team-only access for each skill\n\n**One agent learns, all agents benefit — collective intelligence at scale.**\n\n### 💰 Token Efficiency\nSmarter agents, dramatically lower costs\n- ✅ **Stop repeating work** → Reuse successful solutions instead of starting from zero each time\n- ✅ **Tasks get cheaper** → As skills improve, similar work costs less and less\n- ✅ **Small updates only** → Fix what's broken, don't rebuild everything\n- ✅ **Real savings**: 4.2× better performance with 46% fewer tokens on real-world tasks, delivering measurable economic value. ([GDPVal](#-benchmark-gdpval))\n\nDo more, spend less — agents that actually save you money over time.\n\n---\n\n### The Difference\n\n**❌ Current Agents**\n- Skills degrade silently as tools evolve\n- Failed patterns repeat with no learning mechanism\n- Knowledge remains trapped in individual agents\n\n**✅ OpenSpace-Powered Agents**\n- Multi-layer monitoring catches problems and auto-triggers repairs\n- Successful workflows become reusable, shareable skills\n- When one agent learns something useful, all agents get that knowledge instantly\n\n### 📊 OpenSpace: Turn Your Agent into a Money-Making Coworker\n\n**🎯 Real-World Results That Matter**\nOn 50 professional tasks (**📈 [GDPVal Economic Benchmark](#-benchmark-gdpval)**) across 6 industries, OpenSpace agents earn **4.2× more money** than baseline ([ClawWork](https:\u002F\u002Fgithub.com\u002FHKUDS\u002FClawWork)) agents using the same backbone LLM (Qwen 3.5-Plus). While cutting 46% of costly tokens through skill evolution.\n\n\u003Cdiv align=\"center\">\n\u003Cimg src=\"assets\u002Fbenchmark_kpi.png\" width=\"100%\" alt=\"GDPVal Benchmark — Key Results\" \u002F>\n\u003C\u002Fdiv>\n\n**💼 These Aren't Toy Problems**\n- Building payroll calculators from complex union contracts\n- Preparing tax returns from 15 scattered PDF documents\n- Drafting legal memoranda on California privacy regulations\n- Creating compliance forms and engineering specifications\n\n**📈 Consistent Wins Across All Fields**\n- Compliance work: +18.5% higher earnings\n- Engineering projects: +8.7% better performance\n- Professional documents: 56% fewer tokens needed\n- Every category improved — no exceptions\n\n\u003Cdiv align=\"center\">\n\u003Cimg src=\"assets\u002Fbenchmark_task_showcase.png\" width=\"100%\" alt=\"GDPVal Benchmark — Task Showcase by Category\" \u002F>\n\u003C\u002Fdiv>\n\n**OpenSpace doesn't just make agents smarter** — it makes them economically viable. Real work, real money, measurable results.\n\n## Use Case for Autonomous System Development with OpenSpace\n\n**🖥️ [My Daily Monitor](showcase\u002FREADME.md)** — 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.\n\n\u003Cdiv align=\"center\">\n\u003Cimg src=\"assets\u002Fmy_daily_monitor_dark.png\" width=\"100%\" alt=\"My Daily Monitor – Dark Mode\" \u002F>\n\u003C\u002Fdiv>\n\n---\n\n## 📋 Table of Contents\n\n- [⚡ Quick Start](#-quick-start)\n  - [🤖 Path A: For Your Agent](#-path-a-for-your-agent)\n  - [👤 Path B: As Your Co-Worker](#-path-b-as-your-co-worker)\n  - [📊 Local Dashboard](#-local-dashboard)\n- [📈 Benchmark: GDPVal](#-benchmark-gdpval)\n- [📊 Showcase: My Daily Monitor](#-showcase-my-daily-monitor)\n- [🏗️ Framework](#️-framework)\n  - [🧬 Self-Evolution Engine](#-self-evolution-engine)\n  - [🌐 Cloud Skill Community](#-cloud-skill-community)\n- [🔧 Advanced Configuration](#-advanced-configuration)\n- [📖 Code Structure](#-code-structure)\n- [🤝 Contribute & Roadmap](#-contribute--roadmap)\n- [🔗 Related Projects](#-related-projects)\n\n---\n\n## ⚡ Quick Start\n\n🌐 **Just want to explore?