Polymarket 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:

text

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:

1. Find matching Simmer market via keyword/title matching
2. Run compute_signal() -- standard conviction-based sizing per CLAUDE.md
3. Only trade if whale direction (YES/NO) aligns with signal direction
4. 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

bash

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: [e-mail]

Review the source before providing live credentials if you require full auditability.