Vibe-Trading — plugin by HKUDS

Vibe-Trading is an AI-powered trading agent that transforms natural language requests into actionable trading strategies and insights.

<p align="center"> <b>English</b> | <a href="README_zh.md">中文</a> | <a href="README_ja.md">日本語</a> | <a href="README_ko.md">한국어</a> | <a href="README_ar.md">العربية</a> </p> <p align="center"> <img src="assets/icon.png" width="120" alt="Vibe-Trading Logo"/> </p> <h1 align="center">Vibe-Trading: Your Personal Trading Agent</h1> <p align="center"> <b>One Command to Empower Your Agent with Comprehensive Trading Capabilities</b> </p> <p align="center"> <img src="https://img.shields.io/badge/Python-3.11%2B-3776AB?style=flat&logo=python&logoColor=white" alt="Python"> <img src="https://img.shields.io/badge/Backend-FastAPI-009688?style=flat" alt="FastAPI"> <img src="https://img.shields.io/badge/Frontend-React%2019-61DAFB?style=flat&logo=react&logoColor=white" alt="React"> <a href="https://pypi.org/project/vibe-trading-ai/"><img src="https://img.shields.io/pypi/v/vibe-trading-ai?style=flat&logo=pypi&logoColor=white" alt="PyPI"></a> <a href="LICENSE"><img src="https://img.shields.io/badge/License-MIT-yellow?style=flat" alt="License"></a> <br> <img src="https://img.shields.io/badge/Skills-71-orange" alt="Skills"> <img src="https://img.shields.io/badge/Swarm_Presets-29-7C3AED" alt="Swarm"> <img src="https://img.shields.io/badge/Tools-27-0F766E" alt="Tools"> <img src="https://img.shields.io/badge/Data_Sources-5-2563EB" alt="Data Sources"> <br> <a href="https://github.com/HKUDS/.github/blob/main/profile/README.md"><img src="https://img.shields.io/badge/Feishu-Group-E9DBFC?style=flat-square&logo=feishu&logoColor=white" alt="Feishu"></a> <a href="https://github.com/HKUDS/.github/blob/main/profile/README.md"><img src="https://img.shields.io/badge/WeChat-Group-C5EAB4?style=flat-square&logo=wechat&logoColor=white" alt="WeChat"></a> <a href="https://discord.gg/2vDYc2w5"><img src="https://img.shields.io/badge/Discord-Join-7289DA?style=flat-square&logo=discord&logoColor=white" alt="Discord"></a> </p> <p align="center"> <a href="#-key-features">Features</a>  ·  <a href="#-demo">Demo</a>  ·  <a href="#-what-is-vibe-trading">What Is It</a>  ·  <a href="#-get-started">Get Started</a>  ·  <a href="#-cli-reference">CLI</a>  ·  <a href="#-api-server">API</a>  ·  <a href="#-mcp-plugin">MCP</a>  ·  <a href="#-project-structure">Structure</a>  ·  <a href="#-roadmap">Roadmap</a>  ·  <a href="#-contributing">Contributing</a>  ·  <a href="#contributors">Contributors</a> </p> <p align="center"> <a href="#-get-started"><img src="assets/pip-install.svg" height="45" alt="pip install vibe-trading-ai"></a> </p>

📰 News

2026-04-19 📦 v0.1.5: Published to PyPI & ClawHub. python-multipart CVE floor bump, 5 new MCP tools wired (analyze_trade_journal + 4 shadow-account tools), pattern_recognition → pattern registry fix, Docker dep parity, SKILL manifest synced (22 MCP tools / 71 skills).
2026-04-18 👥 Shadow Account: Extract your strategy rules from a broker journal → backtest the shadow across markets → 8-section HTML/PDF report showing exactly how much you leave on the table (rule violations, early exits, missed signals, counterfactual trades). 4 new tools, 1 skill, 32 tools total. Trade Journal + Shadow Account samples now live in the web UI welcome screen.
2026-04-17 📊 Trade Journal Analyzer + Universal File Reader: Upload broker exports (同花顺/东财/富途/generic CSV) → auto trading profile (holding days, win rate, PnL ratio, drawdown) + 4 bias diagnostics (disposition effect, overtrading, chasing momentum, anchoring). read_document now dispatches PDF, Word, Excel, PowerPoint, images (OCR), and 40+ text formats behind one unified call.

