Case
8638500190
- Built deep-scraper skill (CDP-based X feed extraction) - Three-stage pipeline: scrape → triage → investigate - Paper trading simulator with position tracking - First live investigation: verified kch123 Polymarket profile ($9.3M P&L) - Opened first paper position: Seahawks Super Bowl @ 68c - Telegram alerts with inline action buttons - Portal build in progress (night shift)
282 lines
9.8 KiB
Python
282 lines
9.8 KiB
Python
#!/usr/bin/env python3
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"""
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Triage scraped X posts — identify posts with verifiable claims and links.
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Extracts structured "investigation tasks" for agent follow-up.
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Usage:
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python3 triage-posts.py <posts.json> [--output triage.json]
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"""
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import argparse
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import json
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import re
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import os
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from datetime import datetime, timezone
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# Patterns that suggest a verifiable claim
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CLAIM_PATTERNS = [
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# Performance claims
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(r'(\d+[\d.]*)\s*%\s*(win|success|profit|return|accuracy|hit rate)', 'performance_claim'),
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(r'wins?\s+(\d+[\d.]*)\s*%', 'performance_claim'),
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(r'(\d+[\d.]*)\s*%\s+of the time', 'performance_claim'),
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(r'(\d+[\d.]*)x\s+(return|profit|gain)', 'multiplier_claim'),
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# Copy/follow trading
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(r'copy(ing|cat)?\s+(trader|user|bet|position|strat)', 'copy_trading'),
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(r'follow\s+(this|my|their)\s+(trade|bet|position|strat)', 'copy_trading'),
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(r'mirror(ing)?\s+(trade|bet|position)', 'copy_trading'),
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# Arbitrage/spread
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(r'(arb|arbitrage|spread|mismatch|mispriced)', 'arbitrage_opp'),
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(r'risk[\s-]?free', 'arbitrage_opp'),
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(r'guaranteed\s+(profit|return|money)', 'arbitrage_opp'),
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# Prediction/betting
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(r'(polymarket|kalshi|manifold|prediction\s+market)', 'prediction_market'),
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(r'(odds|probability)\s+.{0,20}\s*(\d+[\d.]*)\s*%', 'odds_claim'),
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(r'(yes|no)\s+shares?\s+at\s+(\d+)', 'shares_price'),
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# Price/target claims
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(r'(target|pt|price target)\s*[:\s]+\$?\s*(\d[\d,.]*)', 'price_target'),
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(r'(entry|buy)\s*(at|zone|point)\s*[:\s]+\$?\s*(\d[\d,.]*)', 'entry_point'),
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# Airdrop/free money
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(r'(airdrop|free\s+money|free\s+tokens?|claiming)', 'airdrop'),
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(r'(step\s+\d|how\s+to\s+(get|claim|earn))', 'howto'),
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# User/account references
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(r'@\w+.*?(portfolio|track\s*record|history|performance)', 'user_reference'),
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(r'(this\s+(guy|trader|user|person|account))\s+.{0,30}(profit|win|return|made)', 'user_reference'),
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]
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# Link domains that are investigatable
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INVESTIGATABLE_DOMAINS = {
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'polymarket.com': 'prediction_market',
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'kalshi.com': 'prediction_market',
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'manifold.markets': 'prediction_market',
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'dexscreener.com': 'token_chart',
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'dextools.io': 'token_chart',
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'birdeye.so': 'token_chart',
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'coingecko.com': 'token_info',
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'coinmarketcap.com': 'token_info',
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'tradingview.com': 'chart',
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'etherscan.io': 'blockchain',
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'solscan.io': 'blockchain',
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'basescan.org': 'blockchain',
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'github.com': 'code_repo',
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'docs.google.com': 'document',
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'notion.so': 'document',
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'medium.com': 'article',
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'substack.com': 'article',
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'youtube.com': 'video',
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'youtu.be': 'video',
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}
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def extract_claims(text):
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"""Extract verifiable claims from post text."""
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claims = []
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for pattern, claim_type in CLAIM_PATTERNS:
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matches = re.finditer(pattern, text, re.IGNORECASE)
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for m in matches:
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claims.append({
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'type': claim_type,
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'match': m.group(0),
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'span': [m.start(), m.end()],
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})
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return claims
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def classify_links(links):
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"""Classify links by investigatable domain."""
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classified = []
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for link in links:
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url = link.get('url', '')
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link_type = 'unknown'
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for domain, dtype in INVESTIGATABLE_DOMAINS.items():
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if domain in url:
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link_type = dtype
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break
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classified.append({
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'url': url,
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'text': link.get('text', ''),
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'type': link_type,
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})
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return classified
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def triage_post(post):
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"""Analyze a single post for investigation potential."""
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text = post.get('text', '') or ''
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# Extract claims
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claims = extract_claims(text)
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# Classify links
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all_links = (post.get('links', []) or [])
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card = post.get('card') or {}
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if card.get('url'):
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all_links.append({'url': card['url'], 'text': card.get('title', '')})
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classified_links = classify_links(all_links)
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investigatable_links = [l for l in classified_links if l['type'] != 'unknown']
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# Has the post got something worth investigating?
