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Documentation Index

Fetch the complete documentation index at: https://docs.simplefunctions.dev/llms.txt

Use this file to discover all available pages before exploring further.

Use this cookbook when you need to assemble live market data into an agent or trading workflow. The Real-Time Data API page lists endpoints. This page shows how to combine them with the CLI and agent APIs. Last live probe: 2026-05-06 UTC, after the data API registry-hydration deploy.

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Tested observations

The live probes produced these operational facts:
ProbeResult
sf discover --quality --json --limit 3Returned ranked opportunities from world, contagion, cross-venue, ideas, and new markets.
sf inspect KXHORMUZWEEKLY-26MAY10-T40 --jsonReturned price, best bid/ask, spread, volume, indicators, regime, contagion, trend, and next actions.
sf book KXHORMUZWEEKLY-26MAY10-T40 --jsonReturned bid/ask levels and depth.
GET /v1/search?q=fed&limit=2Returned autocomplete-grade Polymarket results.
GET /v1/search?q=KXHORMUZWEEKLY-26MAY10-T40&limit=5&strict=0Hydrated and returned the exact Kalshi ticker with score 1000.
GET /v1/markets/KXHORMUZWEEKLY-26MAY10-T40Hydrated and returned Kalshi metadata, last price, best bid/ask, volume, close time, and heat.
GET /v1/movers?window=1h&n=3&minVol=1000Returned live movers, mostly Polymarket in this probe.
GET /v1/orderbook/KXHORMUZWEEKLY-26MAY10-T40Hydrated the market and returned non-empty bids, asks, and ts.
GET /v1/candles/KXHORMUZWEEKLY-26MAY10-T40?tf=1h&limit=5Returned five 1-hour OHLCV candles.
GET /v1/trades/KXHORMUZWEEKLY-26MAY10-T40?limit=5Returned an empty recent-trades array, which is normal when no recent in-memory trade prints are cached.
Interpretation: the data-domain API is the fast feed. Exact Kalshi ticker reads can hydrate markets that were not present in the warm registry. sf inspect and sf book remain the richer analytical fallback because they add regime, indicators, suggestion, and CLI-native receipts.

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Choose the right surface

NeedUse firstFallback
Cold-start candidate listsf discover --quality --jsonGET /v1/movers, GET /v1/search
Ticker autocompleteGET /v1/search?q=...sf query ... --json
Agent world contextsf world --jsonGET /api/agent/world?format=json
One market dossiersf inspect <ticker> --jsonGET /api/agent/inspect/{ticker}
Orderbook depthGET /v1/orderbook/{ticker}sf book <ticker> --json
Fast moversGET /v1/moverssf discover --quality --json
Historical strategy checksf backtest <ticker> ... --jsonstored traces / snapshots
Custom market makingGET /v1/orderbook, GET /v1/trades, WebSocketQuoteEngine paper mode

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Cold-start loop

Start broad: 
sf discover --quality --json --limit 10
Then inspect a candidate: 
sf inspect KXHORMUZWEEKLY-26MAY10-T40 --json
Then pull book depth: 
sf book KXHORMUZWEEKLY-26MAY10-T40 --json
For a service using HTTP only: 
curl "https://simplefunctions.dev/api/agent/world?format=json"
curl "https://simplefunctions.dev/api/agent/inspect/KXHORMUZWEEKLY-26MAY10-T40?format=json"
curl "https://data.simplefunctions.dev/v1/movers?window=1h&n=20&minVol=1000&dir=both"

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Data API cold start

Use data API search and movers before subscribing to individual topics: 
curl "https://data.simplefunctions.dev/v1/search?q=fed&limit=10"
curl "https://data.simplefunctions.dev/v1/movers?window=1h&n=20&minVol=1000&dir=both"
curl "https://data.simplefunctions.dev/v1/snapshot"
Important conventions:
FieldConvention
Data API pricesDecimal probabilities in [0, 1].
CLI pricesUsually cents for human/agent trade surfaces.
generated_atUnix seconds.
tsUnix milliseconds.
Exact Kalshi ticker missThe API attempts direct Kalshi hydration before returning not found or an empty cache.
Empty orderbookUsually invalid ticker, inactive venue book, temporary venue failure, or an actually empty market. Check /v1/markets/{ticker} next.
Empty tradesOften just no recent in-memory trade prints for that process. It is not proof that the market has never traded.