<details> <summary>Earlier news</summary>

2026-04-16 🧠 Agent Harness: Persistent cross-session memory, FTS5 session search, self-evolving skills (full CRUD), 5-layer context compression, read/write tool batching. 27 tools, 107 new tests.
2026-04-15 🤖 Z.ai + MiniMax: Z.ai provider (#35), MiniMax temperature fix + model update (#33). 13 providers.
2026-04-14 🔧 MCP Stability: Fixed backtest tool Connection closed error on stdio transport (#32).
2026-04-13 🌐 Cross-Market Composite Backtest: New CompositeEngine backtests mixed-market portfolios (e.g. A-shares + crypto) with shared capital pool and per-market rules. Also fixed swarm template variable fallback and frontend timeout.
2026-04-12 🌍 Multi-Platform Export: /pine exports strategies to TradingView (Pine Script v6), TDX (通达信/同花顺/东方财富), and MetaTrader 5 (MQL5) in one command.
2026-04-11 🛡️ Reliability & DX: vibe-trading init .env bootstrap (#19), preflight checks, runtime data-source fallback, hardened backtest engine. Multi-language README (#21).
2026-04-10 📦 v0.1.4: Docker fix (#8), web_search MCP tool, 12 LLM providers, akshare/ccxt deps. Published to PyPI and ClawHub.
2026-04-09 📊 Backtest Wave 2: ChinaFutures, GlobalFutures, Forex, Options v2 engines. Monte Carlo, Bootstrap CI, Walk-Forward validation.
2026-04-08 🔧 Multi-market backtest with per-market rules, Pine Script v6 export, 5 data sources with auto-fallback.

</details>

💡 What Is Vibe-Trading?

Vibe-Trading is an AI-powered multi-agent finance workspace that turns natural language requests into executable trading strategies, research insights, and portfolio analysis across global markets.

Key Capabilities:

• Natural Language → Strategy — Describe an idea; the agent writes, tests, and exports trading code<br> • 5 Data Sources, Zero Config — A-shares, HK/US, crypto, futures & forex with automatic fallback<br> • 29 Expert Teams — Pre-built multi-agent swarm workflows for investment, trading & risk<br> • Cross-Session Memory — Remembers preferences and insights; creates & evolves reusable skills<br> • 7 Backtest Engines — Cross-market composite testing with statistical validation & 4 optimizers<br> • Multi-Platform Export — One-click to TradingView, TDX (通达信/同花顺), and MetaTrader 5

✨ Key Features

<table width="100%"> <tr> <td align="center" width="25%" valign="top"> <img src="assets/scene-research.png" height="150" alt="Research"/><br> <h3>🔍 DeepResearch for Trading</h3> <img src="https://img.shields.io/badge/71_Skills-FF6B6B?style=for-the-badge&logo=bookstack&logoColor=white" alt="Skills" /><br><br> <div align="left" style="font-size: 4px;"> • 71 specialist skills with persistent cross-session memory<br> • Self-evolving: agent creates & refines workflows from experience<br> • 5-layer context compression — no info lost in long sessions<br> • Natural-language task routing across all finance domains </div> </td> <td align="center" width="25%" valign="top"> <img src="assets/scene-swarm.png" height="150" alt="Swarm"/><br> <h3>🐝 Swarm Intelligence</h3> <img src="https://img.shields.io/badge/29_Trading_Teams-4ECDC4?style=for-the-badge&logo=hive&logoColor=white" alt="Swarm" /><br><br> <div align="left"> • 29 out-of-the-box trading team presets<br> • DAG-based multi-agent orchestration<br> • Real-time streaming dashboard with live agent status<br> • FTS5 session search across all past conversations </div> </td> <td align="center" width="25%" valign="top"> <img src="assets/scene-backtest.png" height="150" alt="Backtest"/><br> <h3>📊 Cross-Market Backtest</h3> <img src="https://img.shields.io/badge/5_Data_Sources-FFD93D?style=for-the-badge&logo=bitcoin&logoColor=black" alt="Backtest" /><br><br> <div align="left"> • A-shares, HK/US equities, crypto, futures & forex<br> • 7 market engines + composite cross-market engine with shared capital pool<br> • Statistical validation: Monte Carlo, Bootstrap CI, Walk-Forward<br> • 15+ performance metrics & 4 optimizers </div> </td> <td align="center" width="25%" valign="top"> <img src="assets/scene-quant.png" height="150" alt="Quant"/><br> <h3>🧮 Quant Analysis Toolkit</h3> <img src="https://img.shields.io/badge/Quant_Tools-C77DFF?style=for-the-badge&logo=wolfram&logoColor=white" alt="Quant" /><br><br> <div align="left"> • Factor IC/IR analysis & quantile backtesting<br> • Black-Scholes pricing & full Greeks calculation<br> • Technical pattern recognition & detection<br> • Portfolio optimization via MVO/Risk Parity/BL </div> </td> </tr> </table>