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has_claims = len(claims) > 0
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has_links = len(investigatable_links) > 0
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has_any_links = len(classified_links) > 0
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# Priority scoring
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priority = 0
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if has_claims:
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priority += 2
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# Performance claims are highest priority
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if any(c['type'] in ('performance_claim', 'multiplier_claim') for c in claims):
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priority += 2
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if any(c['type'] in ('copy_trading', 'arbitrage_opp') for c in claims):
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priority += 1
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if has_links:
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priority += 2
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if any(l['type'] == 'prediction_market' for l in investigatable_links):
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priority += 2
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if any(l['type'] in ('token_chart', 'blockchain') for l in investigatable_links):
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priority += 1
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if has_any_links and not has_links:
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priority += 1
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# Build investigation tasks
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tasks = []
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for claim in claims:
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if claim['type'] == 'performance_claim':
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tasks.append({
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'action': 'verify_performance',
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'description': f"Verify claim: {claim['match']}",
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'method': 'Check linked profile/data for actual track record',
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})
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elif claim['type'] == 'copy_trading':
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tasks.append({
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'action': 'verify_trader',
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'description': f"Verify trader referenced: {claim['match']}",
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'method': 'Check trader profile, recent bets/trades, actual P&L',
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})
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elif claim['type'] == 'arbitrage_opp':
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tasks.append({
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'action': 'verify_arb',
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'description': f"Verify opportunity: {claim['match']}",
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'method': 'Check if spread/mismatch still exists, calculate actual risk',
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})
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elif claim['type'] in ('odds_claim', 'shares_price', 'prediction_market'):
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tasks.append({
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'action': 'check_market',
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'description': f"Check prediction market: {claim['match']}",
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'method': 'Verify current odds, volume, resolution criteria',
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})
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elif claim['type'] == 'price_target':
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tasks.append({
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'action': 'check_price',
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'description': f"Verify price claim: {claim['match']}",
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'method': 'Check current price vs target, chart pattern',
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})
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elif claim['type'] == 'airdrop':
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tasks.append({
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'action': 'verify_airdrop',
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'description': f"Check airdrop legitimacy: {claim['match']}",
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'method': 'Verify project, check for scam signals, confirm eligibility',
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})
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for link in investigatable_links:
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tasks.append({
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'action': f'browse_{link["type"]}',
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'description': f'Follow and analyze: {link["url"]}',
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'url': link['url'],
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'method': f'Browse to {link["type"]} link, extract current data',
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})
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# For unknown links that might be interesting
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for link in classified_links:
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if link['type'] == 'unknown' and link['url'].startswith('http') and 'x.com' not in link['url']:
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tasks.append({
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'action': 'browse_unknown',
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'description': f'Check external link: {link["url"]}',
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'url': link['url'],
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'method': 'Browse to link, determine if relevant',
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})
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return {
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'author': post.get('author', {}),
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'text': text,
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'url': post.get('url', ''),
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'timestamp': post.get('timestamp'),
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'metrics': post.get('metrics', {}),
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'claims': claims,
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'links': classified_links,
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'investigatable_links': investigatable_links,
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'priority': priority,
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'tasks': tasks,
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'worth_investigating': priority >= 2,
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}
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def main():
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parser = argparse.ArgumentParser(description="Triage X posts for investigation")
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parser.add_argument("input", help="Path to posts.json")
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parser.add_argument("--output", help="Output file")
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parser.add_argument("--min-priority", type=int, default=2, help="Min priority to include")
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args = parser.parse_args()
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with open(args.input) as f:
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data = json.load(f)
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posts = data.get('posts', [])
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print(f"Triaging {len(posts)} posts...")
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triaged = []
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for post in posts:
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result = triage_post(post)
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triaged.append(result)
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# Sort by priority
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triaged.sort(key=lambda x: x['priority'], reverse=True)
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# Filter
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worth = [t for t in triaged if t['priority'] >= args.min_priority]
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output = {
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'triaged_at': datetime.now(timezone.utc).isoformat(),
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'total_posts': len(posts),
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'worth_investigating': len(worth),
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'posts': triaged,
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'investigation_queue': worth,
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}
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output_path = args.output or os.path.join(os.path.dirname(args.input), 'triage.json')
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with open(output_path, 'w') as f:
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json.dump(output, f, indent=2)
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# Print summary
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print(f"\n=== Triage Summary ===")
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print(f"Total: {len(posts)} | Worth investigating: {len(worth)}")
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if worth:
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print(f"\n=== Investigation Queue ===")
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for t in worth:
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author = t['author'].get('handle', '?')
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claims = [c['type'] for c in t['claims']]
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links = [l['type'] for l in t['investigatable_links']]
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print(f"\n [{t['priority']}] {author}")
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print(f" {t['text'][:150]}...")
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if claims:
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print(f" Claims: {', '.join(claims)}")
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if links:
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print(f" Links: {', '.join(links)}")
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print(f" Tasks: {len(t['tasks'])}")
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else:
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print("\nNo posts met the investigation threshold.")
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print(f"\nSaved to {output_path}")
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if __name__ == "__main__":
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main()
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