indicator-scanner

Q: How do I install indicator-scanner?

Run npx skills add https://github.com/marketcalls/openalgo-indicator-skills --skill indicator-scanner in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/indicator-scanner/ (personal) or .claude/skills/indicator-scanner/ (project).

by marketcalls

Scan multiple symbols with indicator conditions. Find stocks matching RSI oversold, EMA crossovers, Supertrend signals, and custom filter combinations.

Installs: 582
Last 24h: —
Trending rank: —
Security: Not audited

Install

Works with every agent the skills CLI supports.

npx skills add https://github.com/marketcalls/openalgo-indicator-skills --skill indicator-scanner

01
Install
Run the command in your project. The CLI asks which agents to install for.
02
Describe the task
Ask your agent for something this skill covers. It loads indicator-scanner automatically when relevant.
03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.

SKILL.md

The instructions your agent reads when the skill is triggered.

Create a multi-symbol indicator scanner that screens stocks by technical conditions.

Arguments

Parse $ARGUMENTS as: scan-type watchlist

$0 = scan type (e.g., rsi-oversold, rsi-overbought, ema-crossover, supertrend-buy, supertrend-sell, macd-crossover, adx-trending, custom). Default: rsi-oversold
$1 = watchlist (e.g., nifty50, banknifty, custom). Default: nifty50

If no arguments, ask the user what they want to scan for.

Instructions

Read the indicator-expert rules for reference
Create scanners/{scan_type}/ directory (on-demand)
Create {scan_type}_scanner.py
The script must:
- Load .env from project root
- Define the watchlist (predefined or custom)
- Fetch data for each symbol via client.history()
- Compute indicator(s) using openalgo.ta
- Check the scan condition
- Print results as a formatted table
- Save results to CSV
- Optionally get real-time LTP via client.quotes() for current values

Scan Logic Pattern

results = []
for symbol in watchlist:
    df = fetch_data(symbol, exchange, interval)
    close = df["close"]

    # Compute indicator
    rsi = ta.rsi(close, 14)
    current_rsi = rsi.iloc[-1]

    # Check condition
    if current_rsi < 30:  # RSI oversold
        results.append({
            "symbol": symbol,
            "ltp": close.iloc[-1],
            "rsi": current_rsi,
            "signal": "OVERSOLD",
        })

# Print table
df_results = pd.DataFrame(results)
print(df_results.to_string(index=False))
df_results.to_csv(script_dir / f"{scan_type}_results.csv", index=False)

Predefined Scan Types

Scan Type	Condition	Indicator
`rsi-oversold`	RSI(14) < 30	RSI
`rsi-overbought`	RSI(14) > 70	RSI
`ema-crossover`	EMA(10) crossed above EMA(20) in last 3 bars	EMA
`ema-crossunder`	EMA(10) crossed below EMA(20) in last 3 bars	EMA
`supertrend-buy`	Supertrend direction changed to -1 (uptrend)	Supertrend
`supertrend-sell`	Supertrend direction changed to 1 (downtrend)	Supertrend
`macd-crossover`	MACD crossed above Signal in last 3 bars	MACD
`adx-trending`	ADX > 25 (strong trend)	ADX
`bb-squeeze`	Bollinger Width at 20-bar low (volatility squeeze)	Bollinger
`volume-spike`	Volume > 2x 20-day average	Volume
`custom`	Ask user for conditions	Any

Predefined Watchlists

NIFTY 50 (nifty50)

NIFTY50 = [
    "ADANIENT", "ADANIPORTS", "APOLLOHOSP", "ASIANPAINT", "AXISBANK",
    "BAJAJ-AUTO", "BAJFINANCE", "BAJAJFINSV", "BPCL", "BHARTIARTL",
    "BRITANNIA", "CIPLA", "COALINDIA", "DIVISLAB", "DRREDDY",
    "EICHERMOT", "GRASIM", "HCLTECH", "HDFCBANK", "HDFCLIFE",
    "HEROMOTOCO", "HINDALCO", "HINDUNILVR", "ICICIBANK", "INDUSINDBK",
    "INFY", "ITC", "JSWSTEEL", "KOTAKBANK", "LT",
    "M&M", "MARUTI", "NESTLEIND", "NTPC", "ONGC",
    "POWERGRID", "RELIANCE", "SBILIFE", "SBIN", "SUNPHARMA",
    "TCS", "TATACONSUM", "TATAMOTORS", "TATASTEEL", "TECHM",
    "TITAN", "ULTRACEMCO", "UPL", "WIPRO",
]

Bank NIFTY (banknifty)

BANKNIFTY = [
    "HDFCBANK", "ICICIBANK", "KOTAKBANK", "AXISBANK", "SBIN",
    "INDUSINDBK", "BANKBARODA", "FEDERALBNK", "PNB", "IDFCFIRSTB",
    "BANDHANBNK", "AUBANK",
]

Output Format

Symbol     LTP      RSI(14)  Signal
------     ---      -------  ------
SBIN       769.60   28.4     OVERSOLD
TATASTEEL  142.30   25.1     OVERSOLD
COALINDIA  385.00   29.7     OVERSOLD

Scan: RSI Oversold (<30) | Watchlist: NIFTY 50 | Date: 2025-02-28
Found 3 / 50 symbols matching condition
Results saved to: scanners/rsi_oversold/rsi_oversold_results.csv

Example Usage

/indicator-scanner rsi-oversold nifty50 /indicator-scanner ema-crossover banknifty /indicator-scanner supertrend-buy nifty50 /indicator-scanner volume-spike nifty50 /indicator-scanner custom

FAQ

What does the indicator-scanner skill do?

Scan multiple symbols with indicator conditions. Find stocks matching RSI oversold, EMA crossovers, Supertrend signals, and custom filter combinations.

How do I install indicator-scanner?

Run npx skills add https://github.com/marketcalls/openalgo-indicator-skills --skill indicator-scanner in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/indicator-scanner/ (personal) or .claude/skills/indicator-scanner/ (project).

Which AI agents can use indicator-scanner?

Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.

Is indicator-scanner safe to install?

No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.

Who maintains indicator-scanner?

It is published by marketcalls in marketcalls/openalgo-indicator-skills. It has 582 recorded installs.