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Coverage contract

The data API has two layers:
LayerWhat it coversHow to use it
Warm registryFast browse, featured, snapshot, movers, and common search.Use for cold start and broad discovery.
Exact-ticker hydrationValid Kalshi tickers that missed the warm registry.Use /v1/markets/{ticker}, /v1/orderbook/{ticker}, /v1/candles/{ticker}, or exact ticker search.
Hydration is intentionally exact-ticker only. Kalshi text search parameters are not reliable enough for arbitrary query fallback, and brute-force loading every active Kalshi market would pull in too much low-signal traffic. For broad discovery, use sf discover, sf query, /v1/search, /v1/movers, and /v1/snapshot.

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Orderbook fallback pattern

When building a market-making or alpha pipeline, use a fallback chain: 
1. Try data API: GET /v1/orderbook/{ticker}
2. If bids/asks empty, call: GET /v1/markets/{ticker}
3. If the market is missing, skip the ticker or re-run discovery.
4. If the market is active but book is empty, call: sf book <ticker> --json
5. If still empty, call: sf inspect <ticker> --json
6. If inspect says market closed, stale, or low liquidity, skip quoting.
7. If inspect says active and book is present, use the API or CLI book as the current snapshot.
Example shell: 
BOOK="$(curl -sS "https://data.simplefunctions.dev/v1/orderbook/KXHORMUZWEEKLY-26MAY10-T40")"
echo "$BOOK"

sf book KXHORMUZWEEKLY-26MAY10-T40 --json
sf inspect KXHORMUZWEEKLY-26MAY10-T40 --json
Keep this distinction in dashboards: “no cached data-domain book” is not the same as “no live market book.”

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WebSocket subscription

Use WebSocket when you have a known ticker set: 
const ws = new WebSocket("wss://app.simplefunctions.dev/ws")

ws.addEventListener("open", () => {
  ws.send(JSON.stringify({
    action: "subscribe",
    topics: [
      "featured",
      "ticker:KXHORMUZWEEKLY-26MAY10-T40",
      "orderbook:KXHORMUZWEEKLY-26MAY10-T40",
      "trade:KXHORMUZWEEKLY-26MAY10-T40",
      "candle:KXHORMUZWEEKLY-26MAY10-T40:1m"
    ]
  }))
})

ws.addEventListener("message", (event) => {
  const frame = JSON.parse(event.data)
  console.log(frame.type, frame)
})
Subscribe only after you have selected markets. For discovery, use discover, movers, search, or snapshot.

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Replay record shape

For custom research, store normalized frames: 
{
  "ts": 1778040615000,
  "source": "sf.book",
  "ticker": "KXHORMUZWEEKLY-26MAY10-T40",
  "venue": "kalshi",
  "bestBid": 57,
  "bestAsk": 59,
  "bidDepth": 5434,
  "askDepth": 7997,
  "levels": {
    "bids": [[57, 209], [56, 228]],
    "asks": [[59, 1], [60, 22]]
  }
}
Store the source because data API, CLI book, inspect, and WebSocket frames have different coverage guarantees.

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Alpha research packet

A practical read-only packet for an agent: 
sf discover --quality --json --limit 10
sf world --delta --json --since 1h
sf inspect <ticker> --json
sf book <ticker> --json
sf backtest <ticker> --entry-below 60 --stop 35 --tp 75 --quantity 5 --days 7 --json
The backtest command is read-only. Treat low dataPoints as a warning that the result is not a full evaluation.

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Market-making packet

Before creating a quote: 
sf inspect <ticker> --json
sf book <ticker> --json
sf quoteengine status --json
sf quote list --json
Only after approval: 
sf quote create <ticker> --paper --spread 3 --size 5 --max-exposure 20 --stop-loss 5
Start with Market making for QuoteEngine operation.

Real-Time Data API

Endpoint reference and WebSocket topics.

Market making

QuoteEngine workflow and operational gates.

Evaluation and replay

How to evaluate agents and strategies from traces and backtests.

World Model

Agent context and delta strategy.