Sync portfolio positions from Polymarket, Kalshi, and Manifold
55
69%
Does it follow best practices?
Run evals on this skill
Adds up to 20 points to the overall score
Low
Low-risk findings worth noting
Fix and improve this skill with Tessl
tessl review fix ./src/skills/bundled/portfolio-sync/SKILL.mdReal methods to fetch and sync positions from each prediction market platform.
Polymarket positions are held as ERC-1155 tokens on Polygon. Query on-chain balances.
import os
import requests
WALLET = os.getenv("POLY_FUNDER_ADDRESS")
CTF_CONTRACT = "0x4D97DCd97eC945f40cF65F87097ACe5EA0476045" # Conditional Token Framework
def get_polymarket_positions(token_ids: list[str]) -> dict:
"""
Get balances for specific token IDs
Args:
token_ids: List of token IDs to check (from market data)
Returns:
Dict of token_id -> balance in shares
"""
positions = {}
for token_id in token_ids:
token_int = int(token_id)
# ERC-1155 balanceOf call
data = f"0x00fdd58e000000000000000000000000{WALLET[2:].lower()}{token_int:064x}"
r = requests.post("https://polygon-rpc.com/", json={
"jsonrpc": "2.0",
"method": "eth_call",
"params": [{"to": CTF_CONTRACT, "data": data}, "latest"],
"id": 1
})
result = r.json().get("result", "0x0")
balance = int(result, 16) / 1e6 # Raw to shares
if balance > 0:
positions[token_id] = balance
return positions
# Example: Check positions for BTC 15-min market
btc_tokens = [
"21742633143463906290569050155826241533067272736897614950488156847949938836455", # YES
"48331043336612883890938759509493159234755048973500640148014422747788308965745" # NO
]
positions = get_polymarket_positions(btc_tokens)
for token_id, balance in positions.items():
print(f"Token {token_id[:20]}...: {balance} shares")def get_all_polymarket_positions(wallet: str):
"""Get all positions for a wallet via Gamma API"""
url = f"https://gamma-api.polymarket.com/positions?user={wallet.lower()}"
r = requests.get(url)
if r.status_code != 200:
return []
positions = r.json()
result = []
for p in positions:
result.append({
"market_id": p.get("conditionId"),
"market_question": p.get("title", "Unknown"),
"token_id": p.get("tokenId"),
"outcome": p.get("outcome"),
"size": float(p.get("size", 0)),
"avg_price": float(p.get("avgPrice", 0)),
"current_price": float(p.get("currentPrice", 0)),
"pnl": float(p.get("pnl", 0)),
"value": float(p.get("value", 0))
})
return result
positions = get_all_polymarket_positions(WALLET)
for p in positions:
print(f"{p['market_question'][:40]}")
print(f" {p['outcome']}: {p['size']} shares @ {p['avg_price']:.2f} -> {p['current_price']:.2f}")
print(f" PnL: ${p['pnl']:.2f}")def get_usdc_balance(wallet: str) -> float:
"""Get USDC balance on Polygon"""
USDC = "0x2791Bca1f2de4661ED88A30C99A7a9449Aa84174" # USDC on Polygon
# ERC-20 balanceOf
data = f"0x70a08231000000000000000000000000{wallet[2:].lower()}"
r = requests.post("https://polygon-rpc.com/", json={
"jsonrpc": "2.0",
"method": "eth_call",
"params": [{"to": USDC, "data": data}, "latest"],
"id": 1
})
result = r.json().get("result", "0x0")
balance = int(result, 16) / 1e6 # USDC has 6 decimals
return balance
usdc = get_usdc_balance(WALLET)
print(f"USDC Balance: ${usdc:.2f}")import requests
import time
BASE_URL = "https://trading-api.kalshi.com/trade-api/v2"
class KalshiSync:
def __init__(self, email: str, password: str):
self.email = email
self.password = password
self.token = None
self.token_expiry = 0
def _auth(self):
if time.time() > self.token_expiry - 60:
r = requests.post(f"{BASE_URL}/login", json={
"email": self.email,
"password": self.password
})
r.raise_for_status()
self.token = r.json()["token"]
self.token_expiry = time.time() + 29 * 60
def _headers(self):
self._auth()
return {"Authorization": f"Bearer {self.token}"}
def get_positions(self):
"""Get all Kalshi positions"""
