Install
openclaw skills install @diagnostikon/polymarket-whale-scanner-traderPolymarket Whale Scanner Trader
Scans public Polymarket leaderboards to identify top-performing whale wallets by SmartScore, then trades markets where these whales have high-conviction positions. Dynamically discovers the best traders -- no manual wallet configuration needed.
Whale Scanner Trader
This is a template. The default signal follows top Polymarket whales ranked by SmartScore -- remix it with on-chain analysis, wallet clustering, or time-weighted activity decay. The skill handles all the plumbing (leaderboard fetching, whale scoring, consensus building, trade execution, safeguards). Your agent provides the alpha.
Strategy Overview
Top Polymarket traders have an edge. The public predicting.top leaderboard ranks wallets by SmartScore -- a composite of win rate, Sharpe ratio, profit factor, and consistency. This skill dynamically discovers the best-performing traders, fetches their recent activity, and builds a consensus map of what the whales are betting on.
When multiple high-scoring whales agree on a direction AND the conviction-based signal independently confirms that direction, the skill trades. This dual-confirmation requirement filters out noise and only acts on high-confidence setups.
Signal Logic
Step 1: Fetch and Filter Leaderboard
Top traders are fetched from predicting.top/api/leaderboard and filtered by:
| Filter | Default | Purpose |
|---|---|---|
| SmartScore | >= 70 | Only follow proven traders |
| Win rate | >= 55% | Must have positive edge |
Step 2: Build Whale Consensus
For each qualifying whale, recent activity is fetched from the Polymarket data API. Net positions are extracted (buy YES vs buy NO volume per market), then aggregated across all whales:
whale_consensus[market] = {yes_votes, no_votes, total_size, whales}
Markets are ranked by total whale size -- strongest conviction first.
Step 3: Match and Confirm
For each whale consensus market:
- Find matching Simmer market via keyword/title matching
- Run
compute_signal()-- standard conviction-based sizing per CLAUDE.md - Only trade if whale direction (YES/NO) aligns with signal direction
- Check
context_ok()for flip-flop and slippage safeguards
Conviction Sizing
Standard conviction-based sizing from CLAUDE.md:
| p | conviction | size |
|---|---|---|
| 38% | 0% | $5 (floor) |
| 30% | 21% | $8 |
| 20% | 47% | $19 |
| 0% | 100% | $40 |
Remix Ideas
- On-chain clustering: Group wallets by transaction patterns to identify whale syndicates
- Time decay: Weight recent whale activity more heavily than older positions
- Size-weighted votes: A whale's $50k position counts more than a $1k position
- Contrarian mode: Fade the whales when SmartScore drops (they're losing their edge)
- Sector filtering: Only follow whales in categories they historically perform best in
Risk Parameters
| Parameter | Default | Notes |
|---|---|---|
| Max position size | $40 USDC | Per market, reached at max conviction |
| Min market volume | $3,000 | Liquidity filter |
| Max bid-ask spread | 10% | Avoid illiquid markets |
| Min days to resolution | 7 | Need time for the trade to work |
| Max open positions | 8 | Concentrated whale-aligned bets |
Installation & Setup
clawhub install polymarket-whale-scanner-trader
Requires: SIMMER_API_KEY environment variable.
Cron Schedule
Runs on demand or via automaton. Cron is set to null -- configure it in the Simmer UI when ready.
Safety & Execution Mode
The skill defaults to paper trading (venue="sim"). Real trades only execute when --live is passed explicitly.
| Scenario | Mode | Financial risk |
|---|---|---|
python trader.py | Paper (sim) | None |
| Cron / automaton | Paper (sim) | None |
python trader.py --live | Live (polymarket) | Real USDC |
The automaton cron is set to null -- it does not run on a schedule until you configure it in the Simmer UI. autostart: false means it won't start automatically on install.
Required Credentials
| Variable | Required | Notes |
|---|---|---|
SIMMER_API_KEY | Yes | Trading authority -- keep this credential private. |
Tunables (Risk Parameters)
All risk parameters are declared in clawhub.json as tunables and adjustable from the Simmer UI without code changes. They use SIMMER_-prefixed env vars so apply_skill_config() can load them securely.
| Variable | Default | Purpose |
|---|---|---|
SIMMER_MAX_POSITION | 40 | Max USDC per trade (reached at 100% conviction) |
SIMMER_MIN_TRADE | 5 | Floor for any trade (min USDC regardless of conviction) |
SIMMER_MIN_VOLUME | 3000 | Min market volume filter (USD) |
SIMMER_MAX_SPREAD | 0.10 | Max bid-ask spread (0.10 = 10%) |
SIMMER_MIN_DAYS | 7 | Min days until market resolves |
SIMMER_MAX_POSITIONS | 8 | Max concurrent open positions |
SIMMER_YES_THRESHOLD | 0.38 | Buy YES if market price <= this value |
SIMMER_NO_THRESHOLD | 0.62 | Sell NO if market price >= this value |
SIMMER_MIN_SMART_SCORE | 70 | Min SmartScore to qualify as a whale to follow |
SIMMER_MIN_WIN_RATE | 0.55 | Min win rate to qualify as a whale to follow |
SIMMER_LEADERBOARD_LIMIT | 20 | How many traders to fetch from the leaderboard |
Dependency
simmer-sdk is published on PyPI by Simmer Markets.
- PyPI: https://pypi.org/project/simmer-sdk/
- GitHub: https://github.com/SpartanLabsXyz/simmer-sdk
- Publisher: hello@simmer.markets
Review the source before providing live credentials if you require full auditability.