Polymarket Whale Contrarian Trader

v1.0.6

Detects smart money divergence where top-performing whale wallets take positions opposite to retail consensus. When markets are at probability extremes but w...

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by@diagnostikon

OpenClaw Prompt Flow

Install with OpenClaw

Best for remote or guided setup. Copy the exact prompt, then paste it into OpenClaw for diagnostikon/polymarket-whale-contrarian-trader.

Previewing Install & Setup.

Prompt PreviewInstall & Setup

Install the skill "Polymarket Whale Contrarian Trader" (diagnostikon/polymarket-whale-contrarian-trader) from ClawHub.
Skill page: https://clawhub.ai/diagnostikon/polymarket-whale-contrarian-trader
Keep the work scoped to this skill only.
After install, inspect the skill metadata and help me finish setup.
Use only the metadata you can verify from ClawHub; do not invent missing requirements.
Ask before making any broader environment changes.

Command Line

CLI Commands

Use the direct CLI path if you want to install manually and keep every step visible.

OpenClaw CLI

Bare skill slug

openclaw skills install polymarket-whale-contrarian-trader

ClawHub CLI

Package manager switcher

npx clawhub@latest install polymarket-whale-contrarian-trader

Security Scan

Capability signals

CryptoRequires walletRequires sensitive credentials

These labels describe what authority the skill may exercise. They are separate from suspicious or malicious moderation verdicts.

VirusTotal

Benign

View report →

OpenClaw

Benign

medium confidence

✓

Purpose & Capability

Name/description, SKILL.md, clawhub.json, and trader.py consistently implement a Polymarket whale-contrarian trading strategy. The single required credential (SIMMER_API_KEY) and the declared pip dependency (simmer-sdk) are appropriate for placing trades via the SimmerClient.

ℹ

Instruction Scope

Instructions and code limit themselves to fetching public leaderboard and Polymarket data, cross-referencing markets, and placing trades via SimmerClient. One notable detail: the leaderboard is fetched from a third-party URL (https://predicting.top) rather than an official Polymarket leaderboard — this is functional but introduces a trust dependency (see guidance). The skill respects paper mode by default unless explicitly run with a --live flag.

✓

Install Mechanism

No install spec in the repository files, but clawhub.json declares a pip dependency on 'simmer-sdk' which is consistent with the code's import. Installing a single known pip package is expected for this skill.

✓

Credentials

Only SIMMER_API_KEY and tunable env vars are required. SIMMER_API_KEY is justified because the skill uses SimmerClient to simulate or execute trades. No unrelated credentials or config paths are requested.

✓

Persistence & Privilege

always is false and autostart is false in metadata; the skill is user-invocable and can run autonomously (default platform behavior) but it does not request elevated/always-enabled presence or attempt to modify other skills. It only applies its own skill config when available.

Assessment

This skill appears to do what it claims, but take these precautions before enabling live trading: 1) Keep the skill in paper mode (default) and thoroughly backtest signals before using --live; 2) The skill pulls a leaderboard from https://predicting.top (a third‑party service). Verify the source's trustworthiness — a manipulated leaderboard could create false signals; consider switching to an official leaderboard if available; 3) Provide SIMMER_API_KEY only when you understand what account/funds it controls; prefer keys/accounts with limited funds and the minimal permissions needed; 4) Review and run the included trader.py locally to confirm behavior (it is readable and not obfuscated); 5) Be aware that algorithmic trading has financial risk — limiting MAX_POSITION, MAX_POSITIONS, and using conservative tunables is advisable. If you want higher assurance, request the maintainer/source for provenance or replace the leaderboard endpoint with a vetted data source.

