Mmcp.market

polymarket skill

by kevinnft·kevinnft/ai-agent-skills·14 stars·MIT

Query Polymarket: markets, prices, orderbooks, history.

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Install the polymarket skill

A skill is a folder. Copy it into your agent's skills folder and the agent loads it when the task matches its description. 

git clone --depth 1 https://github.com/kevinnft/ai-agent-skills.git /tmp/ai-agent-skills
mkdir -p ~/.claude/skills
cp -r /tmp/ai-agent-skills/skills/research/polymarket ~/.claude/skills/polymarket
available in every project

In the Claude apps, zip the folder and upload it from the Skills settings. The folder on GitHub

The instructions your agent would load

SKILL.md as published, without the frontmatter. Read it on GitHub

Polymarket — Prediction Market Data

Query prediction market data from Polymarket using their public REST APIs. All endpoints are read-only and require zero authentication.

See references/api-endpoints.md for the full endpoint reference with curl examples.

When to Use

  • User asks about prediction markets, betting odds, or event probabilities
  • User wants to know "what are the odds of X happening?"
  • User asks about Polymarket specifically
  • User wants market prices, orderbook data, or price history
  • User asks to monitor or track prediction market movements

Key Concepts

  • Events contain one or more Markets (1:many relationship)
  • Markets are binary outcomes with Yes/No prices between 0.00 and 1.00
  • Prices ARE probabilities: price 0.65 means the market thinks 65% likely
  • outcomePrices field: JSON-encoded array like ["0.80", "0.20"]
  • clobTokenIds field: JSON-encoded array of two token IDs [Yes, No] for price/book queries
  • conditionId field: hex string used for price history queries
  • Volume is in USDC (US dollars)

Three Public APIs

  1. Gamma API at gamma-api.polymarket.com — Discovery, search, browsing
  2. CLOB API at clob.polymarket.com — Real-time prices, orderbooks, history
  3. Data API at data-api.polymarket.com — Trades, open interest

Typical Workflow

When a user asks about prediction market odds:

  1. Search using the Gamma API public-search endpoint with their query
  2. Parse the response — extract events and their nested markets
  3. Present market question, current prices as percentages, and volume
  4. Deep dive if asked — use clobTokenIds for orderbook, conditionId for history

Presenting Results

Format prices as percentages for readability:

  • outcomePrices ["0.652", "0.348"] becomes "Yes: 65.2%, No: 34.8%"
  • Always show the market question and probability
  • Include volume when available

Example: "Will X happen?" — 65.2% Yes ($1.2M volume)

Parsing Double-Encoded Fields

The Gamma API returns outcomePrices, outcomes, and clobTokenIds as JSON strings inside JSON responses (double-encoded). When processing with Python, parse them with json.loads(market['outcomePrices']) to get the actual array.

Rate Limits

Generous — unlikely to hit for normal usage:

  • Gamma: 4,000 requests per 10 seconds (general)
  • CLOB: 9,000 requests per 10 seconds (general)
  • Data: 1,000 requests per 10 seconds (general)

Limitations

  • This skill is read-only — it does not support placing trades
  • Trading requires wallet-based crypto authentication (EIP-712 signatures)
  • Some new markets may have empty price history
  • Geographic restrictions apply to trading but read-only data is globally accessible

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