** Browse community skills, evolution lineage at **[open-space.cloud](https:\u002F\u002Fopen-space.cloud)** — no installation needed.\n\n```bash\ngit clone https:\u002F\u002Fgithub.com\u002FHKUDS\u002FOpenSpace.git && cd OpenSpace\npip install -e .\nopenspace-mcp --help   # verify installation\n```\n\n> [!TIP]\n> **Slow clone?** The `assets\u002F` folder (~50 MB of images) makes the default clone large. Use this lightweight alternative to skip it:\n> ```bash\n> git clone --filter=blob:none --sparse https:\u002F\u002Fgithub.com\u002FHKUDS\u002FOpenSpace.git\n> cd OpenSpace\n> git sparse-checkout set '\u002F*' '!assets\u002F'\n> pip install -e .\n> ```\n\n**Choose your path:**\n- **[Path A](#-path-a-for-your-agent)** — Plug OpenSpace into your agent\n- **[Path B](#-path-b-as-your-co-worker)** — Use OpenSpace directly as your AI co-worker\n\n### 🤖 Path A: For Your Agent\n\nWorks with any agent that supports skills (`SKILL.md`) — [Claude Code](https:\u002F\u002Fdocs.anthropic.com\u002Fen\u002Fdocs\u002Fclaude-code), [Codex](https:\u002F\u002Fgithub.com\u002Fopenai\u002Fcodex), [OpenClaw](https:\u002F\u002Fgithub.com\u002Fopenclaw\u002Fopenclaw), [nanobot](https:\u002F\u002Fgithub.com\u002FHKUDS\u002Fnanobot), etc.\n\n**① Add OpenSpace to your agent's MCP config:**\n\n```json\n{\n  \"mcpServers\": {\n    \"openspace\": {\n      \"command\": \"openspace-mcp\",\n      \"toolTimeout\": 600,\n      \"env\": {\n        \"OPENSPACE_HOST_SKILL_DIRS\": \"\u002Fpath\u002Fto\u002Fyour\u002Fagent\u002Fskills\",\n        \"OPENSPACE_WORKSPACE\": \"\u002Fpath\u002Fto\u002FOpenSpace\",\n        \"OPENSPACE_API_KEY\": \"sk-xxx (optional, for cloud)\"\n      }\n    }\n  }\n}\n```\n\n> [!TIP]\n> Credentials (API key, model) are **auto-detected** from your agent's config; you usually don't need to set them manually.\n\n> [!NOTE]\n> OpenSpace supports 3 launch modes:\n> - **stdio**: keep `command: \"openspace-mcp\"` in the host config.\n> - **SSE**: start `openspace-mcp --transport sse --host 127.0.0.1 --port 8080`.\n> - **streamable HTTP**: start `openspace-mcp --transport streamable-http --host 127.0.0.1 --port 8081`.\n>\n> Common remote endpoints:\n> - SSE endpoint: `http:\u002F\u002F127.0.0.1:8080\u002Fsse`\n> - streamable HTTP endpoint: `http:\u002F\u002F127.0.0.1:8081\u002Fmcp`\n>\n> `stdio` is the simplest option. HTTP modes keep OpenSpace as a standalone server, but **host-specific registration syntax** and **host-side timeouts** still apply.\n\n**② Copy skills** into your agent's skills directory:\n\n```bash\ncp -r OpenSpace\u002Fopenspace\u002Fhost_skills\u002Fdelegate-task\u002F \u002Fpath\u002Fto\u002Fyour\u002Fagent\u002Fskills\u002F\ncp -r OpenSpace\u002Fopenspace\u002Fhost_skills\u002Fskill-discovery\u002F \u002Fpath\u002Fto\u002Fyour\u002Fagent\u002Fskills\u002F\n```\n\nDone. 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\u002Fskills\u002FREADME.md`](openspace\u002Fskills\u002FREADME.md).\n\n> [!NOTE]\n> **Cloud community (optional):** Register at **[open-space.cloud](https:\u002F\u002Fopen-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.