71 Skills across 7 Categories

📊 71 specialized finance skills organized into 7 categories
🌐 Complete coverage from traditional markets to crypto & DeFi
🔬 Comprehensive capabilities spanning data sourcing to quantitative research

Category	Skills	Examples
Data Source	6	`data-routing`, `tushare`, `yfinance`, `okx-market`, `akshare`, `ccxt`
Strategy	17	`strategy-generate`, `cross-market-strategy`, `technical-basic`, `candlestick`, `ichimoku`, `elliott-wave`, `smc`, `multi-factor`, `ml-strategy`
Analysis	15	`factor-research`, `macro-analysis`, `global-macro`, `valuation-model`, `earnings-forecast`, `credit-analysis`
Asset Class	9	`options-strategy`, `options-advanced`, `convertible-bond`, `etf-analysis`, `asset-allocation`, `sector-rotation`
Crypto	7	`perp-funding-basis`, `liquidation-heatmap`, `stablecoin-flow`, `defi-yield`, `onchain-analysis`
Flow	7	`hk-connect-flow`, `us-etf-flow`, `edgar-sec-filings`, `financial-statement`, `adr-hshare`
Tool	8	`backtest-diagnose`, `report-generate`, `pine-script`, `doc-reader`, `web-reader`

29 Agent Swarm Team Presets

🏢 29 ready-to-use agent teams
⚡ Pre-configured finance workflows
🎯 Investment, trading & risk management presets

Preset	Workflow
`investment_committee`	Bull/bear debate → risk review → PM final call
`global_equities_desk`	A-share + HK/US + crypto researcher → global strategist
`crypto_trading_desk`	Funding/basis + liquidation + flow → risk manager
`earnings_research_desk`	Fundamental + revision + options → earnings strategist
`macro_rates_fx_desk`	Rates + FX + commodity → macro PM
`quant_strategy_desk`	Screening + factor research → backtest → risk audit
`technical_analysis_panel`	Classic TA + Ichimoku + harmonic + Elliott + SMC → consensus
`risk_committee`	Drawdown + tail risk + regime review → sign-off
`global_allocation_committee`	A-shares + crypto + HK/US → cross-market allocation

<sub>Plus 20+ additional specialist presets — run vibe-trading --swarm-presets to explore all.

</sub>

🎬 Demo

https://github.com/user-attachments/assets/4e4dcb80-7358-4b9a-92f0-1e29612e6e86

</td> <td width="50%">

https://github.com/user-attachments/assets/3754a414-c3ee-464f-b1e8-78e1a74fbd30

</td> </tr> <tr> <td colspan="2" align="center"><sub>☝️ Natural-language backtest & multi-agent swarm debate — Web UI + CLI</sub></td> </tr> </table> </div>

🚀 Quick Started

One-line install (PyPI)

pip install vibe-trading-ai

Package name vs commands: The PyPI package is vibe-trading-ai. Once installed, you get three commands:

Command Purpose
vibe-trading Interactive CLI / TUI
vibe-trading serve Launch FastAPI web server
vibe-trading-mcp Start MCP server (for Claude Desktop, OpenClaw, Cursor, etc.)

