Financial Intel

Financial Intelligence Skill

Real-time momentum scoring and market intelligence for 6,500+ stocks and crypto assets. Powered by Banana Farmer — an AI momentum scanner that combines technical analysis, price momentum, and social sentiment into a single 0-100 Ripeness Score.

Backed by 730 days of tracked data across 12,450+ signals with a verified 80% five-day win rate.

Quick Start

Option A — Self-provision a free key instantly (no account needed):

curl -s -X POST "https://bananafarmer.app/api/bot/v1/keys/trial" \
  -H "Content-Type: application/json" \
  -d '{"name": "My Agent", "email": "you@example.com"}'

Save the key from the response. One key per email, instant, no credit card.

Option B — Sign up for a full account: bananafarmer.app/developers

Then:

1. Set your key: export BF_API_KEY=bf_bot_your_key_here (or add to OpenClaw config)
2. Try it: python3 scripts/bf-lookup.py AAPL — you get score, badge, RSI, coil, price action, bull/bear case, and what to watch for

That is it. You are now scanning 6,500+ assets for momentum signals.

Prompt Examples

Single Ticker Analysis

Look up any stock or crypto symbol for a full momentum profile: score, badge, RSI, coil pattern, EMA alignment, price action, volatility, scoring breakdown, AI summary, and bull/bear cases.

Example prompts:

• "What's the momentum on AAPL?"
• "Look up TSLA for me"
• "How's Bitcoin looking?"
• "Check NVDA's score and technicals"
• "Is CRWV ripe?"
• "What's the coil score on AMD?"
• "Pull up the full analysis on SMCI"
• "Is PLTR overbought right now?"

How to run:

python3 scripts/bf-lookup.py AAPL
python3 scripts/bf-lookup.py TSLA NVDA AMD   # Multiple tickers at once
python3 scripts/bf-lookup.py BTC              # Crypto works too

What you get back: Score (0-100), badge (ripe/ripening/overripe/too-late/neutral), current price, 1d and 5d change, RSI with overbought/oversold labels, coil score with breakout flag, EMA 20/50 alignment, 52-week high proximity, volatility metrics, scoring breakdown (technical/momentum/social), key drivers, AI summary bullets, bull case, bear case, and what to watch for.

Top Signals / Batch Analysis

See the highest-scoring momentum signals right now — the tickers showing the strongest alignment across technical, price action, and social indicators.

Example prompts:

• "What are the top signals right now?"
• "Show me the hottest momentum setups"
• "Any ripe signals today?"
• "Top 5 stocks by momentum score"
• "What's ripening that I should watch?"
• "Show me the top 20 signals"
• "Any ripe crypto signals?"

How to run:

python3 scripts/bf-market.py top                        # Default top 10, all badges
python3 scripts/bf-market.py top --limit 20             # Top 20
python3 scripts/bf-market.py top --badge ripe           # Only ripe signals
python3 scripts/bf-market.py top --badge ripening       # Only ripening (watchlist candidates)
python3 scripts/bf-market.py top --limit 5 --badge ripe # Top 5 ripe only

What you get back: Ranked table with symbol, score, badge, 1-day change, 5-day change, and key drivers for each signal. Results are deduplicated by symbol automatically.

Portfolio Tracking

Track multiple holdings across accounts. Get a morning-brief-style intelligence report with alerts for RSI overbought/oversold, big daily moves, ripe/overripe signals, risk flags, and P&L calculations.

Example prompts:

• "Check my portfolio"
• "How are my holdings doing?"
• "Run a portfolio brief"
• "Any alerts on my positions?"
• "How's my aggressive account looking?"
• "What's the P&L on my tech holdings?"
• "Any of my holdings overbought?"
• "Which of my stocks are ripe right now?"

How to run:

python3 scripts/bf-portfolio.py portfolios.json                 # Full brief, all accounts
python3 scripts/bf-portfolio.py portfolios.json --account aaron  # Filter to one account
python3 scripts/bf-portfolio.py portfolios.json --json           # JSON output for piping

Portfolio file format (portfolios.json):

{
  "accounts": [
    {
      "id": "personal",
      "name": "My Portfolio",
      "risk_profile": "aggressive",
      "holdings": [
        {"symbol": "AAPL", "shares": 50, "cost_basis": 185.00},
        {"symbol": "NVDA", "shares": 20, "cost_basis": 450.00},
        {"symbol": "TSLA", "shares": 10, "cost_basis": 210.00}
      ]
    },
    {
      "id": "retirement",
      "name": "IRA Account",
      "risk_profile": "conservative",
      "holdings": [
        {"symbol": "VOO", "shares": 100, "cost_basis": 430.00},
        {"symbol": "ABBV", "shares": 40, "cost_basis": 155.00}
      ]
    }
  ]
}

What you get back: Market status, data freshness, per-account sections with alerts (overbought, oversold, big moves, ripe/overripe signals, too-late warnings, risk-profile mismatches), and detailed holding lines showing price, score, badge, changes, RSI, shares, cost basis, and unrealized P&L with percentages.

