prediction-market-data

prediction-market-data is a skill for Claude Code, Codex from AIsa-team/agent-skills. It costs 22 tokens per session (3,410 once invoked), scanned A, original, Apache-2.0.

A data tool for prediction markets such as Polymarket and Kalshi, where people trade contracts linked to the likelihood of future events.

In plain words
What is it for?
Checking event probabilities, researching market sentiment, analysing trading activity, tracking wallet positions and profit or loss, and looking for cross-market arbitrage.
Why use it?
It brings market prices, order books, positions, trades, and historical data together for research. It can help compare markets and examine possible price differences.

Skill for Claude CodeCodex

Which agent this was written for is unclear — built for openclaw. Also seen: positional $N argument; mentions Claude Code; mentions Codex.

Good fit Checking event probabilities, researching market sentiment, analysing trading activity, tracking wallet positions and profit or loss, and looking for cross-market arbitrage.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/aisa-team/agent-skills/prediction-market-data
Install

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.

Any agent
npx skills add AIsa-team/agent-skills --skill prediction-market-data
Clone the repo
git clone --depth 1 https://github.com/AIsa-team/agent-skills

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for prediction-market-data

README.md
[![agentmods](https://agentmods.dev/badge/skills/aisa-team/agent-skills/prediction-market-data/github.svg)](https://agentmods.dev/skills/aisa-team/agent-skills/prediction-market-data)
Your own site
<a href="https://agentmods.dev/skills/aisa-team/agent-skills/prediction-market-data"><img src="https://agentmods.dev/badge/skills/aisa-team/agent-skills/prediction-market-data/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.

agentmods 80×15 button for prediction-market-data

Your own site · 80×15
<a href="https://agentmods.dev/skills/aisa-team/agent-skills/prediction-market-data"><img src="https://agentmods.dev/badge/skills/aisa-team/agent-skills/prediction-market-data.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 22 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,410 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 15 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 173
    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 182
    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 190
    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 198
    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 207
    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 216
    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 224
    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 232
    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 240
    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 250
    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 259
    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 268
    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 277
    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 287
    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 297
    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.
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00022 $0.03410
Opus 5 $0.00011 $0.01705
Sonnet 5 $0.00004 $0.00682
Haiku 4.5 $0.00002 $0.00341

Measured 12d ago against content hash 6999da8a5f34, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

prediction-market-data 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.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/prediction_market_client.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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
financial/prediction-market-data/SKILL.md · 395 lines

How it starts

The opening of the file, as written. The whole thing — 395 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Cross-Platform Prediction Market Data 📈

Prediction markets data access for autonomous agents. Powered by AIsa.

One API key. Full Polymarket and Kalshi intelligence.

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?

Probability Checks

"What are the odds of [event] happening?"

Market Sentiment

"Research the current market sentiment on the upcoming election."

Trading Analysis

"Analyze historical prices and orderbooks for this market."

Portfolio Tracking

"Track portfolio positions and P&L for wallet address X."

Arbitrage Detection

"Find arbitrage opportunities across Polymarket and Kalshi."

Quick Start

export AISA_API_KEY="your-key"

How to Look Up IDs

Most endpoints require an ID that comes from the /markets response. Always query markets first, then pass the relevant ID to downstream endpoints.

  1. Polymarket token_id: Query /polymarket/markets, find side_a.id or side_b.id in the response, then pass it to /polymarket/market-price/{token_id}.
  2. Polymarket condition_id: Query /polymarket/markets, find condition_id in the response, then pass it to /polymarket/candlesticks/{condition_id}.
  3. Kalshi market_ticker: Query /kalshi/markets, find market_ticker in the response, then pass it to /kalshi/market-price/{market_ticker}.

End-to-End Examples

Get the current price of a Polymarket market

Prices require a token_id, which comes from the /markets response. Always query markets first.

Read the full file on GitHub · 395 lines

Files

What ships with it

2 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.

Changes

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.

  1. 12d ago First seen · 395 lines · 22 tokens per session scan A 6999da8a5f34

Subscribe to this mod's changes

prediction-market-data is a skill published in the GitHub repository AIsa-team/agent-skills (25 stars, last pushed 2d ago), licensed Apache-2.0. It adds 22 tokens to every session and 3,410 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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