Kalshi exchange mechanics — RSA-PSS auth, order schema, YES/NO orderbook convention, WebSocket, and endpoint surface. Market-type-agnostic shared layer for all Kalshi skills.
npx skills add https://github.com/agiprolabs/claude-trading-skills --skill kalshi-api
CFTC-regulated US event exchange. USD-denominated binary contracts settle at $1.00 (YES wins) or $0.00 (NO wins). REST + WebSocket, RSA-PSS authentication on every request.
For contract semantics and settlement rules, see the kalshi-weather-markets and kalshi-crypto-index-markets skills. For strategy, sizing, and backtesting, see prediction-market-strategy.
> VERIFY BEFORE CODING.
> The Kalshi API has broken backward compatibility before: the host changed (old trading-api.kalshi.com → dead), and the order schema changed (integer cents → dollar strings). Always smoke-test signing and order bodies against a live response before shipping.
>
> Canonical sources:
> - API reference: <https://docs.kalshi.com> (legacy mirror: <https://trading-api.readme.io>)
> - Official Python starter: <https://github.com/Kalshi/kalshi-starter-code-python>
https://api.elections.kalshi.com/trade-api/v2demo-api.kalshi.co) has a near-empty book; use production even for read-only pullsKALSHI_KEY_ID=<your-key-uuid>
KALSHI_PRIVATE_KEY_PATH=~/.kalshi/private.pem
Generate the key in the Kalshi dashboard. Store secrets in environment variables or a secrets manager — never in code.
pip install httpx cryptography
The host and signature format are where implementations break. Three common failures:
trading-api.kalshi.com host → 401import os, time, base64, httpx
from cryptography.hazmat.primitives import hashes, serialization
from cryptography.hazmat.primitives.asymmetric import padding
BASE = "https://api.elections.kalshi.com/trade-api/v2"
KEY_ID = os.environ["KALSHI_KEY_ID"]
with open(os.environ["KALSHI_PRIVATE_KEY_PATH"], "rb") as f:
PRIV = serialization.load_pem_private_key(f.read(), password=None)
def _headers(method: str, path: str) -> dict:
"""path must include /trade-api/v2 prefix and exclude query string."""
ts = str(int(time.time() * 1000)) # milliseconds
msg = f"{ts}{method}{path}".encode()
sig = PRIV.sign(
msg,
padding.PSS(mgf=padding.MGF1(hashes.SHA256()),
salt_length=padding.PSS.DIGEST_LENGTH),
hashes.SHA256(),
)
return {
"KALSHI-ACCESS-KEY": KEY_ID,
"KALSHI-ACCESS-TIMESTAMP": ts,
"KALSHI-ACCESS-SIGNATURE": base64.b64encode(sig).decode(),
}
def get(path: str, params=None):
# Sign the path only — query goes into params, not the signature
r = httpx.get(BASE + path, params=params,
headers=_headers("GET", "/trade-api/v2" + path))
r.raise_for_status()
return r.json()
def post(path: str, body: dict):
r = httpx.post(BASE + path, json=body,
headers=_headers("POST", "/trade-api/v2" + path))
r.raise_for_status()
return r.json()
# Example: open markets in a series
markets = get("/markets", params={"series_ticker": "KXHIGHNY", "status": "open"})
Signature spec: RSA-PSS, MGF1 over SHA-256, salt length = PSS.DIGEST_LENGTH. String to sign: {timestamp_ms}{METHOD}{path} where path includes /trade-api/v2 and excludes the query string.
Headers: KALSHI-ACCESS-KEY (UUID), KALSHI-ACCESS-TIMESTAMP (ms), KALSHI-ACCESS-SIGNATURE (base64).
# Returns OHLC for yes_bid / yes_ask + volume + open_interest
# Values are dollar strings: {"close": "0.42"}
candles = get(
f"/series/KXHIGHNY/markets/{ticker}/candlesticks",
params={"start_ts": start_epoch, "end_ts": end_epoch, "period_interval": 60},
)
period_interval is in minutes: 1, 60, or 1440.