r = requests.get(f"{BASE_URL}/portfolio/positions", headers=self._headers())
r.raise_for_status()
positions = []
for p in r.json().get("market_positions", []):
# Get market details
market = requests.get(
f"{BASE_URL}/markets/{p['ticker']}",
headers=self._headers()
).json().get("market", {})
positions.append({
"market_id": p["ticker"],
"market_question": market.get("title", p["ticker"]),
"side": "YES" if p.get("position", 0) > 0 else "NO",
"size": abs(p.get("position", 0)),
"avg_price": p.get("average_price", 0) / 100,
"current_price": market.get("yes_bid", 50) / 100,
"value": abs(p.get("position", 0)) * market.get("yes_bid", 50) / 100,
"pnl": p.get("realized_pnl", 0) / 100
})
return positions
def get_balance(self):
"""Get Kalshi balance"""
r = requests.get(f"{BASE_URL}/portfolio/balance", headers=self._headers())
r.raise_for_status()
data = r.json()
return {
"available": data.get("balance", 0) / 100,
"portfolio_value": data.get("portfolio_value", 0) / 100
}
# Usage
sync = KalshiSync(os.getenv("KALSHI_EMAIL"), os.getenv("KALSHI_PASSWORD"))
positions = sync.get_positions()
for p in positions:
print(f"{p['market_question'][:40]}")
print(f" {p['side']}: {p['size']} @ {p['avg_price']:.2f} -> {p['current_price']:.2f}")
balance = sync.get_balance()
print(f"\nAvailable: ${balance['available']:.2f}")
print(f"Portfolio: ${balance['portfolio_value']:.2f}")import requests
API_URL = "https://api.manifold.markets/v0"
API_KEY = os.getenv("MANIFOLD_API_KEY")
def get_manifold_positions():
"""Get all Manifold positions"""
headers = {"Authorization": f"Key {API_KEY}"}
# Get user profile
r = requests.get(f"{API_URL}/me", headers=headers)
r.raise_for_status()
user = r.json()
user_id = user["id"]
balance = user.get("balance", 0)
# Get all bets
r = requests.get(f"{API_URL}/bets", headers=headers, params={"userId": user_id, "limit": 1000})
bets = r.json()
# Aggregate positions by market
markets = {}
for bet in bets:
if bet.get("isSold") or bet.get("isCancelled"):
continue
mid = bet["contractId"]
if mid not in markets:
markets[mid] = {
"yes_shares": 0,
"no_shares": 0,
"invested": 0,
"question": bet.get("contractQuestion", "Unknown")
}
if bet["outcome"] == "YES":
markets[mid]["yes_shares"] += bet.get("shares", 0)
else:
markets[mid]["no_shares"] += bet.get("shares", 0)
markets[mid]["invested"] += bet["amount"]
# Get current prices
positions = []
for mid, data in markets.items():
if data["yes_shares"] == 0 and data["no_shares"] == 0:
continue
# Fetch current market price
r = requests.get(f"{API_URL}/market/{mid}")
if r.status_code == 200:
market = r.json()
prob = market.get("probability", 0.5)
yes_value = data["yes_shares"] * prob
no_value = data["no_shares"] * (1 - prob)
total_value = yes_value + no_value
pnl = total_value - data["invested"]
positions.append({
"market_id": mid,
"market_question": data["question"],
"yes_shares": data["yes_shares"],
"no_shares": data["no_shares"],
"invested": data["invested"],
"current_value": total_value,
"probability": prob,
"pnl": pnl,
"url": market.get("url", "")
})
return positions, balance
positions, balance = get_manifold_positions()
print(f"Mana Balance: {balance}")
for p in positions:
print(f"\n{p['market_question'][:50]}")
print(f" YES: {p['yes_shares']:.1f} shares, NO: {p['no_shares']:.1f} shares")
print(f" Value: {p['current_value']:.0f}M, PnL: {p['pnl']:+.0f}M")#!/usr/bin/env python3
"""
Sync portfolio from all prediction markets
"""
import os
from dataclasses import dataclass
from typing import List
@dataclass
class Position:
platform: str
market_id: str
market_question: str
side: str
size: float
avg_price: float
current_price: float
value: float
pnl: float
pnl_pct: float
def sync_all_portfolios() -> List[Position]:
"""Sync positions from all platforms"""
all_positions = []
