Supply Chain & Logistics Trader

This is a template.
The default signal is keyword-based market discovery (shipping, port, logistics, commodity, supply chain) — remix it with freight index APIs (Baltic Dry Index), satellite AIS vessel tracking data, or real-time port authority feeds.
The skill handles all the plumbing (market discovery, trade execution, safeguards). Your agent provides the alpha.

Strategy Overview

Supply chain prediction markets are among the most underserved categories on Polymarket. This skill identifies and trades markets related to:

• - Port congestion — Rotterdam, Suez Canal, LA/Long Beach delays
• Commodity prices — Brent crude, steel, lithium thresholds
• Demand spikes — GPU/chip shortages, EV battery supply
• Company logistics — Tesla delivery delays, Maersk shipping times, Amazon Prime SLAs

Research shows prediction markets can reduce supply chain forecasting errors by 20–50% vs traditional methods (CFTC data). This makes these markets both tradable AND informative.

Signal Logic

Default Signal: Conviction-Based Sizing with Disruption Bias

1. 1. Discover active supply chain markets on Polymarket
2. Compute base conviction from distance to threshold (0% at boundary → 100% at p=0/p=1)
3. Apply disruption_bias() — combines seasonal shipping cycles with commodity predictability
4. Size = max(MIN_TRADE, conviction × bias × MAX_POSITION) — capped at MAXPOSITION
5. Skip markets with spread > MAXSPREAD or fewer than MIN_DAYS to resolution

Disruption Bias (built-in, no API required)

INLINECODE2 multiplies conviction using two independent factors simultaneously:

Factor 1 — Seasonal Shipping Cycle

Container shipping has a well-documented Q4 crunch (Oct–Dec) driven by pre-holiday inventory builds. Congestion and delay markets are structurally more likely to resolve YES in peak season.

Period	Multiplier	Why
Q4: Oct–Dec	1.25x	Peak season — pre-holiday crunch, port congestion likely
Q1: Jan–Mar

0.85x | Off-season — lower disruption probability |
| Apr–Sep | 1.05x | Mild mid-year activity |

Only applied when the question contains shipping/port/freight/cargo keywords.

Factor 2 — Commodity Predictability

Commodity type	Multiplier	Why
Crude oil / energy / LNG	1.20x	Most liquid commodity — highly modeled, information-rich
Semiconductors / chips / GPU

1.15x | Documented cycles, policy-driven — trackable |
| Lithium / cobalt / EV battery | 1.15x | China-concentrated supply — export data publicly trackable |
| Chokepoints (Suez, Red Sea, Panama) | 1.10x | Geopolitical risk well-documented and persistent |
| Agricultural / grain / harvest | 0.85x | Weather-dependent, high variance — hard to model |

Combined multiplier capped at 1.40x. A Q4 container shipping market mentioning Suez would score 1.25 × 1.10 = 1.375x.

Remix Ideas

• - Baltic Dry Index: BDI weekly change as direct conviction input — rising BDI = lean into shipping disruption YES
• AIS vessel tracking (MarineTraffic): Real vessel queue counts at LA/Long Beach as direct oracle for port congestion markets
• USDA crop reports: Trade agricultural supply markets in the 48h window before/after report release
• Port authority RSS feeds: Rotterdam, Singapore, Shanghai real-time congestion data as entry trigger

Market Categories Tracked

CODEBLOCK0

Risk Parameters

Parameter	Default	Notes
Max position size	$25 USDC	Per market
Min market volume

$5,000 | Liquidity filter | | Max bid-ask spread | 10% | Slippage guard | | Min days to resolution | 7 | Avoid last-minute noise | | Max open positions | 5 | Concentration limit |

Installation & Setup

CODEBLOCK1

Requires: SIMMER_API_KEY environment variable.

Cron Schedule

Runs every 15 minutes (*/15 * * * *). Markets are slow-moving enough that high-frequency execution is unnecessary.

Safety & Execution Mode

The skill defaults to paper trading (venue="sim"). Real trades only execute when --live is passed explicitly.

Scenario	Mode	Financial risk
INLINECODE7	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
INLINECODE11	Yes	Trading authority — keep this credential private. Do not place a live-capable key in any environment where automated code could call --live.

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
INLINECODE17	INLINECODE18	Max USDC per trade (reached at 100% conviction)
INLINECODE19

5000 | 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 | 5 | 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_TRADE | 5 | Floor for any trade (min USDC regardless of conviction) |

Dependency

INLINECODE33 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.