Alert types generated:

• SIGNAL: holding is ripe or overripe
• CAUTION: holding is too-late (momentum exhausted)
• OVERBOUGHT: RSI above 70 (or 80 for strong warning)
• OVERSOLD: RSI below 30 (potential bounce zone)
• BIG MOVE: more than 5% daily change
• WEEKLY: more than 10% five-day change
• NOTE: high momentum in conservative account

Market Overview

Get a bird's-eye view of the market: how many signals are firing by badge, what is trending, new ripe signals, and a narrative summary.

Example prompts:

• "What's the market doing today?"
• "Give me a market pulse"
• "How's the overall momentum landscape?"
• "How many ripe signals are there right now?"
• "What's trending in the market?"
• "Any new ripe signals today?"

How to run:

python3 scripts/bf-market.py pulse

What you get back: Narrative summary, signal counts broken down by badge (ripe, ripening, overripe, too-late, neutral), trending symbols, and newly ripe signals that just crossed the threshold.

Performance Tracking / Proof Data

See which signals actually played out: winners and losers with real entry prices, current prices, percentage moves, and milestone returns over multiple time horizons.

Example prompts:

• "Which signals worked this week?"
• "Show me recent winners"
• "What's the track record look like?"
• "Any big movers from recent signals?"
• "Show me winners from the last 30 days"
• "What percentage of signals won this week?"
• "What were the biggest losers recently?"

How to run:

python3 scripts/bf-movers.py                       # Default: last 7 days, top 5
python3 scripts/bf-movers.py --days 30 --limit 10  # Last 30 days, top 10
python3 scripts/bf-movers.py --days 1 --limit 3    # Today's movers

What you get back: Winners and losers sections, each showing symbol, percentage change, entry price, current price, and milestone returns (1d, 3d, 5d, 10d). Summary line with calculated win rate for the period.

Risk Assessment

Evaluate whether a stock is extended, overbought, or showing risk flags. Combine RSI, badge, coil, and volatility data into a risk picture.

Example prompts:

• "Is TSLA overbought?"
• "What's the risk on NVDA right now?"
• "Is AMD overripe?"
• "Should I be worried about my SMCI position?"
• "What's the max drawdown on CRWV?"
• "Is this too late to buy PLTR?"
• "Any of the top signals looking overextended?"

How to run:

python3 scripts/bf-lookup.py TSLA   # Check RSI, badge, volatility, and bear case

What to look for in the output:

• RSI above 70: overbought warning, watch for pullback
• RSI above 80: strongly overbought
• Badge "overripe": already extended, pullback likely
• Badge "too-late": chasing at this level carries elevated risk
• Max drawdown percentage: historical worst case from entry
• Average daily range: how volatile it trades
• Bear case: the AI-generated downside scenario

Comparison Queries

Compare multiple tickers side by side for momentum scores, technicals, and risk profiles.

Example prompts:

• "Compare AAPL vs MSFT momentum"
• "Which has better momentum: NVDA or AMD?"
• "Look up TSLA, RIVN, and LCID"
• "Compare the big tech names — AAPL, GOOGL, MSFT, META"
• "Which mega cap has the highest coil score?"

How to run:

python3 scripts/bf-compare.py AAPL MSFT          # Side-by-side table comparison
python3 scripts/bf-compare.py NVDA AMD INTC AVGO # Compare semiconductor names
python3 scripts/bf-compare.py TSLA RIVN LCID     # EV sector comparison
python3 scripts/bf-lookup.py AAPL MSFT           # Full deep-dive for each (more detail)

What you get back: A formatted comparison table showing score, badge, price, RSI, coil score, EMA alignment, 52-week proximity, scoring breakdown, and volatility side by side. Includes a verdict (strongest/weakest momentum) and risk flags (overbought, coiled for breakout).

Watchlist Management

Use the top signals and portfolio tools together to build and track watchlists. Filter by badge to focus on ripening setups that are worth monitoring.

