Opportunity Capture

prediction-trader

Vor 45 Tagen aktualisiertSetup in <1 Min.

Überblick

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

So funktioniert diese Skill

SKILL.mdALPHIO / VERIFIZIERT

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)

Am besten geeignet für

Wann du sie einsetzt

01 · VOR DEM MEETING

Ein Entscheidungsbriefing vorbereiten

Mach aus verstreuten Belegen vor dem Investmentkomitee einen strukturierten Case.

02 · TEAM-WORKFLOW

Übergaben standardisieren

Erzeuge konsistente Research-Ergebnisse über Analysten, Portfoliomanager und Agents hinweg.

03 · LIVE-UPDATE

Die These auffrischen

Aktualisiere die Szenarien nach einem neuen Katalysator, einer KPI-Veröffentlichung oder einem Quartalsergebnis.

Community-Notizen

Wird mit jedem Einsatz besser.

Feedback erscheint hier, sobald diese Skill genutzt und geprüft wird.

Feedback geben

Mehr entdecken