Moonpay Prediction Market

Organization

moonpay

moonpay-prediction-market

Trade on prediction markets (Polymarket, Kalshi). Search markets, buy/sell positions, track PnL, and view trade history.

Overview

Publisher	moonpay
Repository	`skills`
Skill name	`moonpay-prediction-market`
Stars	112
Forks	30
Bundled files	Instructions only
License	MIT
Links	Skill source Repository Homepage

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
Self-contained
Everything the model needs lives in the instructions — no extra files to sync.
Open source
Published by moonpay on GitHub. Read the source before you install it.

Installation

Install the Moonpay Prediction Market AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/moonpay/skills/tree/main/skills/moonpay-prediction-market
Enable the skill in any chat where you want it available.

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/moonpay/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/skills/moonpay-prediction-market .claude/skills/moonpay-prediction-market

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Moonpay Prediction Market in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Moonpay Prediction Market on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Moonpay Prediction Market is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Prediction markets

Goal

Search prediction markets, buy and sell outcome shares, track positions and PnL.

Supports two providers:

Polymarket — runs on Polygon (USDC.e). Requires an EVM wallet.
Kalshi — runs on Solana (USDC). Requires a Solana wallet.

Prerequisites

Authenticate: mp login --email <email> then mp verify --email <email> --code <code>
Have a local wallet: mp wallet list (create with mp wallet create --name "main" if needed)
Register your wallet with the provider (one-time setup):

bash
# For Polymarket (use your EVM/Polygon address)
mp prediction-market user create --provider polymarket --wallet <evm-address>

# For Kalshi (use your Solana address)
mp prediction-market user create --provider kalshi --wallet <solana-address>

Fund the wallet — Polymarket needs USDC.e on Polygon, Kalshi needs USDC on Solana. See the moonpay-fund-polymarket or moonpay-buy-crypto skills.

Browse and research markets

bash
# Search markets by keyword
mp prediction-market market search --provider polymarket --query "bitcoin" --limit 10

# Get trending markets (sorted by 24h volume, min $150K)
mp prediction-market market trending list --provider polymarket --limit 10

# Browse market categories/tags
mp prediction-market market tag list --provider polymarket

# Filter markets by tag
mp prediction-market market search --provider polymarket --query "*" --tagIds "crypto,politics"

# Get full event details (all markets, outcomes, prices)
mp prediction-market market event retrieve --provider polymarket --slug <event-slug>

# Check current price for an outcome token
mp prediction-market market price retrieve --provider polymarket --tokenId <token-id>

# View price history for an outcome
mp prediction-market market price-history list --provider polymarket --tokenId <token-id> --interval 1w

Buy and sell positions

bash
# Buy shares of an outcome
mp prediction-market position buy \
  --wallet main \
  --provider polymarket \
  --tokenId <outcome-token-id> \
  --price 0.65 \
  --size 100

# Sell shares
mp prediction-market position sell \
  --wallet main \
  --provider polymarket \
  --tokenId <outcome-token-id> \
  --price 0.70 \
  --size 50

Key concepts:

tokenId comes from outcomeTokens[].tokenId in market search results
price is 0-1 (e.g., 0.65 = 65 cents per share, implies 65% probability)
size is the number of shares
Cost = price x size (e.g., 0.65 x 100 = $65 USDC)
If the outcome resolves YES, each share pays $1. Profit = (1 - price) x size

Track positions and performance

bash
# View open positions
mp prediction-market position list --provider polymarket --wallet <address>

# View closed positions
mp prediction-market position list --provider polymarket --wallet <address> --status closed

# Get PnL summary
mp prediction-market pnl retrieve --provider polymarket --wallet <address>

# View trade history
mp prediction-market trade list --provider polymarket --wallet <address>

# View all activity (trades, splits, merges, redemptions)
mp prediction-market activity list --provider polymarket --wallet <address>

Workflow

Discover: Search or browse trending markets.
Research: Get event details, check prices, review price history.
Trade: Buy shares on outcomes you believe are mispriced.
Monitor: Track positions and PnL.
Exit: Sell positions when your thesis changes, or wait for resolution.

Example: trade a market

bash
# 1. Find a market
mp prediction-market market search --provider polymarket --query "bitcoin 100k"

# 2. Get event details (note the outcomeTokens)
mp prediction-market market event retrieve --provider polymarket --slug <slug-from-search>

# 3. Check price history
mp prediction-market market price-history list --provider polymarket --tokenId <yes-token-id> --interval 1w

# 4. Buy 50 "Yes" shares at 40 cents
mp prediction-market position buy --wallet main --provider polymarket --tokenId <yes-token-id> --price 0.40 --size 50

# 5. Check your position
mp prediction-market position list --provider polymarket --wallet <address>

# 6. Sell later at a higher price
mp prediction-market position sell --wallet main --provider polymarket --tokenId <yes-token-id> --price 0.60 --size 50

Price history intervals

Interval	Description
`1hr`	Last hour
`1d`	Last day
`1w`	Last week
`1m`	Last month
`max`	All time

Tips

Use mp --json prediction-market ... for programmatic output
Markets with higher volume and liquidity have tighter spreads
Check acceptingOrders — closed markets cannot be traded
negRisk markets use a different settlement framework — the CLI handles this automatically
Polymarket uses USDC.e on Polygon; Kalshi uses USDC on Solana

Related skills

moonpay-fund-polymarket — Fund your Polymarket wallet with USDC.e and POL
moonpay-check-wallet — Check Polygon/Solana balances
moonpay-swap-tokens — Bridge tokens to Polygon
moonpay-trading-automation — Automate trading strategies

Frequently asked questions

What does the Moonpay Prediction Market AI skill do?

Trade on prediction markets (Polymarket, Kalshi). Search markets, buy/sell positions, track PnL, and view trade history.

Why use Moonpay Prediction Market on TypingMind?

Because you install it once and use it with any model. Moonpay Prediction Market is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Moonpay Prediction Market in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/moonpay/skills/tree/main/skills/moonpay-prediction-market. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Moonpay Prediction Market?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Moonpay Prediction Market?

As many as you like. As long as a model supports skills, you can use Moonpay Prediction Market with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Moonpay Prediction Market AI skill free?

Yes. It is published on GitHub by moonpay under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

View all

Create Paperclip Bundled Skill

paperclipai

OrganizationPopular

Turn an idea, tweet, or task into a skill in the Paperclip skills catalog (packages/skills-catalog). Use when asked to FIND or MAKE a skill and publish it as a bundled/optional catalog skill: research…

Tavily

Tavily web search, content extraction, and research tools.

Deep Research

Multi-source deep research using firecrawl and exa MCPs. Searches the web, synthesizes findings, and delivers cited reports with source attribution. Use when the user wants thorough research on any…

Exa Search

Neural search via Exa MCP for web, code, and company research. Use when the user needs web search, code examples, company intel, people lookup, or AI-powered deep research with Exa's neural search…

Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Prediction markets

Goal

Prerequisites

Browse and research markets

Buy and sell positions

Track positions and performance

Workflow

Example: trade a market

Price history intervals

Tips

Related skills

Frequently asked questions

Related AI Skills

Set up your own AI workspace now