Polymarket 24h Precipitation Range Trader

Trades mispricings in precipitation-range markets by reconstructing the implied probability distribution across bins for the same city and period, detecting...

Security Scan

The skill's code, instructions, and declared requirements are consistent with a Polymarket trading bot that uses the Simmer SDK; it requires a single trading API key and defaults to paper trading.

Purpose & Capability

Name/description match the implementation: the code discovers precipitation-range markets, reconstructs distributions, detects sum/monotonicity violations, and places trades via a SimmerClient. Required artifacts (SIMMER_API_KEY, simmer-sdk) are appropriate for a trading skill.

Instruction Scope

SKILL.md and trader.py limit actions to market discovery, parsing, analysis, and trade execution via the Simmer API. The skill does not instruct reading unrelated system files or exfiltrating data to third-party endpoints. It explicitly defaults to simulation unless run with --live.

Install Mechanism

No external download URLs or extract steps; installation is via pip dependency 'simmer-sdk' declared in clawhub.json. Using a pip package is a common pattern but carries the usual supply-chain risks—review the simmer-sdk package/source before installing.

Credentials

The only required env var is SIMMER_API_KEY (declared). The script also reads tunable SIMMER_* variables from env which are declared as tunables in clawhub.json. Requesting a single trading API key is proportionate; treat SIMMER_API_KEY as high-value and scope permissions as appropriate.

Persistence & Privilege

autostart: false and cron: null mean the skill will not run automatically by default. always is not set. The automaton entrypoint is declared but not autostarted — normal for an optional trading skill.

Assessment

This appears to be a coherent Polymarket trading skill that intentionally defaults to paper trading and requires one high-value credential (SIMMER_API_KEY). Before installing: (1) confirm you trust the simmer-sdk pip package and inspect its source, (2) do not run the script with --live unless you intend to place real USDC trades and have reviewed risk/tunables, (3) restrict the SIMMER_API_KEY permissions and rotate it if you later uninstall the skill, and (4) if you want stricter safety, run initially in a sandboxed environment and review logs of any live execution.

24h Precipitation Range Trader

This is a template. The default signal is distribution-sum and monotonicity violation detection across precipitation-range bin markets — remix it with weather API feeds, historical precipitation data, or climate model ensembles. The skill handles all the plumbing (market discovery, distribution construction, trade execution, safeguards). Your agent provides the alpha.

Strategy Overview

Polymarket lists multiple precipitation range bins for the same city and period:

• "Will Seattle have more than 5 inches of precipitation in April?" = 18.8%
• "Will Seattle have between 4.5 and 5 inches in April?" = 17.5%
• "Will Seattle have between 4 and 4.5 inches in April?" = 29%
• "Will Seattle have between 3.5 and 4 inches in April?" = 19%
• "Will Seattle have between 3 and 3.5 inches in April?" = 19%
• "Will Seattle have between 2.5 and 3 inches in April?" = 20%

These range bins form a probability distribution that must sum to ~100%. When they don't, individual bins are mispriced. Additionally, cumulative markets ("more than X inches") must be monotonically decreasing as X increases.

The Edge: Distribution Arbitrage for Precipitation Markets

In traditional markets, discrete outcome probabilities must sum to 1.0 — this is a fundamental axiom. On Polymarket, each precipitation range bin trades independently with its own order book and liquidity. Retail treats each bin as an isolated bet without checking the full distribution.

Violation Type 1: Sum Deviation

All range bins for a (city, period) must sum to ~100%:

P(2.5-3in) + P(3-3.5in) + P(3.5-4in) + P(4-4.5in) + P(4.5-5in) + P(>5in) = 100%

If the sum is 108%, at least one bin is overpriced. If the sum is 92%, at least one bin is underpriced.

Violation Type 2: Cumulative Monotonicity Break

Cumulative markets must be monotonic:

P(>3in) >= P(>3.5in) >= P(>4in) >= P(>4.5in) >= P(>5in)    [more_than: decreasing]
P(<3in) <= P(<3.5in) <= P(<4in) <= P(<4.5in) <= P(<5in)    [less_than: increasing]

If a higher threshold has a higher "more than" probability than a lower threshold, the curve is broken.

Why This Works

1. Retail trades in silos — most users view each precipitation bin independently and don't cross-reference the full distribution
2. No market maker enforcing consistency — unlike bookmakers who balance their book, Polymarket has no mechanism to keep bins summing to 100%
3. Mathematical, not opinion — the violations are provable inconsistencies in the probability axioms
4. Multiple cities, monthly resolution — many cities with monthly precipitation markets create a large opportunity surface

Signal Logic

1. Discover all precipitation range markets via keyword search ("precipitation", "inches", "rainfall", "Seattle")
2. Parse each question: extract city, precipitation range (between X and Y / more than X / less than X), and period (month)
3. Group into distributions by (city, period)
4. For each distribution with 2+ bins:
   • Check if all range bins sum to ~100% (tolerance configurable via SIMMER_SUM_TOLERANCE)
   • If sum > 105%: identify and sell the most overpriced bin (highest relative to neighbors)
   • If sum < 95%: identify and buy the most underpriced bin (lowest relative to neighbors)
   • Check monotonicity on cumulative bins ("more than X" decreasing, "less than X" increasing)
5. Rank violations by magnitude
6. Trade only violations that also pass threshold gates (YES_THRESHOLD / NO_THRESHOLD)
7. Size by conviction (violation magnitude + threshold distance), not flat amount

Safety & Execution Mode

The skill defaults to paper trading (venue="sim"). Real trades only with --live flag.

Scenario	Mode	Financial risk
python trader.py	Paper (sim)	None
Cron / automaton	Paper (sim)	None
python trader.py --live	Live (polymarket)	Real USDC

autostart: false and cron: null mean nothing runs automatically until configured in Simmer UI.

Required Credentials

Variable	Required	Notes
SIMMER_API_KEY	Yes	Trading authority. Treat as a high-value credential.

Tunables (Risk Parameters)

All declared as tunables in clawhub.json and adjustable from the Simmer UI.

Variable	Default	Purpose
SIMMER_MAX_POSITION	35	Max USDC per trade at full conviction
SIMMER_MIN_TRADE	5	Floor for any trade
SIMMER_MIN_VOLUME	5000	Min market volume filter (USD)
SIMMER_MAX_SPREAD	0.08	Max bid-ask spread
SIMMER_MIN_DAYS	0	Min days until resolution (0 = allow same-day)
SIMMER_MAX_POSITIONS	8	Max concurrent open positions
SIMMER_YES_THRESHOLD	0.38	Buy YES only if market probability <= this
SIMMER_NO_THRESHOLD	0.62	Sell NO only if market probability >= this
SIMMER_SUM_TOLERANCE	0.05	Allowed deviation from 100% sum before trading

Edge Thesis

Precipitation range markets on Polymarket are structured as discrete probability distributions. Each bin trades independently, but they are mathematically constrained to sum to 100%. When retail order flow pushes individual bins without propagating to the full distribution, the sum deviates — creating pure mathematical arbitrage. This skill reconstructs the distribution, finds where the axioms break, and trades the repair.

Dependency

simmer-sdk by Simmer Markets (SpartanLabsXyz)

• PyPI: https://pypi.org/project/simmer-sdk/
• GitHub: https://github.com/SpartanLabsXyz/simmer-sdk