Skill: warren618/vibe-trading (version 0.1.8)

--- name: vibe-trading version: 0.1.8 description: Professional finance research toolkit — backtesting (7 engines + benchmark comparison panel), factor analysis, Alpha Zoo (452 pre-built alphas across qlib158/alpha101/gtja191/academic), options pricing, 75 finance skills, 29 multi-agent swarm teams, Trade Journal analyzer, and Shadow Account (extract → backtest → render) across 6 data sources (tushare, yfinance, okx, akshare, ccxt, futu). dependencies: python: ">=3.11" pip: - vibe-trading-ai env: - name: TUSHARE_TOKEN description: "Tushare API token for China A-share data (optional — HK/US/crypto work without any key)" required: false - name: OPENAI_API_KEY description: "OpenAI-compatible API key — only needed for run_swarm (multi-agent teams). All other tools work without it." required: false - name: LANGCHAIN_MODEL_NAME description: "LLM model name for run_swarm (e.g. deepseek/deepseek-v3.2). Only needed if using run_swarm." required: false mcp: command: vibe-trading-mcp args: [] --- # Vibe-Trading Professional finance research toolkit with AI-powered backtesting (7 engines), multi-agent teams, 75 specialized skills, the **Alpha Zoo** (452 pre-built quantitative alphas across qlib158 / alpha101 / gtja191 / academic with one-line CLI benchmarking), and the Shadow Account loop — extract your implicit trading rules from a journal, backtest them across A股/港股/美股/crypto, then see where they would have served you better. ## Setup ```bash pip install vibe-trading-ai ``` > **Package name vs commands:** The PyPI package is `vibe-trading-ai`. Once installed, you get: > > | 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.) | Add to your agent's MCP config: ```json { "mcpServers": { "vibe-trading": { "command": "vibe-trading-mcp" } } } ``` ### API Key Requirements **21 of 22 MCP tools work with zero API keys.** After `pip install`, backtesting, market data, factor analysis, options pricing, chart patterns, web search, document reading, trade journal analysis, shadow-account extraction/backtest/report, the Alpha Zoo (452 pre-built alphas), and all 75 skills are ready to use for HK/US equities and crypto. | Feature | Key needed | When | |---------|-----------|------| | HK/US equities & crypto | None | Always free (yfinance + OKX) | | China A-share data | `TUSHARE_TOKEN` | Only if you query A-share symbols | | Multi-agent swarm (`run_swarm`) | `OPENAI_API_KEY` + `LANGCHAIN_MODEL_NAME` | Swarm spawns internal LLM workers | ## What You Can Do ### Shadow Account — flagship loop Feed a CSV broker export (同花顺 / 东财 / 富途 / generic), and the agent will: 1. `analyze_trade_journal` — profile your behavior (holding period, win rate, disposition effect, chasing, overtrading, anchoring). 2. `extract_shadow_strategy` — distill 3-5 if-then rules that describe your profitable roundtrips. 3. `run_shadow_backtest` — backtest those rules across A/HK/US/crypto and compute delta-PnL vs your realized trades. 4. `render_shadow_report` — produce an HTML/PDF report (8 sections + charts) with today's matching signals. 5. `scan_shadow_signals` — list today's symbols that match your shadow's entry cadence (research only). ### Backtesting Create and run quantitative strategies across 7 engines (ChinaA, GlobalEquity, Crypto, ChinaFutures, GlobalFutures, Forex + options) with 6 data sources: - **HK/US equities** via yfinance (free, no API key) - **Cryptocurrency** via OKX or CCXT/100+ exchanges (free, no API key) - **China A-shares** via Tushare (token) or AKShare (free fallback) - **Futures, forex, macro** via AKShare (free, no API key) - **HK & A-share equities** via Futu (broker login required, optional) Example workflow: 1. Use `list_skills()` to discover strategy patterns 2. Use `load_skill("strategy-generate")` for the strategy creation guide 3. Use `write_file()` to create `config.json` and `code/signal_engine.py` 4. Use `backtest()` to run and get metrics (Sharpe, return, drawdown, etc.) ### Multi-Agent Swarm Teams 29 pre-built agent teams for complex research: - **Investment Committee**: bull/bear debate → risk review → PM decision - **Global Equities Desk**: A-share + HK/US + crypto → global strategist - **Crypto Trading Desk**: funding/basis + liquidation + flow → risk manager - **Earnings Research Desk**: fundamentals + revisions + options → earnings strategist - **Macro/Rates/FX Desk**: rates + FX + commodities → macro PM - **Quant Strategy Desk**: screening → factor research → backtest → risk audit - **Risk Committee**: drawdown, tail risk, regime analysis - And 22 more specialized teams Use `list_swarm_presets()` to see all teams, then `run_swarm()` to execute. ### Alpha Zoo (452 pre-built alphas) One-line cross-sectional IC / IR / alive-reversed-dead categorisation across four bundled zoos: - **qlib158** (154 alphas) — Microsoft Qlib's `Alpha158` feature handler, Apache-2.0 with pinned commit SHA. - **alpha101** (101 alphas) — Kakushadze (2015) "101 Formulaic Alphas" (arXiv:1601.00991), written from the paper appendix. - **gtja191** (191 alphas) — Guotai Junan 2014 "191 Short-period Trading Alpha Factors" research report. - **academic** (6 factors) — Fama-French 5 + Carhart momentum (honest price-based proxies). Each alpha ships with `__alpha_meta__` (formula LaTeX + theme + universe + warmup + columns required), guarded by an AST purity gate + 300-row lookahead sentinel test. Use the `vibe-trading alpha {list,show,bench,compare,export-manifest}` CLI, the `/alpha/*` REST routes (browser at `/alpha-zoo`), or compose multi-factor signals via `ZooSignalEngine.from_zoo(...)`. ### Finance Skills (75) Comprehensive knowledge base covering: - Technical analysis (candlestick, Elliott wave, Ichimoku, SMC, harmonic, chanlun) - Quantitative methods (factor research, ML strategy, pair trading, multi-factor) - Risk management (VaR/CVaR, stress testing, hedging) - Options (Black-Scholes, Greeks, multi-leg strategies, payoff diagrams) - HK/US equities (SEC filings, earnings revisions, ETF flows, ADR/H-share arbitrage) - Crypto trading desk (funding rates, liquidation heatmaps, stablecoin flows, token unlocks, DeFi yields) - Behavioral finance, trade journal diagnostics, shadow account - Macro analysis, credit research, sector rotation, and more Use `load_skill(name)` to access full methodology docs with code templates. ## Available MCP Tools (22) | Tool | Description | API Key | |------|-------------|---------| | `list_skills` | List all 75 finance skills | None | | `load_skill` | Load full skill documentation | None | | `backtest` | Run vectorized backtest engine | None* | | `factor_analysis` | IC/IR analysis + layered backtest | None* | | `analyze_options` | Black-Scholes price + Greeks | None | | `pattern_recognition` | Detect chart patterns (H&S, double top, etc.) | None | | `get_market_data` | Fetch OHLCV data across 6 sources (auto-detect + fallback) | None* | | `web_search` | Search the web via DuckDuckGo | None | | `read_url` | Fetch web page as Markdown | None | | `read_document` | Extract text from PDF/DOCX/XLSX/PPTX/images | None | | `write_file` | Write files (config, strategy code) | None | | `read_file` | Read file contents | None | | `analyze_trade_journal` | Parse broker CSV → profile + behavior diagnostics | None | | `extract_shadow_strategy` | Distill 3-5 if-then rules from profitable roundtrips | None | | `run_shadow_backtest` | Multi-market backtest + delta-PnL attribution | None* | | `render_shadow_report` | HTML/PDF shadow report (8 sections + charts) | None | | `scan_shadow_signals` | Today's symbols matching the shadow's cadence | None | | `list_swarm_presets` | List multi-agent team presets | None | | `run_swarm` | Execute a multi-agent research team | LLM key | | `get_swarm_status` | Poll swarm run status without blocking | None | | `get_run_result` | Get final report and task summaries | None | | `list_runs` | List recent swarm runs with metadata | None | <sub>*A-share symbols require `TUSHARE_TOKEN`. HK/US/crypto are free.