Command	Purpose
`vibe-trading`	Interactive CLI / TUI
`vibe-trading serve`	Launch FastAPI web server
`vibe-trading-mcp`	Start MCP server (for Claude Desktop, OpenClaw, Cursor, etc.)

vibe-trading init              # interactive .env setup
vibe-trading                   # launch CLI
vibe-trading serve --port 8899 # launch web UI
vibe-trading-mcp               # start MCP server (stdio)

Or choose a path

Path	Best for	Time
A. Docker	Try it now, zero local setup	2 min
B. Local install	Development, full CLI access	5 min
C. MCP plugin	Plug into your existing agent	3 min
D. ClawHub	One command, no cloning	1 min

Prerequisites

An LLM API key from any supported provider — or run locally with Ollama (no key needed)
Python 3.11+ for Path B
Docker for Path A

Supported LLM providers: OpenRouter, OpenAI, DeepSeek, Gemini, Groq, DashScope/Qwen, Zhipu, Moonshot/Kimi, MiniMax, Xiaomi MIMO, Z.ai, Ollama (local). See .env.example for config.

Tip: All markets work without any API keys thanks to automatic fallback. yfinance (HK/US), OKX (crypto), and AKShare (A-shares, US, HK, futures, forex) are all free. Tushare token is optional — AKShare covers A-shares as a free fallback.

Path A: Docker (zero setup)

git clone https://github.com/HKUDS/Vibe-Trading.git
cd Vibe-Trading
cp agent/.env.example agent/.env
# Edit agent/.env — uncomment your LLM provider and set API key
docker compose up --build

Open http://localhost:8899. Backend + frontend in one container.

Path B: Local install

git clone https://github.com/HKUDS/Vibe-Trading.git
cd Vibe-Trading
python -m venv .venv

# Activate
source .venv/bin/activate          # Linux / macOS
# .venv\Scripts\Activate.ps1       # Windows PowerShell

pip install -e .
cp agent/.env.example agent/.env   # Edit — set your LLM provider API key
vibe-trading                       # Launch interactive TUI

<details> <summary><b>Start web UI (optional)</b></summary>

# Terminal 1: API server
vibe-trading serve --port 8899

# Terminal 2: Frontend dev server
cd frontend && npm install && npm run dev

Open http://localhost:5899. The frontend proxies API calls to localhost:8899.

Production mode (single server):

cd frontend && npm run build && cd ..
vibe-trading serve --port 8899     # FastAPI serves dist/ as static files

</details>

Path C: MCP plugin

See MCP Plugin section below.

Path D: ClawHub (one command)

npx clawhub@latest install vibe-trading --force

The skill + MCP config is downloaded into your agent's skills directory. See ClawHub install for details.

🧠 Environment Variables

Copy agent/.env.example to agent/.env and uncomment the provider block you want. Each provider needs 3-4 variables:

Variable	Required	Description
`LANGCHAIN_PROVIDER`	Yes	Provider name (`openrouter`, `deepseek`, `groq`, `ollama`, etc.)
`<PROVIDER>_API_KEY`	Yes*	API key (`OPENROUTER_API_KEY`, `DEEPSEEK_API_KEY`, etc.)
`<PROVIDER>_BASE_URL`	Yes	API endpoint URL
`LANGCHAIN_MODEL_NAME`	Yes	Model name (e.g. `deepseek/deepseek-v3.2`)
`TUSHARE_TOKEN`	No	Tushare Pro token for A-share data (falls back to AKShare)
`TIMEOUT_SECONDS`	No	LLM call timeout, default 120s

<sub>* Ollama does not require an API key.</sub>

Free data (no key needed): A-shares via AKShare, HK/US equities via yfinance, crypto via OKX, 100+ crypto exchanges via CCXT. The system automatically selects the best available source for each market.

🎯 Recommended Models

Vibe-Trading is a tool-heavy agent — skills, backtests, memory, and swarms all flow through tool calls. Model choice directly decides whether the agent uses its tools or fabricates answers from training data.

Tier	Examples	When to use
Best	`anthropic/claude-opus-4.7`, `anthropic/claude-sonnet-4.6`, `openai/gpt-5.4`, `google/gemini-3.1-pro-preview`	Complex swarms (3+ agents), long research sessions, paper-grade analysis
Sweet spot (default)	`deepseek/deepseek-v3.2`, `x-ai/grok-4.20`, `z-ai/glm-5.1`, `moonshotai/kimi-k2.5`, `qwen/qwen3-max-thinking`	Daily driver — reliable tool-calling at ~1/10 the cost
Avoid for agent use	`-nano`, `-flash-lite`, `*-coder-next`, small / distilled variants	Tool-calling is unreliable — the agent will appear to "answer from memory" instead of loading skills or running backtests

The default agent/.env.example ships with deepseek/deepseek-v3.2 — the cheapest option in the sweet-spot tier.

