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PRIVATE FILTERS ───────────────────────────────────────── VERSION 1.2 // 2026-04-02 CHANGELOG v1.2 2026-04-02 server-side auth, localStorage 30d, agent prompts added v1.1 2026-03-28 geo filters patched (FOMO v4) v1.0 2026-03-20 initial release
FOMO Scanner — Wallet Tiers & Signal Thresholds
FOMO SCANNER v4
4-tier smart wallet system. Auto-promotion based on track record. Cluster detection for coordinated whale activity.
# Smart wallet tiers — signal weight multipliers TIER_1 (Mega Whales) weight: 3.0x Fredi9999 # PnL: $16.6M RN1 # PnL: $5.2M SeriouslySirius # PnL: $3.6M GCottrell93 # PnL: $3.4M aenews # PnL: $3.3M ImJustKen # PnL: $2.8M (geo NO = signal, YES = noise) YatSen # PnL: $2.3M bama124 # PnL: $1.4M TIER_2 (Kings) weight: 2.0x 50+ wallets # $500K-$2M PnL range TIER_3 (Diamonds) weight: 1.5x BGV, Cutnpaste, Erasmus, Eridpnc, Hans, JJo, Logan TIER_4 (Research) weight: 1.25x GreekGamblerPM # Trump sniping, bond markets Jos # resolution criteria arbitrage # Auto-promotion thresholds AUTO_PROMOTE_MIN_REP = 0.80 # 80% correct predictions AUTO_PROMOTE_MIN_TOTAL = 15 # alerts before eligible AUTO_PROMOTE_MIN_GOOD = 10 # correct calls minimum # Signal thresholds NET_BUY_STRONG = $50,000 NET_BUY_GOOD = $20,000 NET_BUY_MODERATE = $5,000 SPIKE_LARGE = 15% SPIKE_GOOD = 10% SPIKE_MODERATE = 5% # Cluster detection (coordinated trading) CLUSTER_WINDOW = 60s # time window CLUSTER_TOLERANCE = 10% # price tolerance MIN_CLUSTER_SIZE = 4 # min simultaneous trades # Manipulation detection VOL_LIQ_EXTREME = 500 # volume-to-liquidity ratio ROUND_TRIP_HIGH = 0.5 # 50% position bought back CHURN_SUSPICIOUS = 5 # rapid in/out trades SPREAD_WIDE = 0.10 # 10% bid-ask
→ repo: github.com/0xarise/fomo-scanner | file: config.py | updated: 2026-04-02
// agent setup prompt
# ══════════════════════════════════════════════════════ # FOMO SCANNER v4 — Agent Setup Prompt # Paste into Claude Code, Codex, or any coding agent. # Fill YOUR_* placeholders before sending. # ══════════════════════════════════════════════════════ Set up 0xarise FOMO Scanner v4 on my machine. Repo: https://github.com/0xarise/fomo-scanner MY CREDENTIALS (fill in): POLY_API_KEY=[your Polymarket API key] TG_BOT_TOKEN=[your Telegram bot token] TG_CHAT_ID=[your Telegram channel/group ID] CONFIG TO APPLY (config.py): TIER_1_WALLETS = [Fredi9999, RN1, SeriouslySirius, GCottrell93, aenews, ImJustKen, YatSen, bama124] # note: ImJustKen — geo NO positions = signal, geo YES = noise. Weight accordingly. TIER_1_WEIGHT = 3.0 TIER_3_WALLETS = [BGV, Cutnpaste, Erasmus, Eridpnc, Hans, JJo, Logan] TIER_4_WALLETS = [GreekGamblerPM, Jos] NET_BUY_STRONG = 50000 NET_BUY_GOOD = 20000 NET_BUY_MODERATE = 5000 SPIKE_LARGE = 0.15 SPIKE_GOOD = 0.10 SPIKE_MODERATE = 0.05 CLUSTER_WINDOW = 60 CLUSTER_TOLERANCE = 0.10 MIN_CLUSTER_SIZE = 4 AUTO_PROMOTE_MIN_REP = 0.80 AUTO_PROMOTE_MIN_TOTAL = 15 AUTO_PROMOTE_MIN_GOOD = 10 VOL_LIQ_EXTREME = 500 ROUND_TRIP_HIGH = 0.5 CHURN_SUSPICIOUS = 5 TASKS: 1. Clone repo to ~/fomo-scanner/ (or preferred path) 2. python -m venv venv && source venv/bin/activate 3. pip install -r requirements.txt 4. Create .env with POLY_API_KEY, TG_BOT_TOKEN, TG_CHAT_ID from above 5. Apply all config values above to config.py 6. Test: python -u fomo_scanner.py --dry-run Expected: scanner initializes, 0 errors, exits cleanly 7. Launch in tmux: tmux new-session -d -s fomo tmux send-keys -t fomo "PYTHONPATH=. python -u fomo_scanner.py" Enter 8. Verify: tmux capture-pane -t fomo -p | tail -20 Expected: "FOMO Scanner v4 running..." with scan cycle output
Whale Scanner — Tracking Config
WHALE SCANNER
Tracks top 250 leaderboard wallets + 18 manually curated seed wallets. Alerts on $5K+ position changes.
