Model

Data vendor / platform: 20 ways to use Ora

Derived signals and event flags as a product, delivered by webhook to clients. Each example is a complete, runnable request with the real answers it returned (49 requests, captured 2026-10-31), what they mean and, where it fits, the action it would send.

Run withAnswers were captured on ora-fin-0.1.1. Another model changes the request JSON and the Playground link; run it there to see its answers.

Rule functions and facts used by this player (64)

ref 10 sma 8 offset 6 rsi 5 ema 3 avg 3 abs 2 pays_dividend 2 adx 2 atr_pct 2 bblower 2 bbmid 2 days_since_split 2 log 2 sqrt 2 std 2 obv 2 atr 2 beat_eps_last 1 beat_revenue_last 1 beat_streak 1 eps_growth_yoy 1 eps_surprise_pct 1 last_earnings_move 1 cut_last 1 days_to_ex_div 1 div_yield_ttm 1 raised_last 1 years_of_growth 1 doji 1 engulfing_bear 1 engulfing_bull 1 evening_star 1 hammer 1 marubozu 1 morning_star 1 shooting_star 1 bbupper 1 macdhist 1 days_to_split 1 last_split_ratio 1 reverse_split_last 1 median 1 percentrank 1 swinghigh 1 swinglow 1 macd 1 macdsignal 1 stochd 1 stochk 1 diminus 1 diplus 1 linreg 1 highest 1 zscore 1 days_to_earnings 1 greatest 1 hl2 1 hlc3 1 least 1 ohlc4 1 tr 1 rec 1 rma 1

Examples 1–10 of 20 · page 1 of 2

Data vendor / platform · example 1

An earnings event-flags feed for clients: NVDA, AAPL, MSFT, AMZN

Deliver a daily row per symbol with exact earnings flags (beat, streak, surprise, reaction) to a client's ingestion endpoint.

ora-fin-0.1.14 symbols, one request each6 questions1 actionworkflow · Mon–Fri at 18:00 ET

ScheduleMon–Fri at 18:00 ET
State4 symbols
Questions6 asked
Answersreal, captured
Actions1 rule · dry run

State

{"symbol":"NVDA"} then AAPL, MSFT, AMZN, one request each. The server fills in the latest completed session.

Questions

`beat`	English → rule	Did the stock beat EPS estimates last quarter?
`beat_rev`	English → rule	Did revenue beat estimates last quarter?
`streak`	rule	`beat_streak >= 4` Beat four quarters in a row
`surprise`	rule	`eps_surprise_pct > 5` EPS beat by more than 5%
`reaction`	rule	`abs(last_earnings_move) > 5` Last earnings move bigger than 5%
`growth`	rule	`eps_growth_yoy > 10` EPS up more than 10% on the year

Answers

Symbol	`beat`rule	`beat_rev`rule	`streak`rule	`surprise`rule	`reaction`rule	`growth`rule	Fired
`NVDA`	0.8591	0.8591	0.9463	0.9463	0.9463	0.9463	`row`
`AAPL`	0.8591	0.8591	0.9463	0.9463	0.9463	0.9463	`row`
`MSFT`	0.8591	0.8591	0.9463	0.0537	0.0537	0.8327	`row`
`AMZN`	0.1409	0.1409	0.0537	0.0537	0.0537	0.0537	`row`

true false not known for rules; forecasts are odds. Hover a column for its question.

Actions

Rules on the answers decide what to send. Each symbol runs its own request, so each one can fire.

beat >= 0→Webhookclient-feed

NVDA 1 of 1 fired · dry run, nothing sent

rowwould send (dry run)Webhook → client-feed

{
  "dataset": "earnings_flags_v1",
  "symbol": "NVDA",
  "as_of": "2026-10-30",
  "beat_eps": 0.8591,
  "beat_revenue": 0.8591,
  "beat_streak_4": 0.9463,
  "surprise_over_5": 0.9463,
  "reaction_over_5": 0.9463,
  "eps_growth_over_10": 0.9463
}