# Polymarket
if os.getenv("POLY_FUNDER_ADDRESS"):
poly_positions = get_all_polymarket_positions(os.getenv("POLY_FUNDER_ADDRESS"))
for p in poly_positions:
avg = p["avg_price"] or 0.01
pnl_pct = ((p["current_price"] - avg) / avg * 100) if avg > 0 else 0
all_positions.append(Position(
platform="polymarket",
market_id=p["market_id"],
market_question=p["market_question"],
side=p["outcome"],
size=p["size"],
avg_price=avg,
current_price=p["current_price"],
value=p["value"],
pnl=p["pnl"],
pnl_pct=pnl_pct
))
# Kalshi
if os.getenv("KALSHI_EMAIL"):
kalshi = KalshiSync(os.getenv("KALSHI_EMAIL"), os.getenv("KALSHI_PASSWORD"))
kalshi_positions = kalshi.get_positions()
for p in kalshi_positions:
avg = p["avg_price"] or 0.01
pnl_pct = ((p["current_price"] - avg) / avg * 100) if avg > 0 else 0
all_positions.append(Position(
platform="kalshi",
market_id=p["market_id"],
market_question=p["market_question"],
side=p["side"],
size=p["size"],
avg_price=avg,
current_price=p["current_price"],
value=p["value"],
pnl=p["pnl"],
pnl_pct=pnl_pct
))
# Manifold
if os.getenv("MANIFOLD_API_KEY"):
mani_positions, _ = get_manifold_positions()
for p in mani_positions:
invested = p["invested"] or 1
pnl_pct = (p["pnl"] / invested * 100) if invested > 0 else 0
# Add YES position
if p["yes_shares"] > 0:
all_positions.append(Position(
platform="manifold",
market_id=p["market_id"],
market_question=p["market_question"],
side="YES",
size=p["yes_shares"],
avg_price=0, # Manifold doesn't track this
current_price=p["probability"],
value=p["yes_shares"] * p["probability"],
pnl=p["pnl"] / 2, # Split PnL
pnl_pct=pnl_pct
))
# Add NO position
if p["no_shares"] > 0:
all_positions.append(Position(
platform="manifold",
market_id=p["market_id"],
market_question=p["market_question"],
side="NO",
size=p["no_shares"],
avg_price=0,
current_price=1 - p["probability"],
value=p["no_shares"] * (1 - p["probability"]),
pnl=p["pnl"] / 2,
pnl_pct=pnl_pct
))
return all_positions
# Run sync
positions = sync_all_portfolios()
# Print summary
total_value = sum(p.value for p in positions)
total_pnl = sum(p.pnl for p in positions)
print(f"\n{'='*60}")
print(f"PORTFOLIO SUMMARY")
print(f"{'='*60}")
print(f"Total Value: ${total_value:.2f}")
print(f"Total PnL: ${total_pnl:+.2f}")
print(f"{'='*60}")
for platform in ["polymarket", "kalshi", "manifold"]:
plat_positions = [p for p in positions if p.platform == platform]
if plat_positions:
plat_value = sum(p.value for p in plat_positions)
plat_pnl = sum(p.pnl for p in plat_positions)
print(f"\n{platform.upper()}: ${plat_value:.2f} (PnL: ${plat_pnl:+.2f})")
for p in plat_positions:
print(f" {p.market_question[:35]}")
print(f" {p.side}: {p.size:.1f} @ {p.avg_price:.2f} -> {p.current_price:.2f}")
print(f" Value: ${p.value:.2f}, PnL: ${p.pnl:+.2f} ({p.pnl_pct:+.1f}%)")#!/usr/bin/env python3
"""
Run every hour to sync positions to database
"""
import sqlite3
from datetime import datetime
def sync_to_db():
"""Sync all positions to SQLite"""
conn = sqlite3.connect("~/.clodds/clodds.db")
positions = sync_all_portfolios()
for p in positions:
conn.execute("""
INSERT OR REPLACE INTO positions
(platform, market_id, market_question, side, size, avg_price, current_price, value, pnl, updated_at)
VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
""", (
p.platform, p.market_id, p.market_question, p.side,
p.size, p.avg_price, p.current_price, p.value, p.pnl,
datetime.now().isoformat()
))
conn.commit()
conn.close()
print(f"Synced {len(positions)} positions at {datetime.now()}")
if __name__ == "__main__":
sync_to_db()Add to crontab:
# Sync every hour
0 * * * * cd /path/to/clodds && python3 -c "from skills.portfolio_sync import sync_to_db; sync_to_db()"alsk1992/CloddsBot
c930628
If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.