prediction-market-arbitrage-api

name	prediction-market-arbitrage-api
description	Find arbitrage opportunities across Polymarket and Kalshi prediction markets via AIsa API. Scan sports markets for cross-platform price discrepancies, compare real-time odds, verify orderbook liquidity. Use when user asks about: prediction market arbitrage, cross-platform price differences, sports betting arbitrage, odds comparison, risk-free profit, market inefficiencies.
license	MIT
compatibility	Designed for Agent Skills compatible clients such as OpenClaw, Claude Code, Hermes, and GitHub-backed skill catalogs. Requires system binaries python3, environment variables AISA_API_KEY and internet access to api.aisa.one.
metadata	{"aisa":{"emoji":"⚖️","requires":{"bins":["python3"],"env":["AISA_API_KEY"]},"primaryEnv":"AISA_API_KEY","compatibility":"Designed for Agent Skills compatible clients such as OpenClaw, Claude Code, Hermes, and GitHub-backed skill catalogs. Requires system binaries python3, environment variables AISA_API_KEY and internet access to api.aisa.one."}}

Prediction Market Arbitrage Api

Find arbitrage opportunities across Polymarket and Kalshi via AIsa API.

Setup

export AISA_API_KEY="your-key"

Get a key at aisa.one ($0.01/query, pay-as-you-go).

Workflow

Finding arbitrage involves these steps:

1. Scan matching markets across platforms (scan for bulk, match for specific)
2. Review spreads — the tool calculates price differences automatically
3. Verify liquidity — use prediction_market_client.py orderbooks to check depth before acting

Quick Examples

Scan a sport for arbitrage

# Scan all NBA markets on a date — shows spreads automatically
python3 scripts/arbitrage_finder.py scan nba --date 2025-04-01

Analyze a specific market

# By Polymarket slug
python3 scripts/arbitrage_finder.py match --polymarket-slug <slug>

# By Kalshi ticker
python3 scripts/arbitrage_finder.py match --kalshi-ticker <ticker>

Verify liquidity before acting

# Check orderbook depth on both sides
python3 scripts/prediction_market_client.py polymarket orderbooks --token-id <id>
python3 scripts/prediction_market_client.py kalshi orderbooks --ticker <ticker>

Commands

arbitrage_finder.py — Automated Detection

python3 scripts/arbitrage_finder.py scan <sport> --date <YYYY-MM-DD> [--min-spread <pct>] [--min-liquidity <usd>] [--json]
python3 scripts/arbitrage_finder.py match --polymarket-slug <slug> [--min-spread <pct>] [--min-liquidity <usd>] [--json]
python3 scripts/arbitrage_finder.py match --kalshi-ticker <ticker> [--min-spread <pct>] [--min-liquidity <usd>] [--json]

Sports: nba, nfl, mlb, nhl, soccer, tennis.

prediction_market_client.py — Raw Market Data

Use for manual price checks and deeper analysis.

# Search markets
python3 scripts/prediction_market_client.py polymarket markets --search <kw> --status open --limit 5
python3 scripts/prediction_market_client.py kalshi markets --search <kw> --status open --limit 5

# Get prices (use token_id / market_ticker from markets output)
python3 scripts/prediction_market_client.py polymarket price <token_id>
python3 scripts/prediction_market_client.py kalshi price <market_ticker>

# Cross-platform sports matching
python3 scripts/prediction_market_client.py sports by-date <sport> --date <YYYY-MM-DD>
python3 scripts/prediction_market_client.py sports matching (--polymarket-slug <slug> | --kalshi-ticker <ticker>)

# Orderbook depth
python3 scripts/prediction_market_client.py polymarket orderbooks --token-id <id>
python3 scripts/prediction_market_client.py kalshi orderbooks --ticker <ticker>

Understanding Arbitrage

Arbitrage exists when the combined cost of all mutually exclusive outcomes across platforms is less than 1.0:

"Yes" at 0.40 on Polymarket + "No" at 0.55 on Kalshi = cost 0.95, guaranteed payout 1.00 → 5.3% profit.

Always verify orderbook depth — a spread without liquidity is not executable.

Security & Permissions

Requires: AISA_API_KEY environment variable.

All operations are read-only via HTTPS GET to api.aisa.one. Arbitrage spreads are calculated locally. No trades executed, no wallets connected, no personal data sent beyond the API key. Every response includes usage.cost and usage.credits_remaining.

Full docs: AIsa API Reference.