AAPL 1 of 1 fired · dry run, nothing sent

rowwould send (dry run)Webhook → client-feed

{
  "dataset": "earnings_flags_v1",
  "symbol": "AAPL",
  "as_of": "2026-10-30",
  "beat_eps": 0.8591,
  "beat_revenue": 0.8591,
  "beat_streak_4": 0.9463,
  "surprise_over_5": 0.9463,
  "reaction_over_5": 0.9463,
  "eps_growth_over_10": 0.9463
}

MSFT 1 of 1 fired · dry run, nothing sent

rowwould send (dry run)Webhook → client-feed

{
  "dataset": "earnings_flags_v1",
  "symbol": "MSFT",
  "as_of": "2026-10-30",
  "beat_eps": 0.8591,
  "beat_revenue": 0.8591,
  "beat_streak_4": 0.9463,
  "surprise_over_5": 0.0537,
  "reaction_over_5": 0.0537,
  "eps_growth_over_10": 0.8327
}

AMZN 1 of 1 fired · dry run, nothing sent

rowwould send (dry run)Webhook → client-feed

{
  "dataset": "earnings_flags_v1",
  "symbol": "AMZN",
  "as_of": "2026-10-30",
  "beat_eps": 0.1409,
  "beat_revenue": 0.1409,
  "beat_streak_4": 0.0537,
  "surprise_over_5": 0.0537,
  "reaction_over_5": 0.0537,
  "eps_growth_over_10": 0.0537
}

What it means

Session of 2026-10-30, 4 symbols: Did the stock beat EPS estimates last quarter: true for NVDA, AAPL, MSFT of 4. Did revenue beat estimates last quarter: true for NVDA, AAPL, MSFT of 4. Beat four quarters in a row: true for NVDA, AAPL, MSFT of 4. EPS beat by more than 5%: true for NVDA, AAPL of 4. row fired for NVDA, AAPL, MSFT, AMZN.

Each field is an exact fact; a value near one half means not known (for example no estimate on record), which the client should store as null.

As a scheduled workflow (Mon–Fri at 18:00 ET)

Create it under Workflows in the console: it runs these questions for every symbol on the schedule and fires the actions per symbol. The answers above are what one run returned.

{
  "name": "An earnings event-flags feed for clients: NVDA, AAPL, MSFT, AMZN",
  "symbols": "NVDA AAPL MSFT AMZN",
  "days": [
    1,
    2,
    3,
    4,
    5
  ],
  "at_time": "18:00",
  "model": "ora-fin-0.1.1",
  "questions": {
    "beat": {
      "type": "yes_no",
      "instructions": "Did the stock beat EPS estimates last quarter?"
    },
    "beat_rev": {
      "type": "yes_no",
      "instructions": "Did revenue beat estimates last quarter?"
    },
    "streak": {
      "type": "yes_no",
      "ask": "beat_streak >= 4"
    },
    "surprise": {
      "type": "yes_no",
      "ask": "eps_surprise_pct > 5"
    },
    "reaction": {
      "type": "yes_no",
      "ask": "abs(last_earnings_move) > 5"
    },
    "growth": {
      "type": "yes_no",
      "ask": "eps_growth_yoy > 10"
    }
  },
  "actions": [
    {
      "id": "row",
      "when": "beat >= 0",
      "do": "webhook",
      "connection": "client-feed",
      "body": {
        "dataset": "earnings_flags_v1",
        "symbol": "{{symbol}}",
        "as_of": "{{as_of}}",
        "beat_eps": "{{beat}}",
        "beat_revenue": "{{beat_rev}}",
        "beat_streak_4": "{{streak}}",
        "surprise_over_5": "{{surprise}}",
        "reaction_over_5": "{{reaction}}",
        "eps_growth_over_10": "{{growth}}"
      }
    }
  ]
}

Request JSON (NVDA; the others differ only in the symbol)