</sub> ## Quick Start ```bash pip install vibe-trading-ai ``` That's it — no API keys needed for HK/US/crypto markets. Start using `backtest`, `get_market_data`, `analyze_options`, `analyze_trade_journal`, `extract_shadow_strategy`, `web_search`, the **Alpha Zoo** (`vibe-trading alpha bench --zoo gtja191 --universe csi300 --period 2018-2025`), and all 75 skills immediately. ## Loading Tools from External MCP Servers The built-in agent can load tools from your own external MCP servers in addition to its local toolset. > **Note:** This is the *MCP client* path — the opposite of the MCP plugin listed above. The plugin above makes Vibe-Trading's tools available to your agents. This section lets Vibe-Trading's own agent call tools from *your* servers. ### Setup Create `~/.vibe-trading/agent.json`: ```json { "mcpServers": { "my-server": { "command": "uvx", "args": ["my-mcp-server"], "toolTimeout": 30, "enabledTools": ["*"] } } } ``` Remote tools appear automatically in every `vibe-trading run` / `vibe-trading chat` call. They are injected after local tools under stable names: `mcp_<server>_<tool>`. ### Config fields | Field | Required | Default | Description | |-------|----------|---------|-------------| | `command` | yes | — | Executable to launch | | `args` | no | `[]` | Command arguments | | `env` | no | `{}` | Extra env vars for the subprocess | | `toolTimeout` | no | `30` | Seconds before a tool call is cancelled | | `enabledTools` | no | `["*"]` | Allowlist of remote tool names. `["*"]` enables all | ### Per-session override (API) > **Security — disabled by default.** `mcpServers` defines subprocess `command`/`args`/`env` and is therefore restricted to operator-level trust. API callers **cannot** inject MCP server definitions through `POST /sessions` unless the server operator explicitly opts in. To enable session-level MCP injection, set the environment variable on the server before starting the agent: ```bash export ALLOW_SESSION_MCP_SERVERS=1 ``` With the opt-in active, pass `mcpServers` inside `session.config` to extend or replace the global config for that session only: ```json { "config": { "mcpServers": { "research": { "command": "uvx", "args": ["research-mcp"], "enabledTools": ["search"] } } } } ``` Without `ALLOW_SESSION_MCP_SERVERS=1`, any `mcpServers` key in `session.config` is silently stripped before config loading. The global operator config on disk (`~/.vibe-trading/agent.json`) is always respected regardless of this flag. ### v1 limits - **Transport:** stdio only. SSE and HTTP transports are rejected. - **Execution:** serial only. MCP tools never enter the parallel readonly path. - **Surfaces:** tools only. Resources and prompts are not exposed. - **Swarm:** MCP tools are excluded from Swarm worker registries in v1. - **Hot reload:** not supported. Restart the process to pick up config changes. ### Failure handling | Case | Behavior | |------|----------| | Missing config file | falls back to empty config — no MCP servers loaded | | Invalid config file | logs a warning and falls back to empty config | | Server fails to start | that server is skipped; local tools and other servers still load | | Tool call times out | returns a normalized error payload instead of raising | | Two server names collide after sanitization | deterministic hash suffix appended; operator warning emitted | ## Examples **Backtest a MACD strategy on Apple:** > Backtest AAPL with MACD crossover strategy (fast=12, slow=26, signal=9) for 2024 **Analyze my trade journal and build a Shadow Account:** > Call analyze_trade_journal on ~/Downloads/tonghuashun.csv, then extract_shadow_strategy with min_support=3, then run_shadow_backtest for the last year, then render_shadow_report. **Run an investment committee review:** > Use run_swarm with investment_committee preset to evaluate NVDA. Variables: target=NVDA.US, market=US **Factor analysis on CSI 300:** > Run factor_analysis on CSI 300 stocks using pe_ttm factor from 2023 to 2024 **Options analysis:** > Use analyze_options: spot=100, strike=105, 90 days, vol=25%, rate=3%


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)