\n\n📖 Per-agent config (OpenClaw \u002F nanobot), all env vars, advanced settings: [`openspace\u002Fhost_skills\u002FREADME.md`](openspace\u002Fhost_skills\u002FREADME.md)\n\n### 👤 Path B: As Your Co-Worker\n\nUse OpenSpace directly — coding, search, tool use, and more — with self-evolving skills and cloud community built in.\n\n> [!NOTE]\n> Create a `.env` file with your LLM API key and optionally `OPENSPACE_API_KEY` for cloud community access (refer to [`openspace\u002F.env.example`](openspace\u002F.env.example)).\n\n```bash\n# Interactive mode\nopenspace\n\n# Execute task\nopenspace --model \"anthropic\u002Fclaude-sonnet-4-5\" --query \"Create a monitoring dashboard for my Docker containers\"\n```\n\nAdd your own custom skills: [`openspace\u002Fskills\u002FREADME.md`](openspace\u002Fskills\u002FREADME.md).\n\n**Cloud CLI** — manage skills from the command line:\n\n```bash\nopenspace-download-skill \u003Cskill_id>         # download a skill from the cloud\nopenspace-upload-skill \u002Fpath\u002Fto\u002Fskill\u002Fdir   # upload a skill to the cloud\n```\n\n\u003Cdetails>\n\u003Csummary>\u003Cb>Python API\u003C\u002Fb>\u003C\u002Fsummary>\n\n```python\nimport asyncio\nfrom openspace import OpenSpace\n\nasync def main():\n    async with OpenSpace() as cs:\n        result = await cs.execute(\"Analyze GitHub trending repos and create a report\")\n        print(result[\"response\"])\n\n        for skill in result.get(\"evolved_skills\", []):\n            print(f\"  Evolved: {skill['name']} ({skill['origin']})\")\n\nasyncio.run(main())\n```\n\n\u003C\u002Fdetails>\n\n### 📊 Local Dashboard\n\nSee how your skills evolve — browse skills, track lineage, compare diffs.\n\n> Requires **Node.js ≥ 20**.\n\n```bash\n# Terminal 1. Start backend API\nopenspace-dashboard --port 7788\n\n# Terminal 2: Start frontend dev server\ncd frontend\nnpm install        # only needed once\nnpm run dev    \n```\n\n📖 **Frontend setup guide**: [`frontend\u002FREADME.md`](frontend\u002FREADME.md)\n\n\u003Cdiv align=\"center\">\n\u003Ctable>\n\u003Ctr>\n\u003Ctd width=\"50%\">\u003Cimg src=\"assets\u002Ffrontend_1.gif\" width=\"100%\" alt=\"Skill Classes\" \u002F>\u003C\u002Ftd>\n\u003Ctd width=\"50%\">\u003Cimg src=\"assets\u002Ffrontend_2.gif\" width=\"100%\" alt=\"Cloud Skill Records\" \u002F>\u003C\u002Ftd>\n\u003C\u002Ftr>\n\u003Ctr>\n\u003Ctd align=\"center\">\u003Csub>Skill Classes — Browse, Search & Sort\u003C\u002Fsub>\u003C\u002Ftd>\n\u003Ctd align=\"center\">\u003Csub>Cloud — Browse & Discover Skill Records\u003C\u002Fsub>\u003C\u002Ftd>\n\u003C\u002Ftr>\n\u003Ctr>\n\u003Ctd width=\"50%\">\u003Cimg src=\"assets\u002Ffrontend_3.gif\" width=\"100%\" alt=\"Version Lineage\" \u002F>\u003C\u002Ftd>\n\u003Ctd width=\"50%\">\u003Cimg src=\"assets\u002Ffrontend_4.gif\" width=\"100%\" alt=\"Workflow Sessions\" \u002F>\u003C\u002Ftd>\n\u003C\u002Ftr>\n\u003Ctr>\n\u003Ctd align=\"center\">\u003Csub>Version Lineage — Skill Evolution Graph\u003C\u002Fsub>\u003C\u002Ftd>\n\u003Ctd align=\"center\">\u003Csub>Workflow Sessions — Execution History & Metrics\u003C\u002Fsub>\u003C\u002Ftd>\n\u003C\u002Ftr>\n\u003C\u002Ftable>\n\u003C\u002Fdiv>\n\n---\n\n## 📈 Benchmark: GDPVal\n\nWe evaluate OpenSpace on [GDPVal](https:\u002F\u002Fhuggingface.co\u002Fdatasets\u002Fopenai\u002Fgdpval) — 220 real-world professional tasks spanning 44 occupations — using the [ClawWork](https:\u002F\u002Fgithub.com\u002FHKUDS\u002FClawWork) 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.\n\nFair 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.