polymarket-ai-divergenceFind markets where Simmer's AI consensus diverges from the real market price, then trade on the mispriced side using Kelly sizing. Scans for divergence, chec...
Install via ClawdBot CLI:
clawdbot install adlai88/polymarket-ai-divergenceFind markets where Simmer's AI consensus diverges from the real market price, then trade the edge.
This is a template. The default logic trades when AI divergence exceeds 2% on zero-fee markets, using Kelly sizing capped at 25%. Remix it with different edge thresholds, sizing strategies, or additional filters (e.g., only trade markets resolving within 7 days). The skill handles plumbing (divergence scanning, fee checks, safeguards, execution). Your agent provides the alpha.
# Scan only (dry run, no trades)
python ai_divergence.py
# Scan + execute trades
python ai_divergence.py --live
# Only show bullish divergences
python ai_divergence.py --bullish
# Only >15% divergence
python ai_divergence.py --min 15
# JSON output
python ai_divergence.py --json
# Cron mode (quiet, trades only)
python ai_divergence.py --live --quiet
# Show config
python ai_divergence.py --config
# Update config
python ai_divergence.py --set max_bet_usd=10
| Key | Env Var | Default | Description |
|-----|---------|---------|-------------|
| min_divergence | SIMMER_DIVERGENCE_MIN | 5.0 | Min divergence % for scanner display |
| min_edge | SIMMER_DIVERGENCE_MIN_EDGE | 0.02 | Min divergence to trade (2%) |
| max_bet_usd | SIMMER_DIVERGENCE_MAX_BET | 5.0 | Max bet per trade |
| max_trades_per_run | SIMMER_DIVERGENCE_MAX_TRADES | 3 | Max trades per cycle |
| kelly_cap | SIMMER_DIVERGENCE_KELLY_CAP | 0.25 | Kelly fraction cap |
| daily_budget | SIMMER_DIVERGENCE_DAILY_BUDGET | 25.0 | Daily spend limit |
| default_direction | SIMMER_DIVERGENCE_DIRECTION | (both) | Filter: "bullish" or "bearish" |
Update via CLI: python ai_divergence.py --set max_bet_usd=10
Each imported market has two prices:
current_probability) ā Simmer's AI consensus price, derived from multi-model ensemble forecastingexternal_price_yes) ā Real market price on Polymarket/Kalshidivergence = AI consensus - external price
When divergence > 0: AI thinks the market is underpriced ā buy YES
When divergence < 0: AI thinks the market is overpriced ā buy NO
Position size uses the Kelly criterion:
kelly_fraction = edge / (1 - price)
position_size = kelly_fraction * max_bet_usd
Capped at kelly_cap (default 25%) to limit risk.
75% of Polymarket markets have 0% fees. The remaining 25% charge 10% (short-duration crypto/sports). This skill only trades zero-fee markets to avoid fee drag eroding the edge.
GET /api/sdk/markets/opportunities ā Divergence-ranked market listGET /api/sdk/context/{market_id} ā Fee rate and safeguards per marketPOST /api/sdk/trade ā Trade execution (via SDK client)GET /api/sdk/positions ā Current portfolio positions"No markets above min edge threshold"
ā All divergences are below the min_edge setting. Lower it with --set min_edge=0.01 or wait for larger divergences.
"Daily budget exhausted"
ā The skill has hit its daily spend limit. Adjust with --set daily_budget=50.
All markets skipped for fees
ā Only zero-fee markets are traded. If all available divergence opportunities have fees, no trades execute. This is by design.
"context fetch failed"
ā The SDK context endpoint is rate-limited (18 req/min). If running frequently, reduce max_trades_per_run.
Generated Mar 1, 2026
A hedge fund or proprietary trading firm uses this skill to automate arbitrage opportunities between AI predictions and market prices on prediction markets. It integrates with their existing risk management systems to execute trades when divergence exceeds thresholds, leveraging Kelly sizing for optimal bet sizing while adhering to daily budget constraints.
An investment manager focuses on political or sports events, deploying this skill to capitalize on mispricings identified by AI consensus. By filtering for zero-fee markets and using safeguards like flip-flop detection, they manage risk while seeking alpha in short-term market inefficiencies around event resolutions.
A crypto trader runs this skill on a cloud server to automatically scan and trade on Polymarket for cryptocurrency-related predictions. It uses the skill's configuration to set minimum edge thresholds and direction filters, optimizing for high-frequency opportunities in volatile markets while avoiding fee drag.
A data analytics company employs this skill to gather insights on AI vs. market price divergences across various topics. They run it in dry-run mode to collect JSON output for backtesting and model validation, helping refine their own forecasting algorithms without executing live trades.
A financial education provider uses this skill as a hands-on demo in courses on algorithmic trading and Kelly criterion. Students configure parameters like min_edge and kelly_cap to simulate trades, learning about risk management and market efficiency in a controlled, real-world context.
Offer this skill as part of a SaaS platform where users pay a monthly fee to access automated trading on prediction markets. Revenue comes from subscription tiers based on features like higher trade limits or advanced analytics, with the skill handling divergence scanning and execution.
Operate a fund that uses this skill to trade on AI divergences, charging investors a management fee plus a performance fee on profits. The skill's safeguards and Kelly sizing help manage risk, while the daily budget and max trades per run control exposure to maximize returns.
License this skill to banks or fintech companies as a customizable trading module. Revenue is generated through licensing fees and support contracts, with integration tips focusing on API key setup and cron job scheduling for automated runs in their existing infrastructure.
š¬ Integration Tip
Ensure the SIMMER_API_KEY is securely stored as an environment variable and install the simmer-sdk via pip before running the skill to avoid dependency issues.
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