Feed Hunter: deep scraper skill, pipeline, simulator, first investigation

- 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)

projects/feed-hunter/investigate.py

@@ -0,0 +1,118 @@
+#!/usr/bin/env python3
+"""
+Investigation report generator for Feed Hunter.
+Reads triage.json and produces investigation tasks as structured prompts
+for the agent to execute.
+
+Usage:
+    python3 investigate.py <triage.json> [--output investigations/]
+
+This doesn't do the investigation itself — it generates the task list
+that the agent (Case) follows using browser/web tools.
+"""
+
+import argparse
+import json
+import os
+from datetime import datetime, timezone
+from pathlib import Path
+
+
+def generate_investigation_prompt(post):
+    """Generate an investigation prompt for the agent."""
+    author = post["author"].get("handle", "unknown")
+    text = post["text"][:500]
+    claims = post.get("claims", [])
+    links = post.get("links", [])
+    tasks = post.get("tasks", [])
+    
+    prompt = f"""## Investigation: {author}
+
+**Post:** {text}
+
+**Claims detected:**
+"""
+    for c in claims:
+        prompt += f"- [{c['type']}] {c['match']}\n"
+    
+    prompt += f"\n**Links found:**\n"
+    for l in links:
+        prompt += f"- [{l['type']}] {l['url']}\n"
+    
+    prompt += f"\n**Investigation tasks:**\n"
+    for i, t in enumerate(tasks, 1):
+        prompt += f"{i}. **{t['action']}**: {t['description']}\n"
+        prompt += f"   Method: {t['method']}\n"
+        if t.get('url'):
+            prompt += f"   URL: {t['url']}\n"
+    
+    prompt += """
+**Deliver:**
+1. Is the claim verifiable? What does the actual data show?
+2. Is there recent activity? (Last 24-48h)
+3. Is this still actionable or has the window closed?
+4. Risk assessment (1-10, where 10 is highest risk)
+5. Verdict: ACTIONABLE / EXPIRED / EXAGGERATED / SCAM / UNVERIFIABLE
+6. If ACTIONABLE: suggested paper trade parameters (asset, entry, size, stop loss, take profit)
+"""
+    return prompt
+
+
+def main():
+    parser = argparse.ArgumentParser()
+    parser.add_argument("input", help="Path to triage.json")
+    parser.add_argument("--output", help="Output directory for investigation files")
+    args = parser.parse_args()
+    
+    with open(args.input) as f:
+        data = json.load(f)
+    
+    queue = data.get("investigation_queue", [])
+    
+    if not queue:
+        print("No posts in investigation queue.")
+        return
+    
+    output_dir = args.output or os.path.join(os.path.dirname(args.input), "investigations")
+    os.makedirs(output_dir, exist_ok=True)
+    
+    timestamp = datetime.now(timezone.utc).strftime("%Y%m%d-%H%M%S")
+    
+    investigations = []
+    for i, post in enumerate(queue):
+        inv = {
+            "id": f"inv-{timestamp}-{i}",
+            "post_author": post["author"].get("handle", "unknown"),
+            "post_url": post.get("url", ""),
+            "priority": post["priority"],
+            "claims": post.get("claims", []),
+            "tasks": post.get("tasks", []),
+            "prompt": generate_investigation_prompt(post),
+            "status": "pending",
+            "result": None,
+        }
+        investigations.append(inv)
+    
+    # Save investigation batch
+    batch_file = os.path.join(output_dir, f"batch-{timestamp}.json")
+    with open(batch_file, "w") as f:
+        json.dump({
+            "batch_id": timestamp,
+            "created_at": datetime.now(timezone.utc).isoformat(),
+            "count": len(investigations),
+            "investigations": investigations,
+        }, f, indent=2)
+    
+    print(f"=== Investigation Batch: {timestamp} ===")
+    print(f"Tasks: {len(investigations)}")
+    for inv in investigations:
+        print(f"\n  [{inv['priority']}] {inv['post_author']}")
+        print(f"  Claims: {[c['type'] for c in inv['claims']]}")
+        print(f"  Tasks: {len(inv['tasks'])}")
+    
+    print(f"\nSaved to {batch_file}")
+    print(f"\nTo execute: agent reads batch file and runs each investigation prompt")
+
+
+if __name__ == "__main__":
+    main()