{
  "model": "ora-fin-0.1.1",
  "state": {
    "symbol": "NVDA"
  },
  "questions": {
    "beat": {
      "type": "yes_no",
      "instructions": "Did the stock beat EPS estimates last quarter?"
    },
    "beat_rev": {
      "type": "yes_no",
      "instructions": "Did revenue beat estimates last quarter?"
    },
    "streak": {
      "type": "yes_no",
      "ask": "beat_streak >= 4"
    },
    "surprise": {
      "type": "yes_no",
      "ask": "eps_surprise_pct > 5"
    },
    "reaction": {
      "type": "yes_no",
      "ask": "abs(last_earnings_move) > 5"
    },
    "growth": {
      "type": "yes_no",
      "ask": "eps_growth_yoy > 10"
    }
  },
  "actions": [
    {
      "id": "row",
      "when": "beat >= 0",
      "do": "webhook",
      "connection": "client-feed",
      "body": {
        "dataset": "earnings_flags_v1",
        "symbol": "{{symbol}}",
        "as_of": "{{as_of}}",
        "beat_eps": "{{beat}}",
        "beat_revenue": "{{beat_rev}}",
        "beat_streak_4": "{{streak}}",
        "surprise_over_5": "{{surprise}}",
        "reaction_over_5": "{{reaction}}",
        "eps_growth_over_10": "{{growth}}"
      }
    }
  ],
  "dry_run": true
}

Response JSON (NVDA, real)

{
  "model": "ora-fin-0.1.1",
  "answers": {
    "beat": {
      "yes_no": 0.8591,
      "rule": "beat_eps_last > 0.5",
      "basis": "pattern"
    },
    "beat_rev": {
      "yes_no": 0.8591,
      "rule": "beat_revenue_last > 0.5",
      "basis": "pattern"
    },
    "streak": {
      "yes_no": 0.9463,
      "rule": "beat_streak >= 4",
      "basis": "rule"
    },
    "surprise": {
      "yes_no": 0.9463,
      "rule": "eps_surprise_pct > 5",
      "basis": "rule"
    },
    "reaction": {
      "yes_no": 0.9463,
      "rule": "abs(last_earnings_move) > 5",
      "basis": "rule"
    },
    "growth": {
      "yes_no": 0.9463,
      "rule": "eps_growth_yoy > 10",
      "basis": "rule"
    }
  },
  "context": {
    "symbol": "NVDA",
    "as_of": "2026-10-30"
  },
  "actions": [
    {
      "id": "row",
      "fired": true,
      "status": "dry_run",
      "do": "webhook",
      "connection": "client-feed",
      "preview": {
        "body": {
          "dataset": "earnings_flags_v1",
          "symbol": "NVDA",
          "as_of": "2026-10-30",
          "beat_eps": 0.8591,
          "beat_revenue": 0.8591,
          "beat_streak_4": 0.9463,
          "surprise_over_5": 0.9463,
          "reaction_over_5": 0.9463,
          "eps_growth_over_10": 0.9463
        }
      }
    }
  ]
}

abs beat_eps_last beat_revenue_last beat_streak eps_growth_yoy eps_surprise_pct last_earnings_move

Try it in the Playground

Data vendor / platform · example 2

Dividend flags dataset: payers, raisers, cutters and ex-dates

Package dividend facts for income-focused clients as a daily dataset.

ora-fin-0.1.14 symbols, one request each6 questions1 action

State4 symbols
Questions6 asked
Answersreal, captured
Actions1 rule · dry run

State

{"symbol":"KO"} then JNJ, PG, O, one request each. The server fills in the latest completed session.

Questions

`pays`	rule	`pays_dividend > 0.5` Pays a dividend
`raised`	rule	`raised_last > 0.5` Raised its last dividend
`cut`	English → rule	Did the stock cut its dividend last time?
`ex`	rule	`days_to_ex_div <= 30` Goes ex-dividend within 30 days
`grower`	rule	`years_of_growth >= 10` Ten years of dividend growth
`yield3`	rule	`div_yield_ttm > 3` Yield above 3%

Answers

Symbol	`pays`rule	`raised`rule	`cut`rule	`ex`rule	`grower`rule	`yield3`rule	Fired
`KO`	0.8591	0.1409	0.1409	0.2049	0.9463	0.0537	`row`
`JNJ`	0.8591	0.1409	0.1409	0.9187	0.9463	0.0648	`row`
`PG`	0.8591	0.1409	0.1409	0.0537	0.9463	0.2091	`row`
`O`	0.8591	0.1409	0.1409	0.0537	0.0537	0.9463	`row`

true false not known for rules; forecasts are odds. Hover a column for its question.