# Wallet discovery LEADERBOARD_PAGES = 4 # top 200 traders fetched SEED_WALLETS = 18 # manually tracked TRACKED_SIMULTANEOUSLY = 50 # Alert thresholds MIN_NON_SPORTS_PNL = $500,000 # min PnL to track MAX_SPORTS_RATIO = 0.5 # max 50% in sports MIN_POSITION_USD = $5,000 # ignore smaller MIN_DELTA_USD = $5,000 # alert threshold # Scan config SCAN_INTERVAL = 300s # 5 minutes REQ_DELAY = 1.0s # between API calls
→ repo: github.com/0xarise/whale-scanner | file: config.py | updated: 2026-04-02
// agent setup prompt
# ══════════════════════════════════════════════════════ # WHALE SCANNER — Agent Setup Prompt # Paste into Claude Code, Codex, or any coding agent. # Fill YOUR_* placeholders before sending. # ══════════════════════════════════════════════════════ Set up 0xarise Whale Scanner on my machine. Repo: https://github.com/0xarise/whale-scanner MY CREDENTIALS (fill in): POLY_API_KEY=[your Polymarket API key] TG_BOT_TOKEN=[your Telegram bot token] TG_CHAT_ID=[your Telegram channel/group ID] CONFIG TO APPLY (config.py): LEADERBOARD_PAGES = 4 # top ~200 traders SEED_WALLETS_COUNT = 18 # manually tracked (populated from repo) TRACKED_SIMULTANEOUSLY = 50 MIN_NON_SPORTS_PNL = 500000 # $500K minimum PnL to qualify MAX_SPORTS_RATIO = 0.5 # ignore wallets >50% in sports MIN_POSITION_USD = 5000 MIN_DELTA_USD = 5000 # alert threshold SCAN_INTERVAL = 300 # seconds (5 min) REQ_DELAY = 1.0 # between API calls TASKS: 1. Clone repo to ~/whale-scanner/ 2. python -m venv venv && source venv/bin/activate 3. pip install -r requirements.txt 4. Create .env with POLY_API_KEY, TG_BOT_TOKEN, TG_CHAT_ID from above 5. Apply config values above to config.py 6. Test: python -u whale_scanner.py --dry-run Expected: leaderboard fetched, wallets loaded, 0 errors 7. Launch in tmux: tmux new-session -d -s whale-tracker tmux send-keys -t whale-tracker "PYTHONPATH=. python -u whale_scanner.py" Enter 8. Verify: tmux capture-pane -t whale-tracker -p | tail -20 Expected: scan cycle with wallet count and next scan timestamp
Contrarian AI — Entry Setup & Scoring
CONTRARIAN AI SCANNER
Finds markets where 89-95%+ consensus might be wrong. Two tiers: T1 auto-alerts, T2 review list. Priority scoring with catalyst detection.