On Kalshi, yes and no are both resting BID ladders — there is no separate ask book. To take the other side you lift the opposing bid:
no_ask = 1 − best_yes_bid # cost to buy NO right now (lift YES bids)
yes_ask = 1 − best_no_bid # cost to buy YES right now (lift NO bids)
P(YES) mid = (best_yes_bid + (1 − best_no_bid)) / 2
Getting this backwards silently inverts every signal. Use the helpers in scripts/kalshi_orderbook.py.
Orderbook response comes in two variants depending on API tier — normalize before using:
{"orderbook": {"yes": [[price, size], ...], "no": [[price, size], ...]}}
If a price value is > 1.0, it is integer cents — divide by 100.
POST /trade-api/v2/portfolio/orders uses fixed-point dollar STRINGS, not integers. The old schema (integer cents, count, yes_price) returns 400 invalid_parameters.
{
"ticker": "KXHIGHNY-26JUN02-B75.5",
"action": "buy",
"side": "yes",
"count_fp": "1.00",
"yes_price_dollars": "0.01",
"client_order_id": "my-strategy-001",
"time_in_force": "good_till_canceled"
}
Critical field rules — each violation returns 400:
| Field | Rule | Common mistake that 400s |
|---|---|---|
| count_fp | fixed-point string "1.00" | integer count: 1 |
| {side}_price_dollars | dollar string "0.01" | integer cents yes_price: 1 |
| time_in_force | required: good_till_canceled \| immediate_or_cancel \| fill_or_kill | omitted |
| client_order_id | [A-Za-z0-9-] only | . or : in the string — bracket tickers contain ., so never copy the ticker directly |
| type | do not send | "type": "limit" |
For the full order lifecycle (amend, decrease, cancel, batch) and strike_type gotchas, see references/auth-and-orders.md.
| Category | Endpoint | Notes |
|---|---|---|
| Balance | GET /portfolio/balance | — |
| Positions | GET /portfolio/positions | — |
| Orders | GET /portfolio/orders | ?status=resting\|canceled\|executed |
| Place order | POST /portfolio/orders | dollar-string schema above |
| Cancel | DELETE /portfolio/orders/{id} | returns {"order": {...status: "canceled"}} |
| Amend | POST /portfolio/orders/{id}/amend | ticker required in body |
| Decrease | POST /portfolio/orders/{id}/decrease | {"reduce_by_fp": "1.00"} |
| Batch | POST /portfolio/orders/batched | {"orders": [...]} |
| Fills | GET /portfolio/fills | ?limit=N |
| Settlements | GET /portfolio/settlements | ?limit=N |
| Markets | GET /markets | ?series_ticker=&status=open&limit=500 |
| Orderbook | GET /markets/{ticker}/orderbook | ?depth=N |
| Candlesticks | GET /series/{series}/markets/{ticker}/candlesticks | ?start_ts=&end_ts=&period_interval=60 |
| Trades | GET /markets/trades | recent trade prints |
Full endpoint surface, market metadata fields, and rate limits: references/endpoints-and-marketdata.md.
WebSocket discovery pipeline: references/websocket.md.
references/auth-and-orders.md — RSA-PSS spec, dollar-string order schema, time_in_force, client_order_id sanitization, amend/decrease/cancel lifecycle, strike_type gotcha, feesreferences/endpoints-and-marketdata.md — Full endpoint table, orderbook variants, market metadata fields (result, open_time, close_time, series_ticker), candlesticks, rate limitsreferences/websocket.md — WS host, discovery pipeline, channels, signing the WS upgradescripts/kalshi_orderbook.py — YES/NO bid-ladder helpers (no_ask, yes_ask, p_yes_mid, overround, kalshi_fee). Pure stdlib, no keys, runs offline.Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).
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Take agiprolabs/kalshi-api from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.
The instructions reference pip.
Without those the skill loads but fails at the first command.