Actions

Rules on the answers decide what to send. Each symbol runs its own request, so each one can fire.

pays >= 0→Webhookclient-feed

KO 1 of 1 fired · dry run, nothing sent

rowwould send (dry run)Webhook → client-feed

{
  "dataset": "dividend_flags_v1",
  "symbol": "KO",
  "as_of": "2026-10-30",
  "pays": 0.8591,
  "raised_last": 0.1409,
  "cut_last": 0.1409,
  "ex_within_30d": 0.2049,
  "growth_10y": 0.9463,
  "yield_over_3": 0.0537
}

JNJ 1 of 1 fired · dry run, nothing sent

rowwould send (dry run)Webhook → client-feed

{
  "dataset": "dividend_flags_v1",
  "symbol": "JNJ",
  "as_of": "2026-10-30",
  "pays": 0.8591,
  "raised_last": 0.1409,
  "cut_last": 0.1409,
  "ex_within_30d": 0.9187,
  "growth_10y": 0.9463,
  "yield_over_3": 0.0648
}

PG 1 of 1 fired · dry run, nothing sent

rowwould send (dry run)Webhook → client-feed

{
  "dataset": "dividend_flags_v1",
  "symbol": "PG",
  "as_of": "2026-10-30",
  "pays": 0.8591,
  "raised_last": 0.1409,
  "cut_last": 0.1409,
  "ex_within_30d": 0.0537,
  "growth_10y": 0.9463,
  "yield_over_3": 0.2091
}

O 1 of 1 fired · dry run, nothing sent

rowwould send (dry run)Webhook → client-feed

{
  "dataset": "dividend_flags_v1",
  "symbol": "O",
  "as_of": "2026-10-30",
  "pays": 0.8591,
  "raised_last": 0.1409,
  "cut_last": 0.1409,
  "ex_within_30d": 0.0537,
  "growth_10y": 0.0537,
  "yield_over_3": 0.9463
}

What it means

Session of 2026-10-30, 4 symbols: Pays a dividend: true for KO, JNJ, PG, O of 4. Raised its last dividend: true for none of 4. Did the stock cut its dividend last time: true for none of 4. Goes ex-dividend within 30 days: true for JNJ of 4. row fired for KO, JNJ, PG, O.

One row per symbol per session, all from the dividend record; clients join it to their own holdings.

Request JSON (KO; the others differ only in the symbol)

{
  "model": "ora-fin-0.1.1",
  "state": {
    "symbol": "KO"
  },
  "questions": {
    "pays": {
      "type": "yes_no",
      "ask": "pays_dividend > 0.5"
    },
    "raised": {
      "type": "yes_no",
      "ask": "raised_last > 0.5"
    },
    "cut": {
      "type": "yes_no",
      "instructions": "Did the stock cut its dividend last time?"
    },
    "ex": {
      "type": "yes_no",
      "ask": "days_to_ex_div <= 30"
    },
    "grower": {
      "type": "yes_no",
      "ask": "years_of_growth >= 10"
    },
    "yield3": {
      "type": "yes_no",
      "ask": "div_yield_ttm > 3"
    }
  },
  "actions": [
    {
      "id": "row",
      "when": "pays >= 0",
      "do": "webhook",
      "connection": "client-feed",
      "body": {
        "dataset": "dividend_flags_v1",
        "symbol": "{{symbol}}",
        "as_of": "{{as_of}}",
        "pays": "{{pays}}",
        "raised_last": "{{raised}}",
        "cut_last": "{{cut}}",
        "ex_within_30d": "{{ex}}",
        "growth_10y": "{{grower}}",
        "yield_over_3": "{{yield3}}"
      }
    }
  ],
  "dry_run": true
}

Response JSON (KO, real)

