Clawshi

Kalshi prediction market data via the public REST API, packaged as a drop-in OpenClaw skill.

Installation

Clone or copy this repo directly into your OpenClaw skills/ directory:

cd <your-workspace>/skills
git clone https://github.com/Payo-Systems/Clawshi.git kalshi-market-data

Or into the global skills directory:

cd ~/.openclaw/skills
git clone https://github.com/Payo-Systems/Clawshi.git kalshi-market-data

OpenClaw discovers it automatically on the next session.

Dependencies

No external dependencies. Uses Python stdlib only (urllib.request + json).

Verify

python3 main.py browse --url "https://kalshi.com" --max 3

Optional: openclaw.json

{
  "skills": {
    "entries": {
      "kalshi-market-data": {
        "enabled": true
      }
    }
  }
}

Skill Structure

skill.yaml          # OpenClaw manifest
main.py             # Entrypoint — exposes browse() and market()
SKILL.md            # Skill docs
scripts/
  kalshi_api.py     # REST API client (stdlib only)

Usage

Browse markets by category

python3 main.py browse --url "https://kalshi.com/category/politics" --max 5

Filter by category: politics, economics, crypto, climate, culture, companies, financials, mentions, science. Sports: https://kalshi.com/sports/all-sports.

Fetch a single market

python3 main.py market "https://kalshi.com/markets/kxfed/fed-meeting/kxfed-26mar"

You can also pass a bare event ticker:

python3 main.py market "KXFED-26MAR"

Output

Browse returns a JSON array:

[
  { "title": "Fed decision in March?", "url": "https://kalshi.com/markets/..." }
]

Market returns a JSON object:

{
  "title": "Who will Trump nominate as Fed Chair?",
  "outcomes": [
    { "label": "Kevin Warsh", "price_cents": 98, "raw": "98%" },
    { "label": "Judy Shelton", "price_cents": 2, "raw": "2%" }
  ],
  "status": "ok",
  "error": null
}