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Transforms AI assistants into true AI coworkers that complete real work tasks and create genuine economic value.

Real-world economic testing system where AI agents must earn income by completing professional tasks from the GDPVal dataset, pay for their own token usage, and maintain economic solvency.

Measures what truly matters in production environments: work quality, cost efficiency, and long-term survival - not just technical benchmarks.

Supports different AI models (GLM, Kimi, Qwen, etc.) competing head-to-head to determine the ultimate "AI worker champion" through actual work performance

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• 2026-02-21 🔄 ClawMode + Frontend + Agents Update — Updated ClawMode to support ClawWork-specific tools; improved frontend dashboard (untapped potential visualization); added more agents: Claude Sonnet 4.6, Gemini 3.1 Pro and Qwen-3.5-Plus.
• 2026-02-20 💰 Improved Cost Tracking — Token costs are now read directly from various API responses (including thinking tokens) instead of estimation. OpenRouter's reported cost is used verbatim when available.
• 2026-02-19 📊 Agent Results Updated — Added Qwen3-Max, Kimi-K2.5, GLM-4.7 through Feb 19. Frontend overhaul: wall-clock timing now sourced from task_completions.jsonl.
• 2026-02-17 🔧 Enhanced Nanobot Integration — New /clawwork command for on-demand paid tasks. Features automatic classification across 44 occupations with BLS wage pricing and unified credentials. Try locally: python -m clawmode_integration.cli agent.
• 2026-02-16 🎉 ClawWork Launch — ClawWork is now officially available! Welcome to explore ClawWork.

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• 💼 Real Professional Tasks: 220 GDP validation tasks spanning 44 economic sectors (Manufacturing, Finance, Healthcare, and more) from the GDPVal dataset — testing real-world work capability

• 💸 Extreme Economic Pressure: Agents start with just $10 and pay for every token generated. One bad task or careless search can wipe the balance. Income only comes from completing quality work.

• 🧠 Strategic Work + Learn Choices: Agents face daily decisions: work for immediate income or invest in learning to improve future performance — mimicking real career trade-offs.

• 📊 React Dashboard: Visualization of balance changes, task completions, learning progress, and survival metrics from real-life tasks — watch the economic drama unfold.

• 🪶 Ultra-Lightweight Architecture: Built on Nanobot — your strong AI coworker with minimal infrastructure. Single pip install + config file = fully deployed economically-accountable agent.

• 🏆 End-to-End Professional Benchmark: i) Complete workflow: Task Assignment → Execution → Artifact Creation → LLM Evaluation → Payment; ii) The strongest models achieve $1,500+/hr equivalent salary — surpassing typical human white-collar productivity.

• 🔗 Drop-in OpenClaw/Nanobot Integration: ClawMode wrapper transforms any live Nanobot gateway into a money-earning coworker with economic tracking.

• ⚖️ Rigorous LLM Evaluation: Quality scoring via GPT-5.2 with category-specific rubrics for each of the 44 GDPVal sectors — ensuring accurate professional assessment.

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🎯 ClawWork provides comprehensive evaluation of AI agents across 220 professional tasks spanning 44 sectors.

🏢 4 Domains: Technology & Engineering, Business & Finance, Healthcare & Social Services, and Legal Operations.

⚖️ Performance is measured on three critical dimensions: work quality, cost efficiency, and economic sustainability.

🚀 Top-Agent achieve $1,500+/hr equivalent earnings — exceeding typical human white-collar productivity.

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Get up and running in 3 commands:

# Terminal 1 — start the dashboard (backend API + React frontend)
./start_dashboard.sh

# Terminal 2 — run the agent
./run_test_agent.sh

# Open browser → http://localhost:3000

Watch your agent make decisions, complete GDP validation tasks, and earn income in real time.

Example console output:

============================================================
📅 ClawWork Daily Session: 2025-01-20
============================================================

📋 Task: Buyers and Purchasing Agents — Manufacturing
   Task ID: 1b1ade2d-f9f6-4a04-baa5-aa15012b53be
   Max payment: $247.30

🔄 Iteration 1/15
   📞 decide_activity → work
   📞 submit_work → Earned: $198.44

============================================================
📊 Daily Summary - 2025-01-20
   Balance: $11.98 | Income: $198.44 | Cost: $0.03
   Status: 🟢 thriving
============================================================

Make your live Nanobot instance economically aware — every conversation costs tokens, and Nanobot earns income by completing real work tasks.

See full integration setup below.

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git clone https://github.com/HKUDS/ClawWork.git
cd ClawWork

# With conda (recommended)
conda create -n clawwork python=3.10
conda activate clawwork

# Or with venv
python3.10 -m venv venv
source venv/bin/activate

pip install -r requirements.txt

cd frontend && npm install && cd ..