{
  "model": "ora-fin-0.1.1",
  "answers": {
    "pays": {
      "yes_no": 0.8591,
      "rule": "pays_dividend > 0.5",
      "basis": "rule"
    },
    "raised": {
      "yes_no": 0.1409,
      "rule": "raised_last > 0.5",
      "basis": "rule"
    },
    "cut": {
      "yes_no": 0.1409,
      "rule": "cut_last > 0.5",
      "basis": "pattern"
    },
    "ex": {
      "yes_no": 0.2049,
      "rule": "days_to_ex_div <= 30",
      "basis": "rule"
    },
    "grower": {
      "yes_no": 0.9463,
      "rule": "years_of_growth >= 10",
      "basis": "rule"
    },
    "yield3": {
      "yes_no": 0.0537,
      "rule": "div_yield_ttm > 3",
      "basis": "rule"
    }
  },
  "context": {
    "symbol": "KO",
    "as_of": "2026-10-30"
  },
  "actions": [
    {
      "id": "row",
      "fired": true,
      "status": "dry_run",
      "do": "webhook",
      "connection": "client-feed",
      "preview": {
        "body": {
          "dataset": "dividend_flags_v1",
          "symbol": "KO",
          "as_of": "2026-10-30",
          "pays": 0.8591,
          "raised_last": 0.1409,
          "cut_last": 0.1409,
          "ex_within_30d": 0.2049,
          "growth_10y": 0.9463,
          "yield_over_3": 0.0537
        }
      }
    }
  ]
}

cut_last days_to_ex_div div_yield_ttm pays_dividend raised_last years_of_growth

Try it in the Playground

Data vendor / platform · example 3

Candlestick pattern signals as a product on SPY constituents (AAPL)

Sell a pattern-detection feed: every named pattern, evaluated exactly on the latest bar, for each symbol.

ora-fin-0.1.1AAPL8 questions

StateAAPL
Questions8 asked
Answersreal, captured
Actionsnone

State

{"symbol":"AAPL"} The server fills in the latest completed session.

Questions

`engulf_bull`	rule	`engulfing_bull()` engulfing bull candle: A green body that engulfs yesterday's red body.
`engulf_bear`	rule	`engulfing_bear()` engulfing bear candle: A red body that engulfs yesterday's green body.
`hammer`	rule	`hammer()` hammer candle: Lower wick at least twice the body, upper wick at most 10% of the range, closing below the close five bars back.
`star`	rule	`shooting_star()` shooting star candle: Upper wick at least twice the body, lower wick at most 10% of the range, after a five-bar rise.
`morning`	rule	`morning_star()` morning star candle: A red bar, a small bar (half its body or less) that stays under its close, then a green bar closing above the middle of the first.
`evening`	rule	`evening_star()` evening star candle: A green bar, a small bar that stays above its close, then a red bar closing below the middle of the first.
`doji`	rule	`doji()` doji candle: Body at most 10% of the day's range.
`marubozu`	rule	`marubozu()` marubozu candle: Body at least 90% of the range: almost no wicks.

Answers

Question	Answer	Reading
`engulf_bull` engulfing bull candle: A green body that engulfs yesterday's red body.	0.2066	false
`engulf_bear` engulfing bear candle: A red body that engulfs yesterday's green body.	0.1532	false
`hammer` hammer candle: Lower wick at least twice the body, upper wick at most 10% of the range, closing below the close five bars back.	0.1795	false
`star` shooting star candle: Upper wick at least twice the body, lower wick at most 10% of the range, after a five-bar rise.	0.0537	false
`morning` morning star candle: A red bar, a small bar (half its body or less) that stays under its close, then a green bar closing above the middle of the first.	0.0805	false
`evening` evening star candle: A green bar, a small bar that stays above its close, then a red bar closing below the middle of the first.	0.1612	false
`doji` doji candle: Body at most 10% of the day's range.	0.3343	false
`marubozu` marubozu candle: Body at least 90% of the range: almost no wicks.	0.0537	false

What it means

For AAPL on the session of 2026-10-30: Not true: engulfing bull candle: A green body that engulfs yesterday's red body.; engulfing bear candle: A red body that engulfs yesterday's green body.; hammer candle: Lower wick at least twice the body, upper wick at most 10% of the range, closing below the close five bars back.; shooting star candle: Upper wick at least twice the body, lower wick at most 10% of the range, after a five-bar rise.; morning star candle: A red bar, a small bar (half its body or less) that stays under its close, then a green bar closing above the middle of the first.; evening star candle: A green bar, a small bar that stays above its close, then a red bar closing below the middle of the first.; doji candle: Body at most 10% of the day's range.; marubozu candle: Body at least 90% of the range: almost no wicks..

Pattern answers are exact, so the feed can document each definition once; clients get the same answer the rule engine gives anyone.