🖥 CLI Reference

vibe-trading               # interactive TUI
vibe-trading run -p "..."  # single run
vibe-trading serve         # API server

<details> <summary><b>Slash commands inside TUI</b></summary>

Command	Description
`/help`	Show all commands
`/skills`	List all 71 finance skills
`/swarm`	List 29 swarm team presets
`/swarm run <preset> [vars_json]`	Run a swarm team with live streaming
`/swarm list`	Swarm run history
`/swarm show <run_id>`	Swarm run details
`/swarm cancel <run_id>`	Cancel a running swarm
`/list`	Recent runs
`/show <run_id>`	Run details + metrics
`/code <run_id>`	Generated strategy code
`/pine <run_id>`	Export indicators (TradingView + TDX + MT5)
`/trace <run_id>`	Full execution replay
`/continue <run_id> <prompt>`	Continue a run with new instructions
`/sessions`	List chat sessions
`/settings`	Show runtime config
`/clear`	Clear screen
`/quit`	Exit

</details> <details> <summary><b>Single run & flags</b></summary>

vibe-trading run -p "Backtest BTC-USDT MACD strategy, last 30 days"
vibe-trading run -p "Analyze AAPL momentum" --json
vibe-trading run -f strategy.txt
echo "Backtest 000001.SZ RSI" | vibe-trading run

vibe-trading -p "your prompt"
vibe-trading --skills
vibe-trading --swarm-presets
vibe-trading --swarm-run investment_committee '{"topic":"BTC outlook"}'
vibe-trading --list
vibe-trading --show <run_id>
vibe-trading --code <run_id>
vibe-trading --pine <run_id>           # Export indicators (TradingView + TDX + MT5)
vibe-trading --trace <run_id>
vibe-trading --continue <run_id> "refine the strategy"
vibe-trading --upload report.pdf

</details>

💡 Examples

Strategy & Backtesting

# Moving average crossover on US equities
vibe-trading run -p "Backtest a 20/50-day moving average crossover on AAPL for the past year, show Sharpe ratio and max drawdown"

# RSI mean-reversion on crypto
vibe-trading run -p "Test RSI(14) mean-reversion on BTC-USDT: buy below 30, sell above 70, last 6 months"

# Multi-factor strategy on A-shares
vibe-trading run -p "Backtest a momentum + value + quality multi-factor strategy on CSI 300 constituents over 2 years"

# After backtesting, export to TradingView / TDX / MetaTrader 5
vibe-trading --pine <run_id>

Market Research

# Equity deep-dive
vibe-trading run -p "Research NVDA: earnings trend, analyst consensus, option flow, and key risks for next quarter"

# Macro analysis
vibe-trading run -p "Analyze the current Fed rate path, USD strength, and impact on EM equities and gold"

# Crypto on-chain
vibe-trading run -p "Deep dive BTC on-chain: whale flows, exchange balances, miner activity, and funding rates"

Swarm Workflows

# Bull/bear debate on a stock
vibe-trading --swarm-run investment_committee '{"topic": "Is TSLA a buy at current levels?"}'

# Quant strategy from screening to backtest
vibe-trading --swarm-run quant_strategy_desk '{"universe": "S&P 500", "horizon": "3 months"}'

# Crypto desk: funding + liquidation + flow → risk manager
vibe-trading --swarm-run crypto_trading_desk '{"asset": "ETH-USDT", "timeframe": "1w"}'

# Global macro portfolio allocation
vibe-trading --swarm-run macro_rates_fx_desk '{"focus": "Fed pivot impact on EM bonds"}'

Cross-Session Memory

# Save your preferences once
vibe-trading run -p "Remember: I prefer RSI-based strategies, max 10% drawdown, hold period 5–20 days"

# The agent recalls them in future sessions automatically
vibe-trading run -p "Build a crypto strategy that fits my risk profile"

Upload & Analyze Documents

# Analyze a broker export or earnings report
vibe-trading --upload trades_export.csv
vibe-trading run -p "Profile my trading behavior and identify any biases"

vibe-trading --upload NVDA_Q1_earnings.pdf
vibe-trading run -p "Summarize the key risks and beats/misses from this earnings report"

