Polymarket Twitter Cross Contagion Trader

核心功能：检测公众人物间的发帖联动效应，基于预设联动系数调整交易信心，在Polymarket平台交易帖子数量类市场，利用市场独立定价的漏洞套利；支持纸交易、实盘模式，可自定义风险参数，还能拓展实时发帖监控、主题聚类等信号逻辑。典型场景：借助马斯克、特朗普等公众人物发帖关联量化交易时使用，需配置SIMMER_API_KEY并安装simmer-sdk，输出交易执行结果。

diagnostikon

热度 48.40

最近更新 2026-05-11 17:39:34

分类：数据依赖：代码执行 / 第三方 API应用场景：财务 / 市场分析 / 数据处理 / 自动化脚本

安装技能

复制下面的话术发给你的 Agent，它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill： npx secure-skills-cli add polymarket-twitter-cross-contagion-trader

Metadata

name: polymarket-twitter-cross-contagion-trader
description: Trades post-count bin markets by detecting cross-person contagion where one public figure posting heavily causes correlated figures to increase their rate. Requires SIMMER_API_KEY and simmer-sdk. Use when you want to exploit inter-person posting correlation that markets price independently.
metadata: {"author":"Diagnostikon","owner":"Diagnostikon","version":"1.0.0","displayName":"Twitter Cross-Contagion Trader","difficulty":"advanced","homepage":"https://simmer.markets/skills","repository":"https://github.com/SpartanLabsXyz/simmer-sdk","requires_env":"SIMMER_API_KEY","requires_pip":"simmer-sdk","default_mode":"paper","live_flag":"--live"}

Twitter Cross-Contagion Trader

This is a template.
The default signal detects cross-person posting correlation from market prices — remix it with real-time Twitter API monitoring, topic co-occurrence tracking, or network graph analysis of reply/quote-tweet chains.
The skill handles all the plumbing (market discovery, trade execution, safeguards). Your agent provides the alpha.

Strategy Overview

Public figures don't post in isolation. When Elon Musk enters a political debate, Trump often responds on Truth Social. When crypto crashes, both CZ and Vitalik spike their posting rates.

Markets price each person's bins independently. This skill exploits the cross-person correlation that markets miss.

Signal Logic

Phase 1: Detect Contagion

Group all post-count bin markets by person
Compute each person's "heat" — are the market prices shifted toward higher bins?
Positive heat = market expects more posts than baseline (person is "hot")

Phase 2: Apply Contagion Coefficients

Source	Target	Beta	Why
Elon	Trump	0.15	Political overlap, mutual commentary
Trump	Elon	0.12	Elon reacts to executive orders
Elon	Vitalik	0.08	Crypto topic overlap
Vitalik	Elon	0.06	Elon sometimes responds to ETH news
Elon	CZ	0.05	Crypto/exchange overlap

Phase 3: Trade with Adjusted Conviction

When person A is hot and beta(A->B) > 0, boost conviction on person B's higher bins.

Remix Ideas

Real-time monitoring: Track actual post counts in real-time instead of inferring from market prices
Reply chain analysis: @-mention graphs show direct contagion paths
Topic clustering: NLP on recent posts to detect shared topics driving correlation
Dynamic beta: Re-estimate contagion coefficients weekly from observed data

Risk Parameters

Parameter	Default	Notes
Max position size	$40 USDC	Per market
Min market volume	$1,000	Standard filter
Max bid-ask spread	10%	Default threshold
Min days to resolution	0	Post-count markets are short-lived
Max open positions	8	Diversify across persons

Installation & Setup

clawhub install polymarket-twitter-cross-contagion-trader

Requires: SIMMER_API_KEY environment variable.

Cron Schedule

Cron is set to null — the skill does not run on a schedule until you configure it in the Simmer UI.

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. 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
`SIMMER_MAX_POSITION`	`40`	Max USDC per trade (reached at 100% conviction)
`SIMMER_MIN_VOLUME`	`1000`	Min market volume filter (USD)
`SIMMER_MAX_SPREAD`	`0.10`	Max bid-ask spread (0.10 = 10%)
`SIMMER_MIN_DAYS`	`0`	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_TRADE`	`5`	Floor for any trade (min USDC regardless of conviction)

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: hello@simmer.markets

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