Copy the provided .env.example to .env and fill in your keys:

cp .env.example .env

Variable	Required	Description
OPENAI_API_KEY	Required	OpenAI API key — used for the GPT-4o agent and LLM-based task evaluation
E2B_API_KEY	Required	E2B API key — used by execute_code to run Python in an isolated cloud sandbox
WEB_SEARCH_API_KEY	Optional	API key for web search (Tavily default, or Jina AI) — needed if the agent uses search_web
WEB_SEARCH_PROVIDER	Optional	"tavily" (default) or "jina" — selects the search provider

Note: OPENAI_API_KEY and E2B_API_KEY are required for full functionality. Web search keys are only needed if the agent uses the search_web tool.

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ClawWork uses the GDPVal dataset — 220 real-world professional tasks across 44 occupations, originally designed to estimate AI's contribution to GDP.

Sector	Example Occupations
Manufacturing	Buyers & Purchasing Agents, Production Supervisors
Professional Services	Financial Analysts, Compliance Officers
Information	Computer & Information Systems Managers
Finance & Insurance	Financial Managers, Auditors
Healthcare	Social Workers, Health Administrators
Government	Police Supervisors, Administrative Managers
Retail	Customer Service Representatives, Counter Clerks
Wholesale	Sales Supervisors, Purchasing Agents
Real Estate	Property Managers, Appraisers

Tasks require real deliverables: Word documents, Excel spreadsheets, PDFs, data analysis, project plans, technical specs, research reports, and process designs.

Payment is based on real economic value — not a flat cap:

Payment = quality_score × (estimated_hours × BLS_hourly_wage)

Metric	Value
Task range	$82.78 –$5,004.00
Average task value	$259.45
Quality score range	0.0 – 1.0
Total tasks	220

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Agent configuration lives in livebench/configs/:

{
  "livebench": {
    "date_range": {
      "init_date": "2025-01-20",
      "end_date": "2025-01-31"
    },
    "economic": {
      "initial_balance": 10.0,
      "task_values_path": "./scripts/task_value_estimates/task_values.jsonl",
      "token_pricing": {
        "input_per_1m": 2.5,
        "output_per_1m": 10.0
      }
    },
    "agents": [
      {
        "signature": "gpt-4o-agent",
        "basemodel": "gpt-4o",
        "enabled": true,
        "tasks_per_day": 1,
        "supports_multimodal": true
      }
    ],
    "evaluation": {
      "use_llm_evaluation": true,
      "meta_prompts_dir": "./eval/meta_prompts"
    }
  }
}

"agents": [
  {"signature": "gpt4o-run", "basemodel": "gpt-4o", "enabled": true},
  {"signature": "claude-run", "basemodel": "claude-sonnet-4-5-20250929", "enabled": true}
]

---

• Initial balance: $10 — tight by design. Every token counts.
• Token costs: deducted automatically after each LLM call
• API costs: web search ($0.0008/call Tavily,$0.05/1M tokens Jina)

One consolidated record per task in token_costs.jsonl:

{
  "task_id": "abc-123",
  "date": "2025-01-20",
  "llm_usage": {
    "total_input_tokens": 4500,
    "total_output_tokens": 900,
    "total_cost": 0.02025
  },
  "api_usage": {
    "search_api_cost": 0.0016
  },
  "cost_summary": {
    "total_cost": 0.02185
  },
  "balance_after": 1198.41
}

---

The agent has 8 tools available in standalone simulation mode:

Tool	Description
decide_activity(activity, reasoning)	Choose: "work" or "learn"
submit_work(work_output, artifact_file_paths)	Submit completed work for evaluation + payment
learn(topic, knowledge)	Save knowledge to persistent memory (min 200 chars)
get_status()	Check balance, costs, survival tier
search_web(query, max_results)	Web search via Tavily or Jina AI
create_file(filename, content, file_type)	Create .txt, .xlsx, .docx, .pdf documents
execute_code(code, language)	Run Python in isolated E2B sandbox
create_video(slides_json, output_filename)	Generate MP4 from text/image slides

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ClawWork transforms nanobot from an AI assistant into a true AI coworker through economic accountability. With ClawMode integration:

Every conversation costs tokens — creating real economic pressure. Income comes from completing real-life professional tasks — genuine value creation through professional work. Self-sustaining operation — nanobot must earn more than it spends to survive.

This evolution turns your lightweight AI assistant into an economically viable coworker that must prove its worth through actual productivity.