Like a lobster shell, security has layers — review code before you run it.

latestvk971m0zqrnsscc33k34h77vkx985py6m

92downloads

0stars

6versions

Updated 2h ago

v1.0.6

MIT-0

Whale Contrarian Trader

Strategy Overview

This skill exploits information asymmetry between retail traders and top-performing whales on Polymarket. When a market's probability sits at an extreme (above 70% or below 30%), it reflects strong retail consensus. If multiple top leaderboard wallets are simultaneously taking the opposite side, it signals that smart money disagrees with the crowd.

The skill fetches the public Polymarket leaderboard, tracks recent whale activity, cross-references it against markets at probability extremes, and trades in the whale's direction when enough whales independently oppose retail consensus.

Signal Logic

Fetch leaderboard -- Pull top 50 wallet addresses from the public leaderboard API.
Fetch wallet activity -- For each whale, retrieve recent trades from the Polymarket data API.
Identify extreme markets -- Markets where probability > CONTRARIAN_THRESHOLD (70%) or < 1 - CONTRARIAN_THRESHOLD (30%).
Detect opposition -- For each extreme market, count whales trading the opposite direction from retail consensus.
Generate signal -- If at least MIN_WHALE_OPPOSITION whales (default: 2) are on the contrarian side, generate a trade signal in the whale's direction.
Conviction sizing -- Base conviction from threshold bands, boosted by a whale multiplier: 1.0 + min(0.4, (whale_count - 1) * 0.1).

Edge Thesis

Whale wallets that appear on the Polymarket leaderboard have demonstrated sustained profitability. Their edge typically comes from:

Superior information: Access to domain experts, proprietary data, or faster news processing.
Better models: Quantitative models that more accurately estimate true probabilities.
Behavioral discipline: Less susceptible to the narrative biases that push retail to extremes.

When retail has pushed a market to a probability extreme (the crowd is very confident), and multiple whales independently disagree, the expected value of following smart money is positive. The more whales that converge on the contrarian side, the stronger the signal.

This is not a guarantee -- whales can be wrong. But systematic tracking of whale-vs-retail divergence at extremes has a positive expected edge over time.

Remix Ideas

Sector-specific whale tracking: Filter whale activity to specific market categories (politics, crypto, sports) where certain whales have demonstrated domain expertise.
Whale quality weighting: Weight signals by whale PnL rank -- a top-5 whale opposing retail is stronger than a top-50 whale.
Time decay: Weight recent whale trades more heavily than older ones (e.g., last 24h vs last 7 days).
Volume-weighted opposition: Instead of counting whale wallets, sum the dollar volume of contrarian whale trades.
Momentum confirmation: Only trade if the whale contrarian activity is increasing over time (more whales joining the opposite side).

Safety

Guard	Default	Purpose
Paper mode	ON	`--live` flag required for real trades
MAX_SPREAD	8%	Skip illiquid markets
MIN_DAYS	7	Avoid near-resolution noise
MAX_POSITIONS	6	Cap portfolio exposure
MIN_VOLUME	$5,000	Skip thin markets
MIN_WHALE_OPPOSITION	2	Require multiple independent whale signals
Flip-flop guard	ON	SDK discipline check
Slippage guard	15%	SDK slippage check

Tunables

Env Var	Default	Description
SIMMER_MAX_POSITION	40	Max position size in USD
SIMMER_MIN_TRADE	5	Min trade size in USD
SIMMER_MIN_VOLUME	5000	Min market volume in USD
SIMMER_MAX_SPREAD	0.08	Max bid-ask spread
SIMMER_MIN_DAYS	7	Min days until resolution
SIMMER_MAX_POSITIONS	6	Max simultaneous positions
SIMMER_YES_THRESHOLD	0.38	YES threshold for conviction sizing
SIMMER_NO_THRESHOLD	0.62	NO threshold for conviction sizing
SIMMER_CONTRARIAN_THRESHOLD	0.70	Probability extreme threshold (retail consensus)
SIMMER_MIN_WHALE_OPPOSITION	2	Min whales required on contrarian side

Dependency

simmer-sdk (pip)
SIMMER_API_KEY environment variable

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