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finance-agent

NSE stock market analysis using Groww API. Use when users ask about Indian stocks, live prices, technical analysis, RSI, moving averages, or market comparison.

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SKILL.md
Quality
Evals
Security

Finance Agent

Read-only NSE stock analysis using Groww Trading API.

Architecture

┌─────────────────────────────────────────┐
│         Opencode Agent                  │
│  (handles reasoning & decisions)        │
└─────────────────────────────────────────┘
           │
           ▼
┌─────────────────────────────────────────┐
│         Markdown Skills                 │
├─────────────────────────────────────────┤
│  stock-data.md      - Live/HIST data    │
│  technical.md        - RSI, MA, MACD     │
│  compare.md          - Stock comparison  │
│  news-analysis.md    - News & sentiment  │
│  analysis-workflow.md - Complete workflow │
└─────────────────────────────────────────┘
           │
           ▼
┌─────────────────────────────────────────┐
│         Data Sources                     │
├─────────────────────────────────────────┤
│  Groww API          - Live prices, RSI   │
│  Web Search          - News, sentiment   │
│  Python Tools        - Analysis scripts  │
└─────────────────────────────────────────┘

Setup

# Install dependencies
pip install growwapi pyotp python-dotenv

# Set environment variables
cp .env.example .env
# Edit .env with your Groww API credentials

Environment Variables

# Option 1: API Key + Secret
GROWW_API_KEY=your_api_key
GROWW_API_SECRET=your_api_secret

# Option 2: TOTP (no daily re-auth)
GROWW_API_KEY=your_totp_token
GROWW_USE_TOTP=true
GROWW_TOTP_SECRET=your_totp_secret

# Option 3: Pre-generated access token
GROWW_ACCESS_TOKEN=your_access_token

Quick Start

CLI Usage

# Get stock data with RSI
python tools/stock_data.py RELIANCE INFY --quote --rsi

# Calculate technical indicators
python tools/technical.py RELIANCE --indicators rsi,ma,macd

# Compare multiple stocks
python tools/compare.py RELIANCE INFY TCS --full

Python API

from tools.groww_client import GrowwClient
from tools.portfolio_analyzer import PortfolioAnalyzer
from tools.technical import calculate_indicators
from tools.compare import compare_stocks

# Initialize
client = GrowwClient()

# Get prices
prices = client.get_ltp(["RELIANCE", "INFY"])
# {'NSE_RELIANCE': 2500.5, 'NSE_INFY': 1580.25}

# Get full quote
quote = client.get_quote("RELIANCE")

# Calculate RSI
rsi = client.calculate_rsi("RELIANCE")
# 58.5

# Get moving averages
ma = client.calculate_moving_averages("RELIANCE")
# {'sma_20': 2450.0, 'sma_50': 2400.0}

# Portfolio - Holdings
holdings = client.get_holdings()
# {'holdings': [{'trading_symbol': 'RELIANCE', 'quantity': 10, 'average_price': 2500}]}

# Portfolio - Positions
positions = client.get_positions()
# {'positions': [{'trading_symbol': 'RELIANCE', 'segment': 'CASH', 'realised_pnl': 500}]}

# Full Portfolio Analysis
analyzer = PortfolioAnalyzer()
summary = analyzer.analyze_portfolio()
# {'total_invested': 65500, 'current_value': 65900, 'total_pl_percentage': 0.61, ...}

# Compare stocks
comparison = compare_stocks(["RELIANCE", "INFY", "TCS"], full=True)

Skills

1. Stock Data (skills/stock-data.md)

  • Live prices (LTP)
  • OHLC data
  • Volume, 52-week high/low
  • Historical candles

2. Technical Analysis (skills/technical.md)

  • RSI (Relative Strength Index)
  • Moving Averages (SMA 20/50/200)
  • MACD signals
  • Support/Resistance levels
  • Trend determination

3. Compare (skills/compare.md)

  • Side-by-side stock comparison
  • Ranking by momentum/RSI
  • Quick selection tool

4. Portfolio Analyzer (skills/portfolio.md)

  • Holdings view (delivery stocks from Demat)
  • Positions view (intraday/derivatives)
  • P&L analysis with unrealized gains/losses
  • Best/worst performer identification
  • Groww Portfolio API integration

5. News Analysis (skills/news-analysis.md)

  • Recent news research via web search
  • Sentiment classification (POSITIVE/NEGATIVE/NEUTRAL)
  • Impact assessment
  • Catalyst identification
  • Use agent's websearch tool to fetch news

6. Workflow (skills/analysis-workflow.md)

  • Complete analysis template
  • Signal interpretation
  • Example analysis

Example Session

User: "What's the RSI for RELIANCE and INFY?"

Agent:

python tools/stock_data.py RELIANCE INFY --rsi

Response:

{
  "RELIANCE": {"ltp": 2500.5, "rsi": 58.5},
  "INFY": {"ltp": 1580.25, "rsi": 62.3}
}

Interpretation: Both in neutral zone (30-70), INFY slightly overbought.

User: "Compare RELIANCE vs TCS for short-term trading"

Agent:

python tools/compare.py RELIANCE TCS --full
python tools/technical.py RELIANCE --indicators rsi,ma,trend
python tools/technical.py TCS --indicators rsi,ma,trend

Available Tools

ToolPurposeExample
stock_data.pyGet prices/datapython tools/stock_data.py RELIANCE --quote
technical.pyCalculate indicatorspython tools/technical.py RELIANCE --indicators rsi,ma
compare.pyCompare stockspython tools/compare.py RELIANCE INFY
portfolio_analyzer.pyPortfolio analysispython tools/portfolio_analyzer.py --analyze
groww_client.pyAPI wrapperclient.get_holdings()
news_tools.pySentiment analysisanalyze_sentiment(news_data)

Portfolio Analysis

# View your holdings with P&L
python tools/portfolio_analyzer.py --holdings

# Full portfolio analysis
python tools/portfolio_analyzer.py --analyze

# View positions (intraday/F&O)
python tools/portfolio_analyzer.py --positions --segment FNO

Python API

from tools.groww_client import GrowwClient
from tools.portfolio_analyzer import PortfolioAnalyzer

client = GrowwClient()

# Get holdings
holdings = client.get_holdings()
# {'holdings': [{'trading_symbol': 'RELIANCE', 'quantity': 10, 'average_price': 2500, ...}]}

# Get positions
positions = client.get_positions()
# {'positions': [{'trading_symbol': 'RELIANCE', 'segment': 'CASH', 'realised_pnl': 500, ...}]}

# Full analysis with P&L
analyzer = PortfolioAnalyzer()
summary = analyzer.analyze_portfolio()
# Returns total invested, current value, P&L, best/worst performers

News Research Workflow

  1. Search news: Use agent's websearch tool

    websearch(query="HDFCBANK stock news March 2026", numResults=10)

  2. Analyze sentiment: Use analyze_sentiment() from news_tools

    from skills.news_tools import analyze_sentiment
sentiment = analyze_sentiment({"results": news_articles})

  3. Assess impact: Combine with technical data for complete analysis

Read-Only

This agent only reads market data. No order placement, no trading.

Repository
lakhanjindam/opencode-finance-agent
Commit

aa3e399

Last updated
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