\n\nReal 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.\n\n\u003Cdiv align=\"center\">\n\u003Cimg src=\"assets\u002Fbenchmark_income.png\" width=\"100%\" alt=\"GDPVal Benchmark — Income Comparison\" \u002F>\n\u003C\u002Fdiv>\n\n- **4.2× Higher Income** vs ClawWork with the same backbone LLM (Qwen 3.5-Plus)\n- **72.8% Value Capture** — $11,484 earned out of $15,764 task value, outperforming all agents\n- **70.8% Average Quality** — +30pp above the best ClawWork agent (40.8%)\n− **45.9% Token Usage** in Phase 2 vs Phase 1 — better results with dramatically lower costs\n\n\u003Cdiv align=\"center\">\n\u003Cimg src=\"assets\u002Fbenchmark_quality_tokens.png\" width=\"100%\" alt=\"GDPVal Benchmark — Quality & Token Efficiency\" \u002F>\n\u003C\u002Fdiv>\n\n### What Real-World Tasks Can OpenSpace Handle?\n\nThe 50 GDPVal tasks span 6 real-world work categories. \n- **Phase 1 (Cold Start)** runs all 50 tasks sequentially — skills accumulate in a shared database as each task completes.\n- **Phase 2 (Warm Rerun)** re-executes the same 50 tasks with the full evolved skill database from Phase 1.\n\nIncome Capture = actual payment earned ÷ maximum possible task value\n\n\u003Cdiv align=\"center\">\n\u003Cimg src=\"assets\u002Fbenchmark_task_showcase.png\" width=\"100%\" alt=\"GDPVal Benchmark — Task Showcase by Category\" \u002F>\n\u003C\u002Fdiv>\n\n## 🎯 Where Evolution Delivers Maximum Impact — And Why:\n\n| Category | Income Δ | Token Δ | Why |\n|---|---|---|---|\n| **📝 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. |\n| **📋 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. |\n| **🎬 Media Production** (3) | 53→58% (+5.8pp) | −46% | Audio\u002Fvideo 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. |\n| **🛠️ 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. |\n| **📊 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. |\n| **📈 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. |\n\n### What Did Evolution Produce? (165 Skills)\n\nAcross 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.\n\n**Key Discovery**: Most skills focus on tool reliability and error recovery, not task-specific knowledge.\n\n\u003Cdiv align=\"center\">\n\u003Cimg src=\"assets\u002Fbenchmark_skill_taxonomy.png\" width=\"100%\" alt=\"GDPVal Benchmark — Evolved Skill Taxonomy\" \u002F>\n\u003C\u002Fdiv>\n\n| Purpose | Count | What It Teaches the Agent |\n|---|---|---|\n| **File Format I\u002FO** | 44 | PDF extraction fallbacks, DOCX parsing, Excel merged-cell handling, PPTX creation. 32\u002F44 *captured* from real failures — each one is a production bug solved. |\n| **Execution Recovery** | 29 | Layered fallback: sandbox fails → shell → file-write-then-run → heredoc. 28\u002F29 *captured* from actual crashes. The foundation that makes everything else reliable. |\n| **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. |\n| **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. |\n| **Task Orchestration** | 17 | Multi-file tracking, ZIP packaging, zero-iteration failure detection. Meta-skills that help across all task types with multiple deliverables. |\n| **Domain Workflow** | 13 | SOAP notes, audio production (**4 generations** from 1 template), video pipelines. Small count but deep evolution within each domain. |\n| **Web & Research** | 11 | SSL\u002Fproxy debugging, search fallbacks, JS-heavy page handling. Includes 2 *fixed* skills — web access is inherently unstable. |\n\n**Reproduce experiments, analysis tools, and results**: [`gdpval_bench\u002FREADME.md`](gdpval_bench\u002FREADME.md)\n\n---\n\n## 📊 Showcase: My Daily Monitor\n\n> **Zero human code was written.