Example prompts:

• "Add NVDA to my watchlist" (add to your portfolios.json)
• "What's ripening that I should watch?"
• "Build me a watchlist of ripening signals"
• "Update my watchlist with today's top ripening stocks"
• "Track these for me: AAPL, NVDA, AMD, TSLA"

How to run:

# Today's curated watchlist picks (pre-selected by the system)
python3 scripts/bf-watchlist.py picks

# Find watchlist candidates from top signals
python3 scripts/bf-market.py top --badge ripening --limit 10

# Track specific symbols (add to portfolios.json with 0 shares)
python3 scripts/bf-portfolio.py portfolios.json

Tip: Use bf-watchlist.py picks for the system's daily curated picks, or create a "watchlist" account in your portfolios.json with shares: 0 and cost_basis: 0 for each symbol. The portfolio brief will show scores, badges, RSI, and alerts without P&L calculations.

{
  "id": "watchlist",
  "name": "Watchlist",
  "risk_profile": "moderate",
  "holdings": [
    {"symbol": "NVDA", "shares": 0, "cost_basis": 0},
    {"symbol": "AMD", "shares": 0, "cost_basis": 0}
  ]
}

Sector and Theme Analysis

Analyze momentum across entire sectors, or drill into specific industry groups.

Example prompts:

• "Which sectors have the most momentum?"
• "What's the hottest sector right now?"
• "How are the semiconductor stocks doing?"
• "Check the EV sector — TSLA, RIVN, LCID, NIO"
• "Run the FAANG names for me"
• "What's happening in biotech?"
• "Check the momentum on airline stocks"

How to run:

# Full sector momentum breakdown (auto-classifies top 50 signals)
python3 scripts/bf-sectors.py

# Sector data as JSON for processing
python3 scripts/bf-sectors.py --json

# Deep-dive a specific sector group
python3 scripts/bf-compare.py NVDA AMD INTC AVGO  # Semiconductors
python3 scripts/bf-compare.py AAPL MSFT GOOGL META # Big tech
python3 scripts/bf-lookup.py TSLA RIVN LCID NIO    # Full detail per ticker

What you get back: The sectors script groups all top signals by sector (Technology, Healthcare, Financials, Energy, Consumer, Industrials, Real Estate, etc.), shows signal count, average score, heat rating (HOT/WARM/COOL/COLD), ripe signal count, and sector leaders. Use bf-compare.py for side-by-side comparison within a sector group.

Historical Context and Win Rates

Query the system's track record and statistical performance data.

Example prompts:

• "What's the 5-day win rate for ripe signals?"
• "How does 1-day performance compare to 5-day?"
• "What's the average return on signals above 90?"
• "How many signals have been tracked total?"
• "What's the historical data span?"
• "Does patience actually improve win rate?"

How to run:

python3 scripts/bf-watchlist.py scorecard  # System win rates by holding period and score threshold
python3 scripts/bf-watchlist.py horizons   # Time horizon analysis (how long to hold)
python3 scripts/bf-market.py health        # System stats and data freshness
python3 scripts/bf-movers.py --days 30     # Recent track record with win rate

Track record reference (from 12,450 signals over 730 days):

Key insight: Win rate starts at 76.5% on day one and climbs to 80.1% by one month. The edge is patience.

Alert-Style Queries

Check for actionable conditions across your holdings or the broader market.

Example prompts:

• "Alert me if any holding goes ripe"
• "Any of my stocks overbought?"
• "Which holdings have RSI below 30?"
• "Are any top signals showing a coil above 70?"
• "What in my portfolio has the biggest move today?"
• "Any too-late warnings on my positions?"

How to run:

# Portfolio alerts (automatically flags ripe, overbought, oversold, big moves)
python3 scripts/bf-portfolio.py portfolios.json

# Market-wide scan for ripe signals
python3 scripts/bf-market.py top --badge ripe --limit 20

# Check specific names for risk
python3 scripts/bf-lookup.py AAPL TSLA NVDA

The portfolio brief automatically generates alerts. Look for the ALERTS section, which flags: SIGNAL (ripe/overripe), CAUTION (too-late), OVERBOUGHT (RSI > 70), OVERSOLD (RSI < 30), BIG MOVE (> 5% daily), WEEKLY (> 10% five-day), and risk-profile mismatches.

System Health Check

Verify data freshness and market status before making decisions.

Example prompts:

• "Is the data fresh?"
• "Is the market open?"
• "Check system health"
• "Any data issues right now?"

How to run:

python3 scripts/bf-market.py health

What you get back: Market status (open, closed, pre-market, after-hours), data freshness (live, recent, stale), and any safety advisory. Always check health before acting on signals — stale data during market hours means something is wrong.

