Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add AIsa-team/agent-skills --skill prediction-market-arbitragegit clone --depth 1 https://github.com/AIsa-team/agent-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/aisa-team/agent-skills/prediction-market-arbitrage)<a href="https://agentmods.dev/skills/aisa-team/agent-skills/prediction-market-arbitrage"><img src="https://agentmods.dev/badge/skills/aisa-team/agent-skills/prediction-market-arbitrage/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/aisa-team/agent-skills/prediction-market-arbitrage"><img src="https://agentmods.dev/badge/skills/aisa-team/agent-skills/prediction-market-arbitrage.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 7 findings, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Data Exfiltration · line 95 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 99 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 107 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 119 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 127 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 139 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 147 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00023 | $0.01819 |
| Opus 5 | $0.00012 | $0.00910 |
| Sonnet 5 | $0.00005 | $0.00364 |
| Haiku 4.5 | $0.00002 | $0.00182 |
Grade A, and why
prediction-market-arbitrage scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
- curl How it starts
The opening of the file, as written. The whole thing — 201 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Cross-Platform Prediction Market Arbitrage ⚖️
Find arbitrage opportunities across prediction markets for autonomous agents. Powered by AIsa.
One API key. Match events across Polymarket and Kalshi to detect price discrepancies and potential risk-free profit opportunities.
Compatibility
Works with any agentskills.io-compatible harness, including:
- Claude Code and Claude (Anthropic)
- OpenAI Codex
- Cursor
- Gemini CLI (Google)
- OpenCode, Goose, OpenClaw, Hermes
- and any other harness that implements the Agent Skills specification
Requires Python 3, a POSIX shell, and AISA_API_KEY (get one at
aisa.one).
What Can You Do?
Detect Price Discrepancies
"Find the current price difference for the US election market between Polymarket and Kalshi."
Match Cross-Platform Markets
"Find the Kalshi equivalent for this Polymarket sports event."
Track Arbitrage Spreads
"Monitor the price spread for the upcoming NBA game across all supported prediction markets."
Analyze Orderbook Depth
"Check the orderbook depth on both platforms to see if the arbitrage opportunity is actionable."
Quick Start
export AISA_API_KEY="your-key"
How to Look Up IDs
Most endpoints require an ID from the /markets or /matching-markets responses. Always query markets first, then pass the relevant ID to downstream endpoints.
- Polymarket
token_id: Query/polymarket/markets, findside_a.idorside_b.idin the response, then use that value in the market price and orderbook endpoints. - Kalshi
market_ticker: Query/kalshi/markets, findmarket_tickerin the response, then use that value in the market price and orderbook endpoints.
Core Capabilities
1. Find Matching Markets
The first step in arbitrage is finding the same event on multiple platforms.
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 12d ago First seen · 201 lines · 23 tokens per session scan A c75574b4b44b
prediction-market-arbitrage is a skill published in the GitHub repository AIsa-team/agent-skills (25 stars, last pushed yesterday), licensed Apache-2.0. It adds 23 tokens to every session and 1,819 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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