
Opportunity Capture
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
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.
Skill.md
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
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 signalsGOOGLE_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.
Feedback will appear here as this skill is used and reviewed.
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