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Polymarket Twitter Cross Contagion Trader

通过检测人物发帖量市场的跨人关联信号,调整对相关人物高位区间市场的下单信念并执行交易;默认纸面模式,需 Simmer 服务凭证与 Python SDK,含仓位、成交量、价差等风控参数。

diagnostikon
diagnostikon
热度 48.30
最近更新 2026-05-11 17:39:34
分类:自动化依赖:代码执行 / 第三方 API / 读写文件应用场景:财务 / 自动化脚本 / 市场分析

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

  1. Group all post-count bin markets by person
  2. Compute each person's "heat" — are the market prices shifted toward higher bins?
  3. 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.

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