🌐 API Server

vibe-trading serve --port 8899

Method	Endpoint	Description
`GET`	`/runs`	List runs
`GET`	`/runs/{run_id}`	Run details
`GET`	`/runs/{run_id}/pine`	Multi-platform indicator export
`POST`	`/sessions`	Create session
`POST`	`/sessions/{id}/messages`	Send message
`GET`	`/sessions/{id}/events`	SSE event stream
`POST`	`/upload`	Upload PDF/file
`GET`	`/swarm/presets`	List swarm presets
`POST`	`/swarm/runs`	Start swarm run
`GET`	`/swarm/runs/{id}/events`	Swarm SSE stream

Interactive docs: http://localhost:8899/docs

🔌 MCP Plugin

Vibe-Trading exposes 17 MCP tools for any MCP-compatible client. Runs as a stdio subprocess — no server setup needed. 16 of 17 tools work with zero API keys (HK/US/crypto). Only run_swarm needs an LLM key.

<details> <summary><b>Claude Desktop</b></summary>

Add to claude_desktop_config.json:

{
  "mcpServers": {
    "vibe-trading": {
      "command": "vibe-trading-mcp"
    }
  }
}

</details> <details> <summary><b>OpenClaw</b></summary>

Add to ~/.openclaw/config.yaml:

skills:
  - name: vibe-trading
    command: vibe-trading-mcp

</details> <details> <summary><b>Cursor / Windsurf / other MCP clients</b></summary>

vibe-trading-mcp                  # stdio (default)
vibe-trading-mcp --transport sse  # SSE for web clients

</details>

MCP tools exposed (17): list_skills, load_skill, backtest, factor_analysis, analyze_options, pattern_recognition, get_market_data, web_search, read_url, read_document, read_file, write_file, list_swarm_presets, run_swarm, get_swarm_status, get_run_result, list_runs.

<details> <summary><b>Install from ClawHub (one command)</b></summary>

npx clawhub@latest install vibe-trading --force

--force is required because the skill references external APIs, which triggers VirusTotal's automated scan. The code is fully open-source and safe to inspect.

This downloads the skill + MCP config into your agent's skills directory. No cloning needed.

Browse on ClawHub: clawhub.ai/skills/vibe-trading

</details> <details> <summary><b>OpenSpace — self-evolving skills</b></summary>

All 71 finance skills are published on open-space.cloud and evolve autonomously through OpenSpace's self-evolution engine.

To use with OpenSpace, add both MCP servers to your agent config:

{
  "mcpServers": {
    "openspace": {
      "command": "openspace-mcp",
      "toolTimeout": 600,
      "env": {
        "OPENSPACE_HOST_SKILL_DIRS": "/path/to/vibe-trading/agent/src/skills",
        "OPENSPACE_WORKSPACE": "/path/to/OpenSpace"
      }
    },
    "vibe-trading": {
      "command": "vibe-trading-mcp"
    }
  }
}

OpenSpace will auto-discover all 71 skills, enabling auto-fix, auto-improve, and community sharing. Search for Vibe-Trading skills via search_skills("finance backtest") in any OpenSpace-connected agent.

