Polymarket Whale Scanner Trader

v1.0.0

Scans public Polymarket leaderboards to identify top-performing whale wallets by SmartScore, then trades markets where these whales have high-conviction posi...

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Install

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-scanner-trader.

Previewing Install & Setup.
Prompt PreviewInstall & Setup
Install the skill "Polymarket Whale Scanner Trader" (diagnostikon/polymarket-whale-scanner-trader) from ClawHub.
Skill page: https://clawhub.ai/diagnostikon/polymarket-whale-scanner-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-scanner-trader

ClawHub CLI

Package manager switcher

npx clawhub@latest install polymarket-whale-scanner-trader
Security Scan
Capability signals
CryptoRequires wallet
These labels describe what authority the skill may exercise. They are separate from suspicious or malicious moderation verdicts.
VirusTotalVirusTotal
Benign
View report →
OpenClawOpenClaw
Benign
high confidence
Purpose & Capability
Name/description (discover top Polymarket traders and trade aligned markets) matches the implementation: the skill fetches predicting.top leaderboard data and Polymarket public activity, computes conviction signals, and uses the simmer-sdk to place trades. Required resources (SIMMER_API_KEY, simmer-sdk) are appropriate for a trading integration and no unrelated credentials or system access are requested.
Instruction Scope
SKILL.md and trader.py confine runtime actions to fetching public leaderboards (predicting.top), Polymarket public data API, computing signals, and calling the Simmer API via simmer-sdk. The instructions explicitly default to paper trading and require an explicit --live flag for real trades. The skill does not instruct reading unrelated local files or other environment variables beyond the declared SIMMER_ tunables.
Install Mechanism
There is no custom installer; clawhub.json declares a pip dependency on 'simmer-sdk'. Installing a third-party PyPI package is a reasonable and expected mechanism for a trading SDK but carries the normal supply-chain risk of pip packages. The SKILL.md and clawhub.json point to a GitHub/PyPI project for simmer-sdk which should be reviewed before supplying live credentials.
Credentials
Only SIMMER_API_KEY (primary trading credential) and SIMMER_*-prefixed tunables are required/used. The number and type of env vars are proportional to a trading skill—no unrelated secrets (AWS, GitHub tokens, etc.) are requested. The code reads only the declared SIMMER_ variables.
Persistence & Privilege
The skill is not always:true, automaton.autostart is false, and cron is null (no automatic scheduling by default). It calls apply_skill_config on the Simmer client if available (to load tunables) but does not modify other skills or system-wide configs. Autonomous invocation is the platform default and is not combined with other worrying flags here.
Assessment
This skill appears to do what it says: follow public Polymarket leaderboards, compute signals, and trade via Simmer. Before enabling live trading: (1) Review the simmer-sdk package source (GitHub/PyPI) to confirm it behaves as expected and doesn't exfiltrate credentials. (2) Keep the SIMMER_API_KEY secret, give it minimal permissions if possible, and test extensively in paper mode (the skill defaults to sim). (3) Do not run with --live until you trust the SDK and have tested edge cases (rate limits, bad leaderboard data). (4) Consider running the code in an isolated environment and auditing any third-party dependencies. If you need a deeper audit (supply-chain review of simmer-sdk or a line-by-line code security review), provide that request and I can highlight specific functions or network calls to inspect further.

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

latestvk979dygwg82pqp7pr6xd7v8jt58481k5
82downloads
0stars
1versions
Updated 3w ago
v1.0.0
MIT-0

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:

FilterDefaultPurpose
SmartScore>= 70Only 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:

  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:

pconvictionsize
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

ParameterDefaultNotes
Max position size$40 USDCPer market, reached at max conviction
Min market volume$3,000Liquidity filter
Max bid-ask spread10%Avoid illiquid markets
Min days to resolution7Need time for the trade to work
Max open positions8Concentrated 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.

ScenarioModeFinancial risk
python trader.pyPaper (sim)None
Cron / automatonPaper (sim)None
python trader.py --liveLive (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

VariableRequiredNotes
SIMMER_API_KEYYesTrading 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.

VariableDefaultPurpose
SIMMER_MAX_POSITION40Max USDC per trade (reached at 100% conviction)
SIMMER_MIN_TRADE5Floor for any trade (min USDC regardless of conviction)
SIMMER_MIN_VOLUME3000Min market volume filter (USD)
SIMMER_MAX_SPREAD0.10Max bid-ask spread (0.10 = 10%)
SIMMER_MIN_DAYS7Min days until market resolves
SIMMER_MAX_POSITIONS8Max concurrent open positions
SIMMER_YES_THRESHOLD0.38Buy YES if market price <= this value
SIMMER_NO_THRESHOLD0.62Sell NO if market price >= this value
SIMMER_MIN_SMART_SCORE70Min SmartScore to qualify as a whale to follow
SIMMER_MIN_WIN_RATE0.55Min win rate to qualify as a whale to follow
SIMMER_LEADERBOARD_LIMIT20How many traders to fetch from the leaderboard

Dependency

simmer-sdk is published on PyPI by Simmer Markets.

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

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