Understanding the Data

Ripeness Score (0-100)

The score is a composite of four pillars weighted by their predictive power:

Higher score means stronger alignment across all pillars. A score of 80 with Technical at 45% and Social at 35% tells a different story than 80 with Technical at 55% and Social at 20% — check the scoring breakdown.

Badge System

Score thresholds for significance: 95+ is rare and highest conviction, 85-94 is strong, 80-84 is actionable.

RSI (Relative Strength Index)

RSI measures momentum on a 0-100 scale:

• Below 30: Oversold. Price has been beaten down; potential bounce zone. Does not mean "buy" — it means selling pressure may be exhausting.
• 30-70: Normal range. No extreme reading.
• Above 70: Overbought. Price has been running hard; watch for pullback. Does not mean "sell" — strong trends stay overbought for weeks.
• Above 80: Strongly overbought. Higher probability of mean reversion.

Coil Score (0-100)

The coil score measures price compression — how tightly a stock's price is consolidating. Think of it as a spring being compressed:

• Below 40: Loose. Price is moving freely, no compression buildup.
• 40-69: Moderate compression. Some consolidation, but not yet significant.
• 70+: Coiled. Price is compressed into a tight range. This often precedes a sharp directional move (breakout or breakdown). This is the single most predictive indicator in the system.

A stock with a high coil score AND a ripe badge is the strongest setup: momentum is aligned, and price compression suggests the next move could be significant.

EMA 20 and EMA 50

Exponential Moving Averages smooth price data over 20 and 50 days:

• Price above both EMAs: Bullish trend — short and medium term aligned upward
• Price above EMA 20, below EMA 50: Short-term bounce in a longer downtrend — proceed with caution
• Price below both EMAs: Bearish trend — momentum is against you
• EMA 20 crossing above EMA 50: Golden cross — potential trend change

Proximity to 52-Week High

A decimal from 0 to 1 representing how close the current price is to its 52-week high:

• 0.95+ (95%+): Near highs — strong relative strength, but resistance ahead
• 0.80-0.95: Healthy uptrend territory
• Below 0.70: Significantly off highs — check if recovery or further decline

Track Record

The system is not new. It has been tracking signals for over two years:

• 12,450+ signals analyzed across 730 days
• 6,563 unique stocks tracked
• 80% five-day win rate with +4.51% average return
• 76.5% one-day win rate climbing to 80.1% by one month
• Win rate is consistent across score thresholds: 80+ scores all perform between 79-81%

Win Rate by Score Threshold (5-day horizon)

The Patience Edge

The data shows holding longer improves outcomes. Day-one win rate is 76.5%. By day five, it is 79.9%. By one month, 80.1%. Average returns scale from +1.35% (1 day) to +8.16% (1 month). The optimal risk/reward window is the 5-to-10-day holding period.

This is not a day-trading system. It catches momentum at 2% instead of 15%, then lets the move develop over days.

Error Handling

BF_API_KEY not set

ERROR: BF_API_KEY not set. Get your key at https://bananafarmer.app

Fix: Export your API key: export BF_API_KEY=bf_bot_your_key_here. Or add it to your OpenClaw config or .env file.

No signal data available

$XYZ: No signal data available

Cause: The symbol is not tracked, was delisted, or is a very low-volume OTC stock. Banana Farmer tracks 6,500+ stocks from NYSE and NASDAQ plus popular crypto. Penny stocks and OTC issues may not have enough data for a signal.

Fix: Verify the ticker symbol is correct. Try the exchange-standard format (no special characters). Crypto tickers use their standard symbols (BTC, ETH, SOL).

API timeout or connection error

$AAPL: Error — <urlopen error timed out>

Cause: The Banana Farmer API did not respond within 15 seconds. This can happen during high-traffic market opens or if the service is temporarily down.

Fix: Wait 30 seconds and retry. If repeated, check system health with python3 scripts/bf-market.py health. If health also times out, the API may be experiencing downtime.

Rate limiting

The API rate limits depend on your tier: Free (10/min, 50/day), Pro (60/min, 10K/day), Max (120/min, 50K/day). Under normal usage you will not hit these limits. If you do:

Fix: Space out requests. The portfolio script fetches one symbol at a time, so a portfolio of 20 holdings makes 21 API calls (20 lookups + 1 health check). This is well within limits.