# Contrarian entry setup MIN_DOMINANT_PRICE = 0.89 # 89%+ on one side MIN_MODEL_EDGE = 0.05 # 5% minimum edge MIN_EV_PER_USD = 0.05 # 5 cents per dollar risked MIN_VOLUME_USD = $2,500 MAX_SPREAD = 0.10 # Tier 1 — auto-alert (high confidence) T1_MIN_DOMINANT = 95% T1_MAX_HOURS = 72 T1_MIN_VOLUME = $5,000 T1_MIN_CATALYST = 0.50 # Tier 2 — review list (moderate setup) T2_MIN_DOMINANT = 89% T2_MAX_HOURS = 336 # 14 days T2_MIN_VOLUME = $500 # Priority scoring SCORE = edge*100 + min(ev,3)*12 + (dominant-0.90)*35 + min(volume/50000,1.2)*8 + catalyst*25 - risk_flags*6 # Catalyst categories (weighted) EARNINGS: 8-10 # eps, revenue, guidance, beat/miss M_AND_A: 10 # acquisition, merger, buyout, takeover MACRO: 10 # CPI, PPI, FOMC, fed, inflation, jobs GEOPOLITICAL: 10 # war, strike, invasion, ceasefire REGULATION: 8 # SEC, DOJ, antitrust, approval, ban TECH: 5-10 # OpenAI, Anthropic, Apple, launches # Risk flags (each = -6 score) WIDE_SPREAD: >6% THIN_LIQUIDITY: <$250 LONG_HORIZON: >7 days WEAK_CATALYST: <35% # Dedup & alert management MAX_ALERTS_PER_CYCLE = 7 DEDUP_HOURS = 8 DEDUP_COOLDOWN_DAYS = 7
→ repo: github.com/0xarise/contrarian-scanner | file: config.py | updated: 2026-04-02
// agent setup prompt
# ══════════════════════════════════════════════════════ # CONTRARIAN AI SCANNER — Agent Setup Prompt # Paste into Claude Code, Codex, or any coding agent. # Fill YOUR_* placeholders before sending. # ══════════════════════════════════════════════════════ Set up 0xarise Contrarian AI Scanner on my machine. Repo: https://github.com/0xarise/contrarian-scanner MY CREDENTIALS (fill in): POLY_API_KEY=[your Polymarket API key] TG_BOT_TOKEN=[your Telegram bot token] TG_CHAT_ID=[your Telegram channel/group ID] ANTHROPIC_API_KEY=[your Anthropic API key — used for AI scoring] CONFIG TO APPLY (config.py): MIN_DOMINANT_PRICE = 0.89 MIN_MODEL_EDGE = 0.05 MIN_EV_PER_USD = 0.05 MIN_VOLUME_USD = 2500 MAX_SPREAD = 0.10 T1_MIN_DOMINANT = 0.95 T1_MAX_HOURS = 72 T1_MIN_VOLUME = 5000 T1_MIN_CATALYST = 0.50 T2_MIN_DOMINANT = 0.89 T2_MAX_HOURS = 336 T2_MIN_VOLUME = 500 MAX_ALERTS_PER_CYCLE = 7 DEDUP_HOURS = 8 DEDUP_COOLDOWN_DAYS = 7 # Score formula: edge*100 + min(ev,3)*12 + (dominant-0.90)*35 # + min(volume/50000,1.2)*8 + catalyst*25 - risk_flags*6 # T1 alerts fire automatically. T2 goes to review list — check manually. TASKS: 1. Clone repo to ~/contrarian-scanner/ 2. python -m venv venv && source venv/bin/activate 3. pip install -r requirements.txt 4. Create .env with all credentials above 5. Apply config values to config.py 6. Test: python -u contrarian_scanner.py --dry-run Expected: markets scanned, scoring runs, 0 errors, no TG messages sent 7. Launch in tmux: tmux new-session -d -s contrarian tmux send-keys -t contrarian "PYTHONPATH=. python -u contrarian_scanner.py" Enter 8. Verify: tmux capture-pane -t contrarian -p | tail -20 Expected: cycle output with T1/T2 counts and next scan time
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