</details>

📁 Project Structure

<details> <summary><b>Click to expand</b></summary>

Vibe-Trading/
├── agent/                          # Backend (Python)
│   ├── cli.py                      # CLI entrypoint — interactive TUI + subcommands
│   ├── api_server.py               # FastAPI server — runs, sessions, upload, swarm, SSE
│   ├── mcp_server.py               # MCP server — 17 tools for OpenClaw / Claude Desktop
│   │
│   ├── src/
│   │   ├── agent/                  # ReAct agent core
│   │   │   ├── loop.py             #   5-layer compression + read/write tool batching
│   │   │   ├── context.py          #   system prompt + auto-recall from persistent memory
│   │   │   ├── skills.py           #   skill loader (71 bundled + user-created via CRUD)
│   │   │   ├── tools.py            #   tool base class + registry
│   │   │   ├── memory.py           #   lightweight workspace state per run
│   │   │   ├── frontmatter.py      #   shared YAML frontmatter parser
│   │   │   └── trace.py            #   execution trace writer
│   │   │
│   │   ├── memory/                 # Cross-session persistent memory
│   │   │   └── persistent.py       #   file-based memory (~/.vibe-trading/memory/)
│   │   │
│   │   ├── tools/                  # 27 auto-discovered agent tools
│   │   │   ├── backtest_tool.py    #   run backtests
│   │   │   ├── remember_tool.py    #   cross-session memory (save/recall/forget)
│   │   │   ├── skill_writer_tool.py #  skill CRUD (save/patch/delete/file)
│   │   │   ├── session_search_tool.py # FTS5 cross-session search
│   │   │   ├── swarm_tool.py       #   launch swarm teams
│   │   │   ├── web_search_tool.py  #   DuckDuckGo web search
│   │   │   └── ...                 #   bash, file I/O, factor analysis, options, etc.
│   │   │
│   │   ├── skills/                 # 71 finance skills in 7 categories (SKILL.md each)
│   │   ├── swarm/                  # Swarm DAG execution engine
│   │   ├── session/                # Multi-turn chat + FTS5 session search
│   │   └── providers/              # LLM provider abstraction
│   │
│   ├── backtest/                   # Backtest engines
│   │   ├── engines/                #   7 engines + composite cross-market engine + options_portfolio
│   │   ├── loaders/                #   5 sources: tushare, okx, yfinance, akshare, ccxt
│   │   │   ├── base.py             #   DataLoader Protocol
│   │   │   └── registry.py         #   Registry + auto-fallback chains
│   │   └── optimizers/             #   MVO, equal vol, max div, risk parity
│   │
│   └── config/swarm/               # 29 swarm preset YAML definitions
│
├── frontend/                       # Web UI (React 19 + Vite + TypeScript)
│   └── src/
│       ├── pages/                  #   Home, Agent, RunDetail, Compare
│       ├── components/             #   chat, charts, layout
│       └── stores/                 #   Zustand state management
│
├── Dockerfile                      # Multi-stage build
├── docker-compose.yml              # One-command deploy
├── pyproject.toml                  # Package config + CLI entrypoint
└── LICENSE                         # MIT

</details>

🏛 Ecosystem

Vibe-Trading is part of the HKUDS agent ecosystem:

<table> <tr> <td align="center" width="25%"> <a href="https://github.com/HKUDS/ClawTeam"><b>ClawTeam</b></a><br> <sub>Agent Swarm Intelligence</sub> </td> <td align="center" width="25%"> <a href="https://github.com/HKUDS/nanobot"><b>NanoBot</b></a><br> <sub>Ultra-Lightweight Personal AI Assistant</sub> </td> <td align="center" width="25%"> <a href="https://github.com/HKUDS/CLI-Anything"><b>CLI-Anything</b></a><br> <sub>Making All Software Agent-Native</sub> </td> <td align="center" width="25%"> <a href="https://github.com/HKUDS/OpenSpace"><b>OpenSpace</b></a><br> <sub>Self-Evolving AI Agent Skills</sub> </td> </tr> </table>

🗺 Roadmap

We ship in phases. Items move to Issues when work begins.

Phase	Feature	Status
Agent Harness	Persistent cross-session memory (remember / recall / forget)	Done
	Self-evolving skills — agent creates, patches, and deletes its own workflows	Done
	FTS5 cross-session search across all past conversations	Done
	5-layer context compression (micro → collapse → auto → manual → iterative)	Done
	Read/write tool batching — parallel execution for readonly tools	Done
Next Up	Autonomous research loop — agent iterates hypotheses overnight	In Progress
	IM integration (Slack / Telegram / WeChat)	Planned
Analysis & Viz	Options volatility surface & Greeks 3D visualization	Planned
	Cross-asset correlation heatmap with rolling window & clustering	Planned
	Benchmark comparison in CLI backtest output	Planned
Skills & Presets	Dividend Analysis skill	Planned
	ESG / Sustainable Investing swarm preset	Planned
Portfolio & Optimization	Advanced portfolio optimizer: leverage, sector caps, turnover constraints	Planned
Future	Strategy marketplace (share & discover)	Exploring
	Live data streaming via WebSocket	Exploring

Contributing

We welcome contributions! See CONTRIBUTING.md for guidelines.

Good first issues are tagged with good first issue — pick one and get started.

Want to contribute something bigger? Check the Roadmap above and open an issue to discuss before starting.

Contributors

Thanks to everyone who has contributed to Vibe-Trading!

Disclaimer

Vibe-Trading is for research, simulation, and backtesting only. It is not investment advice and it does not execute live trades. Past performance does not guarantee future results.

License

MIT License — see LICENSE

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