** 60+ skills evolved from scratch to build a fully working live dashboard.\n\n**My Daily Monitor** is an always-on dashboard streaming processes, servers, news, markets, email, and schedules — with a built-in AI agent.\n\n\u003Cdiv align=\"center\">\n\u003Cimg src=\"assets\u002Fmy_daily_monitor_light.png\" width=\"90%\" alt=\"My Daily Monitor – Light Mode\" \u002F>\n\u003C\u002Fdiv>\n\n### How OpenSpace Built It (From Zero)\n\n| Phase | What Happened | Skills |\n|-------|--------------|--------|\n| 🌱 **Seed** | Analyzed open-source [WorldMonitor](https:\u002F\u002Fgithub.com\u002Fkoala73\u002Fworldmonitor), extracted reference patterns | 6 initial skills |\n| 🏗️ **Scaffold** | Generated project structure, Vite config, TypeScript setup | +8 skills |\n| 🎨 **Build** | Created 20+ panels with data services, API routes, grid layout | +25 skills |\n| 🔧 **Fix** | Auto-repaired broken TypeScript, API mismatches, CSS conflicts | +12 FIX evolutions |\n| 🧬 **Evolve** | Derived enhanced patterns, merged complementary skills | +15 DERIVED skills |\n| 📦 **Capture** | Extracted reusable patterns from successful executions | +8 CAPTURED skills |\n\n### 📈 Skill Evolution Graph\n\n\u003Cdiv align=\"center\">\n\u003Cimg src=\"assets\u002Fmy_daily_monitor_evograph.png\" width=\"90%\" alt=\"Skill Evolution Graph\" \u002F>\n\u003C\u002Fdiv>\n\n> Each node is a skill that OpenSpace learned, extracted, or refined. The full evolution history is open-sourced in [`showcase\u002F.openspace\u002Fopenspace.db`](showcase\u002F.openspace\u002Fopenspace.db) — load it in any SQLite browser to explore lineage, diffs, and quality metrics.\n\n**Full details**: [`showcase\u002FREADME.md`](showcase\u002FREADME.md)\n\n---\n\n## 🏗️ OpenSpace's Framework\n\n\u003Cdiv align=\"center\">\n\u003Cimg src=\"assets\u002Fframework.png\" width=\"90%\" alt=\"OpenSpace Framework\" \u002F>\n\u003C\u002Fdiv>\n\n### 🧬 Self-Evolution Engine\n\nThe core of OpenSpace. Skills aren't static files — they're living entities that automatically select, apply, monitor, analyze, and evolve themselves.\n\n#### 🔄 Autonomous & Continuous Evolution\n\n- **Full Lifecycle Management**: From discovery to application to evolution — all without human intervention. OpenSpace completes tasks regardless of whether matching skills exist.\n\n**Three Evolution Modes**:\n- 🔧 FIX — Repair broken or outdated instructions in-place. Same skill, new version.\n- 🚀 DERIVED — Create enhanced or specialized versions from parent skills. New skill directory, coexists with parents.\n- ✨ CAPTURED — Extract novel reusable patterns from successful executions. Brand new skill, no parent.\n\n**Three Independent Triggers**: Multiple lines of defense against skill degradation — both successful and failed executions drive evolution.\n- **📈 Post-Execution Analysis** — Runs after every task. Analyzes full recordings and suggests FIX\u002FDERIVED\u002FCAPTURED for involved skills.\n- **⚠️ Tool Degradation** — When tool success rates drop, quality monitor finds all dependent skills and batch-evolves them.\n- **📊 Metric Monitor** — Periodically scans skill health metrics (applied rate, completion rate, fallback rate) and evolves underperformers.