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prediction-trader

Prediction-Trader provides AI-powered analysis of prediction markets across Polymarket and Kalshi, augmented with social-signal intelligence. The Skill aggregates market prices and implied probabilities, normalizes outcomes across platforms, and applies machine-learning models to detect trend shifts

Updated today<1 min setup

Overview

Prediction-Trader provides AI-powered analysis of prediction markets across Polymarket and Kalshi, augmented with social-signal intelligence.

Prediction-Trader provides AI-powered analysis of prediction markets across Polymarket and Kalshi, augmented with social-signal intelligence. The Skill aggregates market prices and implied probabilities, normalizes outcomes across platforms, and applies machine-learning models to detect trend shifts, liquidity anomalies, and consensus changes. Social-signal modules extract sentiment, influencer activity, topic volume, and rumor propagation from Twitter, Reddit, Discord, and news sources to weight market signals. Features include real-time dashboards, event-level probability forecasts, trade-idea scoring, risk metrics, position-sizing suggestions, customizable alerts, API access, and backtesting of strategies. Use cases include active prediction-market traders, researchers, journalists, and risk managers seeking event hedges or quantified forecasts. Core advantages are consolidated cross-platform visibility, faster anomaly detection, data-driven trade signals, and reduced monitoring overhead.

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How this skill works

Prediction-Trader provides AI-powered analysis of prediction markets across Polymarket and Kalshi, augmented with social-signal intelligence. The Skill aggregates market prices and implied probabilities, normalizes outcomes across platforms, and applies machine-learning models to detect trend shifts

SKILL.mdALPHIO / VERIFIED

Prediction Trader

AI-powered prediction market analysis assistant that aggregates data from multiple platforms and social signals.

Supported Platforms

  • Polymarket: Offshore prediction market on Polygon (crypto, politics, sports, world events)
  • Kalshi: CFTC-regulated US prediction market (Fed rates, GDP, CPI, economics)

Commands

Compare Markets

python3 {baseDir}/scripts/trader.py compare "[topic]"

Compare prediction markets across both platforms for a given topic.

Get Trending

python3 {baseDir}/scripts/trader.py trending

Get trending prediction markets from both platforms.

Analyze Topic

python3 {baseDir}/scripts/trader.py analyze "[topic]"

Full analysis including market data and social signals.

Platform-Specific

# Polymarket
python3 {baseDir}/scripts/trader.py polymarket trending
python3 {baseDir}/scripts/trader.py polymarket crypto
python3 {baseDir}/scripts/trader.py polymarket search "[query]"

# Kalshi
python3 {baseDir}/scripts/trader.py kalshi fed
python3 {baseDir}/scripts/trader.py kalshi economics
python3 {baseDir}/scripts/trader.py kalshi search "[query]"

Output Format

Results include:

  • Market question/title
  • YES/NO prices (probability)
  • Trading volume
  • Platform source
  • Resolution date (if available)

Requirements

  • UNIFAI_AGENT_API_KEY - UnifAI SDK key for Polymarket tools and social signals
  • GOOGLE_API_KEY - Gemini API key for LLM analysis

Example Usage

User: "Compare Bitcoin prediction markets"

Assistant: I'll compare Bitcoin markets across Polymarket and Kalshi.

python3 {baseDir}/scripts/trader.py compare "bitcoin"

User: "What are the Fed rate predictions?"

Assistant: Let me fetch the Federal Reserve interest rate markets from Kalshi.

python3 {baseDir}/scripts/trader.py kalshi fed

Notes

  • Polymarket data accessed via UnifAI tools (may have rate limits)
  • Kalshi data accessed via direct public API (no auth for read)
  • This tool is read-only; trading requires platform authentication
  • All prices shown as decimals (0.75 = 75% probability)

Best used for

When to use it

Prediction-Trader provides AI-powered analysis of prediction markets across Polymarket and Kalshi, augmented with social-signal intelligence. The Skill aggregates market prices and implied probabilities, normalizes outcomes across platforms, and applies machine-learning models to detect trend shifts

01 · PRE-MEETING

Prepare a decision brief

Turn scattered evidence into a structured case before an investment committee meeting.

02 · TEAM WORKFLOW

Standardize handoffs

Create consistent research outputs across analysts, portfolio managers, and agents.

03 · LIVE UPDATE

Refresh the thesis

Update scenarios after a new catalyst, KPI release, or earnings result.

Community notes

Built to improve with use.

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