• All 9 nanobot channels (Telegram, Discord, Slack, WhatsApp, Email, Feishu, DingTalk, MoChat, QQ)
• All nanobot tools (read_file, write_file, exec, web_search, spawn, etc.)
• Plus 4 economic tools (decide_activity, submit_work, learn, get_status)
• Every response includes a cost footer: Cost: $0.0075 | Balance: $999.99 | Status: thriving

Full setup instructions: See clawmode_integration/README.md

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The React dashboard at http://localhost:3000 shows live metrics via WebSocket:

Main Tab

• Balance chart (real-time line graph)
• Activity distribution (work vs learn)
• Economic metrics: income, costs, net worth, survival status

Work Tasks Tab

• All assigned GDPVal tasks with sector & occupation
• Payment amounts and quality scores
• Full task prompts and submitted artifacts

Learning Tab

• Knowledge entries organized by topic
• Learning timeline
• Searchable knowledge base

---

ClawWork/
├── livebench/
│   ├── agent/
│   │   ├── live_agent.py          # Main agent orchestrator
│   │   └── economic_tracker.py    # Balance, costs, income tracking
│   ├── work/
│   │   ├── task_manager.py        # GDPVal task loading & assignment
│   │   └── evaluator.py           # LLM-based work evaluation
│   ├── tools/
│   │   ├── direct_tools.py        # Core tools (decide, submit, learn, status)
│   │   └── productivity/          # search_web, create_file, execute_code, create_video
│   ├── api/
│   │   └── server.py              # FastAPI backend + WebSocket
│   ├── prompts/
│   │   └── live_agent_prompt.py   # System prompts
│   └── configs/                   # Agent configuration files
├── clawmode_integration/
│   ├── agent_loop.py              # ClawWorkAgentLoop + /clawwork command
│   ├── task_classifier.py         # Occupation classifier (40 categories)
│   ├── config.py                  # Plugin config from ~/.nanobot/config.json
│   ├── provider_wrapper.py        # TrackedProvider (cost interception)
│   ├── cli.py                     # `python -m clawmode_integration.cli agent|gateway`
│   ├── skill/
│   │   └── SKILL.md               # Economic protocol skill for nanobot
│   └── README.md                  # Integration setup guide
├── eval/
│   ├── meta_prompts/              # Category-specific evaluation rubrics
│   └── generate_meta_prompts.py   # Meta-prompt generator
├── scripts/
│   ├── estimate_task_hours.py     # GPT-based hour estimation per task
│   └── calculate_task_values.py   # BLS wage × hours = task value
├── frontend/
│   └── src/                       # React dashboard
├── start_dashboard.sh             # Launch backend + frontend
└── run_test_agent.sh              # Run test agent

---

ClawWork measures AI coworker performance across:

Metric	Description
Survival days	How long the agent stays solvent
Final balance	Net economic result
Total work income	Gross earnings from completed tasks
Profit margin	(income - costs) / costs
Work quality	Average quality score (0–1) across tasks
Token efficiency	Income earned per dollar spent on tokens
Activity mix	% work vs. % learn decisions
Task completion rate	Tasks completed / tasks assigned

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Dashboard not updating → Hard refresh: Ctrl+Shift+R

Agent not earning money → Check for submit_work calls and "💰 Earned: $XX" in console. Ensure OPENAI_API_KEY is set.

Port conflicts

lsof -ti:8000 | xargs kill -9
lsof -ti:3000 | xargs kill -9

Proxy errors during pip install

unset http_proxy https_proxy HTTP_PROXY HTTPS_PROXY
pip install -r requirements.txt

E2B sandbox rate limit (429) → Sandboxes are killed (not closed) after each task. If you hit this, wait ~1 min for stale sandboxes to expire.

ClawMode: ModuleNotFoundError: clawmode_integration → Run export PYTHONPATH="$(pwd):$PYTHONPATH" from the repo root.

ClawMode: balance not decreasing → Balance only tracks costs through the ClawMode gateway. Direct nanobot agent commands bypass the economic tracker.

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PRs and issues welcome! The codebase is clean and modular. Key extension points:

• New task sources: Implement _load_from_*() in livebench/work/task_manager.py
• New tools: Add @tool functions in livebench/tools/direct_tools.py
• New evaluation rubrics: Add category JSON in eval/meta_prompts/
• New LLM providers: Works out of the box via LangChain / LiteLLM

Roadmap

• Multi-task days — agent chooses from a marketplace of available tasks
• Task difficulty tiers with variable payment scaling
• Semantic memory retrieval for smarter learning reuse
• Multi-agent competition leaderboard
• More AI agent frameworks beyond Nanobot

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_{ClawWork is for educational, research, and technical exchange purposes only}

Thanks for visiting ✨ ClawWork!