Fund Ai Assistant

Other

Fund portfolio tracker with AI analysis, multi-agent debate, technical indicators (VaR/Sortino/Calmar), macro monitoring, and rebalancing alerts.

Install

openclaw skills install fund-ai-assistant

Fund AI Assistant

Version: 3.0 | License: MIT-0 | LLM: Any OpenAI-compatible provider

Overview

A local-first fund investment assistant running entirely on your machine. Fetches data from East Money, analyzes with any LLM provider, and supports scheduled tasks via OpenClaw or crontab.

⚠️ Security Notice: This skill requires LLM_MODEL + LLM_API_KEY. Use a dedicated API key. See Section 7 for all security considerations.

1. Features

Feature	Description
📊 Technical Analysis	MACD / KDJ / RSI / Bollinger Bands / MA + VaR / Sortino / Calmar
🤖 AI Quantitative Analysis	Any LLM (OpenAI-compatible), outputs buy/sell/hold with price targets
⚖️ Multi-Agent Debate	6 roles → game-theory judge verdict
📋 Portfolio Rebalancing	Detects allocation drift, outputs precise rebalancing instructions
🎯 Entry Timing	RSI + Bollinger + trend composite score
🌡️ Correlation Heatmap	Pairwise correlation matrix for diversification
🌍 Macro Event Monitor	CSI300 / USD-CNY / FOMC / LPR alerts

2. Environment Variables

Required

Variable	Description
`LLM_MODEL`	Model name, e.g. `gpt-4o-mini`
`LLM_API_KEY`	Your LLM API key

Optional

Variable	Description
`LLM_API_BASE`	⚠️ Custom API URL — if untrusted, your key and data go there. Use endpoints you control. Default: `https://api.openai.com/v1`
`TAVILY_API_KEY`	Tavily API for real-time macro search
`FUND_SCENE_DIR`	Directory with optional `.md` scene templates (default: `./scenes/`)
`PUSH_WEBHOOK_URL`	Generic HTTP POST webhook (WeCom / Feishu / Slack)
`BARK_PUSH_URL`	iOS Bark notification URL
`PUSH_EMAIL`	Target email for SMTP push
`SMTP_HOST/PORT/USER/PASS`	SMTP configuration (used with `PUSH_EMAIL`)
`QQ_WEBHOOK_URL`	QQ bot HTTP interface (go-cqhttp / Lagrange)

Setup Example

export LLM_MODEL="gpt-4o-mini"
export LLM_API_KEY="sk-xxx"

# Optional
export TAVILY_API_KEY="tvly-xxx"
export PUSH_WEBHOOK_URL="https://qyapi.weixin.qq.com/cgi-bin/webhook/send?key=YOUR_KEY"

3. Installation

# 1. Clone
git clone https://github.com/tempest-01/fund-ai-assistant.git
cd fund-ai-assistant

# 2. Install optional dependencies (charts)
pip install -r requirements.txt

# 3. Configure
cp config.example.json config.json
cp positions.example.json positions.json

# 4. Set environment variables (see Section 2)
export LLM_MODEL="your_model"
export LLM_API_KEY="your_key"

# 5. Verify
python3 analyzer.py list
python3 analyzer.py analyze

4. Script Reference

Script	Function	Usage
`analyzer.py`	Main entry, tracking + analysis	`python3 analyzer.py list`
`ai_analysis.py`	AI quantitative analysis	`python3 ai_analysis.py`
`debate_analyzer.py`	Multi-agent debate	`python3 debate_analyzer.py <code>`
`rebalance.py`	Portfolio drift detection	`python3 rebalance.py`
`recommend.py`	Entry timing suggestions	`python3 recommend.py`
`event_monitor.py`	Macro event monitor	`python3 event_monitor.py`
`correlation_v2.py`	Correlation heatmap	`python3 correlation_v2.py`
`fund_api.py`	East Money data API	`python3 fund_api.py`
`technical.py`	Technical indicators	`python3 technical.py`
`chart_generator.py`	PIL chart generation	`python3 chart_generator.py`
`positions.py`	Position record management	`python3 positions.py`
`macro_fetcher.py`	Macro data fetcher	`python3 macro_fetcher.py`
`strip_color.py`	ANSI strip for cron	`cmd \| python3 strip_color.py`
`llm.py`	Unified LLM interface	`from llm import get_llm_config, call_llm`