\n\n#### 📊 Full-Stack Quality Monitoring\nMulti-Layer Tracking: Quality monitoring covers the entire execution stack — from high-level workflows to individual tool calls:\n- **🎯 Skills** — applied rate, completion rate, effective rate, fallback rate\n- **🔨 Tool Calls** — success rate, latency, flagged issues\n- **⚡ Code Execution** — execution status, error patterns\n\n**Cascade Evolution**: When any component degrades — skill workflow or single tool call — evolution automatically triggers for all upstream dependent skills, maintaining system-wide coherence.\n\n#### 🔧 Intelligent & Safe Evolution\n**🤖 Autonomous Evolution**: Each evolution explores the codebase, discovers root causes, and decides fixes autonomously — gathering real evidence before making changes, not generating blindly.\n\n**⚡ 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.\n\n**🛡️ Built-in Safeguards**:\n- Confirmation gates reduce false-positive triggers\n- Anti-loop guards prevent runaway evolution cycles\n- Safety checks flag dangerous patterns (prompt injection, credential exfiltration)\n- Evolved skills are validated before replacing predecessors\n\n**🌐 Collaborative Skill Community**\nA 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.\n\n- **🔐 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.\n\n- **☁️ Collaborative Platform**: open-space.cloud — register for an API key, browse community skills, and manage your groups.\n\n---\n\n## 🔧 Advanced Configuration\n\nFor most users, [Quick Start](#-quick-start) is all you need. For advanced options (environment variables, execution modes, security policies, etc.), see [`openspace\u002Fconfig\u002FREADME.md`](openspace\u002Fconfig\u002FREADME.md).\n\n---\n\n\u003Ca id=\"-code-structure\">\u003C\u002Fa>\n\u003Cdetails>\n\u003Csummary>\u003Cb>📖 Code Structure\u003C\u002Fb>\u003C\u002Fsummary>\n\n> **Legend**: ⚡ Core modules  |  🧬 Skill evolution  |  🌐 Cloud  |  🔧 Supporting modules\n\n```\nOpenSpace\u002F\n├── openspace\u002F\n│   ├── tool_layer.py                     # OpenSpace main class & OpenSpaceConfig\n│   ├── mcp_server.py                     # MCP Server (4 tools for your agent)\n│   ├── __main__.py                       # CLI entry point (python -m openspace)\n│   ├── dashboard_server.py               # Web dashboard API server\n│   │\n│   ├── ⚡ agents\u002F                         # Agent System\n│   │   ├── base.py                       # Base agent class\n│   │   └── grounding_agent.py            # Execution agent (tool calling, iteration, skill injection)\n│   │\n│   ├── ⚡ grounding\u002F                      # Unified Backend System\n│   │   ├── core\u002F\n│   │   │   ├── grounding_client.py       # Unified interface across all backends\n│   │   │   ├── search_tools.py           # Smart Tool RAG (BM25 + embedding + LLM)\n│   │   │   ├── quality\u002F                  # Tool quality tracking & self-evolution\n│   │   │   ├── security\u002F                 # Policies, sandboxing, E2B\n│   │   │   ├── system\u002F                   # System-level provider & tools\n│   │   │   ├── transport\u002F                # Connectors & task managers\n│   │   │   └── tool\u002F                     # Tool abstraction (base, local, remote)\n│   │   └── backends\u002F\n│   │       ├── shell\u002F                    # Shell command execution\n│   │       ├── gui\u002F                      # Anthropic Computer Use\n│   │       ├── mcp\u002F                      # Model Context Protocol (stdio, HTTP, WebSocket)\n│   │       └── web\u002F                      # Web search & browsing\n│   │\n│   ├── 🧬 skill_engine\u002F                  # Self-Evolving Skill System\n│   │   ├── registry.py                   # Discovery, BM25+embedding pre-filter, LLM selection\n│   │   ├── analyzer.py                   # Post-execution analysis (agent loop + tool access)\n│   │   ├── evolver.py                    # FIX \u002F DERIVED \u002F CAPTURED evolution (3 triggers)\n│   │   ├── patch.py                      # Multi-file FULL \u002F DIFF \u002F PATCH application\n│   │   ├── store.py                      # SQLite persistence, version DAG, quality metrics\n│   │   ├── skill_ranker.py               # BM25 + embedding hybrid ranking\n│   │   ├── retrieve_tool.py              # Skill retrieval tool for agents\n│   │   ├── fuzzy_match.py                # Fuzzy matching for skill discovery\n│   │   ├── conversation_formatter.py     # Format execution history for analysis\n│   │   ├── skill_utils.py                # Shared skill utilities\n│   │   └── types.py                      # SkillRecord, SkillLineage, EvolutionSuggestion\n│   │\n│   ├── 🌐 cloud\u002F                         # Cloud Skill Community\n│   │   ├── client.py                     # HTTP client (upload, download, search)\n│   │   ├── search.py                     # Hybrid search engine\n│   │   ├── embedding.py                  # Embedding generation for skill search\n│   │   ├── auth.py                       # API key management\n│   │   └── cli\u002F                          # CLI tools (download_skill, upload_skill)\n│   │\n│   ├── 💬 communication\u002F                  # Multi-Channel Communication Gateway\n│   │   ├── gateway.py                    # Message routing, session management, reply dispatch\n│   │   ├── adapters\u002F                     # Platform adapters (WhatsApp, Feishu)\n│   │   ├── bridges\u002F                      # Non-Python runtimes (WhatsApp Baileys bridge)\n│   │   ├── config.py                     # Communication config loader\n│   │   ├── session_store.py              # Per-channel session persistence\n│   │   └── types.py                      # ChannelMessage, ChannelSource, SendResult\n│   │\n│   ├── 🔧 platform\u002F                      # Platform abstraction (system info, screenshots)\n│   ├── 🔧 host_detection\u002F                # Auto-detect nanobot \u002F openclaw credentials\n│   ├── 🔧 host_skills\u002F                   # SKILL.md definitions for agent integration\n│   │   ├── delegate-task\u002FSKILL.md        # Teaches agent: execute, fix, upload\n│   │   └── skill-discovery\u002FSKILL.md      # Teaches agent: search & discover skills\n│   ├── 🔧 prompts\u002F                       # LLM prompt templates (grounding + skill engine)\n│   ├── 🔧 llm\u002F                           # LiteLLM wrapper with retry & rate limiting\n│   ├── 🔧 config\u002F                        # Layered configuration system\n│   ├── 🔧 local_server\u002F                  # GUI\u002FShell backend Flask server (server mode)\n│   ├── 🔧 recording\u002F                     # Execution recording, screenshots & video capture\n│   ├── 🔧 utils\u002F                         # Logging, UI, telemetry\n│   └── 📦 skills\u002F                        # Built-in skills (lowest priority, user can add here)\n│\n├── frontend\u002F                             # Dashboard UI (React + Tailwind)\n├── gdpval_bench\u002F                         # GDPVal benchmark experiments & results\n├── showcase\u002F                             # My Daily Monitor (60+ evolved skills)\n│   ├── my-daily-monitor\u002F                 # The full app (zero human code)\n│   └── skills\u002F                           # 60+ evolved skills with full lineage\n├── .openspace\u002F                           # Runtime: embedding cache + skill DB\n└── logs\u002F                                 # Execution logs & recordings\n```\n\n\u003C\u002Fdetails>\n\n---\n\n## 🤝 Contribute & Roadmap\n\nWe welcome contributions! OpenSpace today evolves *how to do X*. The next frontier: **evolving how agents organize doing X together**. \n\nGroup infrastructure (visibility, sharing, permissions) is already live. What comes next:\n\n- [ ] **[Kanban](https:\u002F\u002Fgithub.com\u002FBloopAI\u002Fvibe-kanban)-style orchestration** — Shared task board with skill-aware scheduling; scheduling itself evolves\n- [ ] **Collaboration pattern evolution** — Decomposition, handoff, prioritization strategies captured and improved from completed tasks\n- [ ] **Role emergence** — Agents develop role profiles through practice, not configuration\n- [ ] **Cross-group pattern transfer** — Coordination patterns discovered by one group available to others via cloud registry\n\n---\n\n## 🔗 Related Projects\n\nOpenSpace builds upon the following open-source projects. We sincerely thank their authors and contributors:\n\n- **[AnyTool](https:\u002F\u002Fgithub.com\u002FHKUDS\u002FAnyTool)** — Plug-and-play universal tool-use layer for any AI agent\n- **[ClawWork](https:\u002F\u002Fgithub.com\u002FHKUDS\u002FClawWork)** - Transforms AI assistants into true AI coworkers\n- **[WorldMonitor](https:\u002F\u002Fgithub.com\u002Fkoala73\u002Fworldmonitor)** - Real-time global intelligence dashboard\n\n---\n\n\u003Cdiv align=\"center\">\n\n## ⭐ Star History\n\nIf you find OpenSpace helpful, please consider giving us a star! ⭐\n\n\u003Cdiv align=\"center\">\n  \u003Ca href=\"https:\u002F\u002Fstar-history.com\u002F#HKUDS\u002FOpenSpace&Date\">\n    \u003Cpicture>\n      \u003Csource media=\"(prefers-color-scheme: dark)\" srcset=\"https:\u002F\u002Fapi.star-history.com\u002Fsvg?repos=HKUDS\u002FOpenSpace&type=Date&theme=dark\" \u002F>\n      \u003Csource media=\"(prefers-color-scheme: light)\" srcset=\"https:\u002F\u002Fapi.star-history.com\u002Fsvg?repos=HKUDS\u002FOpenSpace&type=Date\" \u002F>\n      \u003Cimg alt=\"Star History Chart\" src=\"https:\u002F\u002Fapi.star-history.com\u002Fsvg?repos=HKUDS\u002FOpenSpace&type=Date\" \u002F>\n    \u003C\u002Fpicture>\n  \u003C\u002Fa>\n\u003C\u002Fdiv>\n\n**🧬 Make You Agent Self-Evolve · 🌐 A Community That Grows Together · 💰 Fewer Tokens, Smarter Agents**\n\n\u003C\u002Fdiv>\n\n---\n\n\u003Cp align=\"center\">\n  \u003Cem> ❤️ Thanks for visiting ✨ OpenSpace!\u003C\u002Fem>\u003Cbr>\u003Cbr>\n  \u003Cimg src=\"https:\u002F\u002Fvisitor-badge.laobi.icu\u002Fbadge?page_id=HKUDS.OpenSpace&style=for-the-badge&color=00d4ff\"\n  alt=\"Views\">\n\u003C\u002Fp>\n","OpenSpace 是一个旨在让AI代理变得更智能、成本更低且能够自我进化的开源项目。它通过减少46%的令牌使用量和实现技能自我进化，帮助用户节省成本并提升效率。项目支持多种主流AI代理如Claude Code、Codex等，并提供一站式的命令行工具来管理和优化这些代理的行为。此外，OpenSpace还具备多渠道通信网关功能，允许与外部平台如WhatsApp和Feishu进行交互。适用于需要构建高效、低成本且能够持续自我优化的人工智能解决方案的场景，特别适合开发者或团队希望增强其AI应用性能的情况。",2,"2026-06-11 03:48:27","high_star"]