Stale data warning

If bf-market.py health reports data freshness as "stale" during market hours, the data pipeline may be delayed. Signals and scores are based on data that refreshes every 15 minutes. Stale data (> 30 minutes old) during open market hours means scores may not reflect current conditions.

Fix: Note the staleness in your analysis. Prices move, but momentum signals are directional and usually remain valid for the session unless there is a major intraday reversal.

403 Forbidden

HTTP Error 403: Forbidden

Cause: Missing or malformed User-Agent header. The API requires a User-Agent: BananaFarmerBot/1.0 header.

Fix: The scripts set this automatically. If you are calling the API directly, make sure to include the header.

Advanced Usage

JSON Output Mode

For programmatic processing, the portfolio script supports JSON output:

python3 scripts/bf-portfolio.py portfolios.json --json

This returns a JSON object with a brief field (the formatted text) and a signals field (score and badge for each looked-up symbol). Use this for piping into other tools, dashboards, or automated workflows.

Multi-Account Portfolios

The portfolio file supports multiple accounts with different risk profiles. Each account gets its own section in the brief with account-specific alerts. A conservative account holding a high-momentum stock will get a NOTE alert that an aggressive account would not.

Supported risk profiles: conservative, moderate, aggressive. The --account filter accepts partial matches on both the account id and name fields.

python3 scripts/bf-portfolio.py portfolios.json --account ira
python3 scripts/bf-portfolio.py portfolios.json --account retirement

Combining Scripts

Chain scripts together for richer analysis:

# Morning routine: health check, then top signals, then portfolio
python3 scripts/bf-market.py health && python3 scripts/bf-market.py top --limit 5 && python3 scripts/bf-portfolio.py portfolios.json

# Find this week's winners, then deep-dive the top one
python3 scripts/bf-movers.py --days 7 --limit 1

# Scan for ripe signals and look up each one
python3 scripts/bf-market.py top --badge ripe --limit 5
python3 scripts/bf-lookup.py AAPL NVDA AMD  # use the symbols from top output

Filtering Top Signals

The top command supports badge and limit filters:

python3 scripts/bf-market.py top --badge ripe --limit 5     # Only highest conviction
python3 scripts/bf-market.py top --badge ripening --limit 10 # Watchlist candidates
python3 scripts/bf-market.py top --limit 50                  # Broad scan

Movers Time Range

Control the lookback window for performance tracking:

python3 scripts/bf-movers.py --days 1 --limit 3   # Today only
python3 scripts/bf-movers.py --days 7 --limit 10   # This week
python3 scripts/bf-movers.py --days 30 --limit 20  # This month

Scripts Reference

All scripts are in the scripts/ directory. All require python3 and BF_API_KEY in the environment. No additional pip packages are needed — everything uses the Python standard library.

Pricing

Get your key instantly at bananafarmer.app/developers. Free tier works immediately — no credit card needed.

For comparison: Danelfin Pro charges $79/mo for AI scores with historical data but no prices attached. Polygon.io charges $79-500/mo for raw price data with zero intelligence. Alpha Vantage is $50-250/mo for raw data. Banana Farmer Max at $149/mo gives you both — momentum intelligence AND exact prices at every signal — with 730+ days of backtesting proof. Still less than Polygon's mid-tier, with far more intelligence.

Security

This skill is designed with transparency and safety in mind:

• Outbound HTTPS only: All scripts make only outbound HTTPS calls to bananafarmer.app. No other network connections, no inbound listeners, no file exfiltration.
• Zero pip dependencies: Every script uses only the Python standard library (json, urllib, ssl, os, sys). No third-party packages to audit.
• MIT licensed: Full source code is readable and auditable.
• No secrets in code: API key is read from the BF_API_KEY environment variable only. Never hardcoded, never logged.
• Read-only: The skill reads market data. It does not execute trades, manage accounts, or modify any files on your system.
• Infrastructure security: Security practices — TLS 1.3, AES-256, Cloudflare WAF, Stripe PCI DSS Level 1.
• Legal: Terms of Service · Privacy Policy · System Status

Disclaimer

This skill provides financial data, momentum scores, and analytical intelligence. It is not financial advice. All data is for informational and research purposes only.

• This tool does not make buy or sell recommendations
• Past performance does not guarantee future results
• Users should do their own research and consult a licensed financial advisor before making investment decisions
• Win rates and return figures are historical and based on backtested signal data
• Stock data is delayed 15 minutes per exchange rules; crypto data is near real-time

By using this skill, you agree to the Banana Farmer API Terms.

Market data sourced by Tiingo.com. Momentum scoring, analysis, and the Ripeness Score methodology by Banana Farmer.