5. Scheduled Tasks (Reference)

# OpenClaw users
openclaw cron add --cron "0 8 * * 1-5" \
  --message "cd /path/to/fund-ai-assistant && python3 event_monitor.py --dry-run"

openclaw cron add --cron "30 9 * * 1-5" \
  --message "cd /path/to/fund-ai-assistant && python3 analyzer.py analyze"

# crontab users
0 8 * * 1-5 cd /path/to/fund-ai-assistant && python3 event_monitor.py >> /var/log/fund.log 2>&1

6. File Structure

fund-ai-assistant/
├── .gitignore
├── _meta.json              # Registry metadata
├── SKILL.md               # This file
├── README.md              # Full bilingual documentation
├── config.example.json     # Tracking list template
├── positions.example.json  # Position record template
├── requirements.txt       # Optional: Pillow / numpy / matplotlib
├── llm.py                # Unified LLM interface
├── analyzer.py            # Main entry
├── ai_analysis.py         # AI quantitative analysis
├── debate_analyzer.py    # Multi-agent debate
├── rebalance.py           # Portfolio drift detection
├── recommend.py          # Entry timing
├── event_monitor.py      # Macro event monitor
├── correlation_v2.py     # Correlation heatmap
├── fund_api.py           # East Money API
├── technical.py          # Technical indicators
├── chart_generator.py    # PIL chart generation
├── macro_fetcher.py      # Macro data
├── positions.py          # Position records
├── strip_color.py        # ANSI color strip
└── assets/             # Chart output (auto-created)

7. Security Notes

Read carefully before installing and running.

Required Credentials

LLM_MODEL and LLM_API_KEY are required. Use a dedicated API key, not a high-value production key.
Before first run, inspect llm.py and fund_api.py to confirm no credential exfiltration.

Filesystem Access

FUND_SCENE_DIR: The skill reads .md template files from the directory you specify.
- Do NOT point it at system directories, home directories, or folders containing secrets.
- If unset, defaults to {skill_dir}/scenes/ (which is created empty).
- Only .md files in that directory are read.

Network Access

East Money APIs: fundgz.1234567.com.cn, api.fund.eastmoney.com — public fund data.
Tavily (if TAVILY_API_KEY set): Real-time macro search.
Push endpoints (if configured): Analysis summaries are sent to the URLs you provide.

Push Channels

If any of these are set, analysis output will be transmitted externally:

Variable	Transmission
`PUSH_WEBHOOK_URL`	HTTP POST to your webhook URL
`BARK_PUSH_URL`	GET request to your Bark URL
`PUSH_EMAIL`	SMTP email to your address
`QQ_WEBHOOK_URL`	HTTP POST to your QQ bot

Use endpoints you control. Do not set these with untrusted third-party URLs.

Data Privacy

All fund data is fetched from East Money on demand; no persistent storage of market data.
Position records (positions.json) are stored locally in the skill directory only.
LLM API key is sent only to the configured LLM_API_BASE endpoint.
No telemetry, no external analytics, no data sent to third parties without explicit configuration.

Recommended Precautions

Use a dedicated LLM API key — not your main production key.
⚠️ Inspect LLM_API_BASE — if set to an untrusted endpoint, your API key and fund data will be sent there. Only use https://api.openai.com/v1 or endpoints you control.
Review llm.py and fund_api.py before first run.
Run in an isolated environment (container or VM) on first use.
Do not set FUND_SCENE_DIR to sensitive directories.
Do not share your LLM_API_KEY or push endpoint URLs.

8. Inspiration & Attribution

astrbot_plugin_fund_analyzer — Multi-agent debate framework inspiration; adapted from stock to fund analysis with added portfolio management features.
OpenClaw — Scheduling and notification infrastructure.
East Money (东方财富) — Fund price and history data source.
Tencent Finance (腾讯财经) — CSI300 real-time data source.

This skill was developed with AI assistance.