Request JSON

{
  "model": "ora-fin-0.1.1",
  "state": {
    "symbol": "AAPL"
  },
  "questions": {
    "engulf_bull": {
      "type": "yes_no",
      "ask": "engulfing_bull()"
    },
    "engulf_bear": {
      "type": "yes_no",
      "ask": "engulfing_bear()"
    },
    "hammer": {
      "type": "yes_no",
      "ask": "hammer()"
    },
    "star": {
      "type": "yes_no",
      "ask": "shooting_star()"
    },
    "morning": {
      "type": "yes_no",
      "ask": "morning_star()"
    },
    "evening": {
      "type": "yes_no",
      "ask": "evening_star()"
    },
    "doji": {
      "type": "yes_no",
      "ask": "doji()"
    },
    "marubozu": {
      "type": "yes_no",
      "ask": "marubozu()"
    }
  }
}

Response JSON (AAPL, real)

{
  "model": "ora-fin-0.1.1",
  "answers": {
    "engulf_bull": {
      "yes_no": 0.2066,
      "rule": "engulfing_bull()",
      "basis": "rule"
    },
    "engulf_bear": {
      "yes_no": 0.1532,
      "rule": "engulfing_bear()",
      "basis": "rule"
    },
    "hammer": {
      "yes_no": 0.1795,
      "rule": "hammer()",
      "basis": "rule"
    },
    "star": {
      "yes_no": 0.0537,
      "rule": "shooting_star()",
      "basis": "rule"
    },
    "morning": {
      "yes_no": 0.0805,
      "rule": "morning_star()",
      "basis": "rule"
    },
    "evening": {
      "yes_no": 0.1612,
      "rule": "evening_star()",
      "basis": "rule"
    },
    "doji": {
      "yes_no": 0.3343,
      "rule": "doji()",
      "basis": "rule"
    },
    "marubozu": {
      "yes_no": 0.0537,
      "rule": "marubozu()",
      "basis": "rule"
    }
  },
  "context": {
    "symbol": "AAPL",
    "as_of": "2026-10-30"
  }
}

doji engulfing_bear engulfing_bull evening_star hammer marubozu morning_star shooting_star

Try it in the Playground

Data vendor / platform · example 4

A technical snapshot API response for MSFT

Answer a client API call with a compact set of trend, momentum and volatility states for one symbol.

ora-fin-0.1.1MSFT6 questions1 action

StateMSFT
Questions6 asked
Answersreal, captured
Actions1 rule · dry run

State

{"symbol":"MSFT"} The server fills in the latest completed session.

Questions

`trend`	rule	`C > ema(C, 20) and ema(C, 20) > sma(C, 50) and sma(C, 50) > sma(C, 200)` Stacked averages: close > 20 EMA > 50 > 200
`adx`	rule	`adx(14) > 25` Trending (ADX above 25)
`rsi`	rule	`rsi(C, 14) > 50` RSI above 50
`macd`	rule	`macdhist(C) > ref(macdhist(C), -1)` MACD histogram rising
`atr`	rule	`atr_pct(14) > 3` A typical day moves more than 3%
`bb`	rule	`(bbupper(C, 20, 2) - bblower(C, 20, 2)) / bbmid(C, 20) < 0.06` Bollinger bands narrower than 6% of price

Answers

Question	Answer	Reading
`trend` Stacked averages: close > 20 EMA > 50 > 200	0.3192	false
`adx` Trending (ADX above 25)	0.3124	false
`rsi` RSI above 50	0.4101	on the line (false)
`macd` MACD histogram rising	0.2073	false
`atr` A typical day moves more than 3%	0.0563	false
`bb` Bollinger bands narrower than 6% of price	0.5745	on the line (true)

Actions

Rules on the answers decide what to send.

trend >= 0→Webhooksnapshot-cache

What each action would send 1 of 1 fired · dry run, nothing sent

cachewould send (dry run)Webhook → snapshot-cache

{
  "symbol": "MSFT",
  "as_of": "2026-10-30",
  "stacked": 0.3192,
  "adx_over_25": 0.3124,
  "rsi_over_50": 0.4101,
  "macd_hist_rising": 0.2073,
  "atr_over_3pct": 0.0563,
  "bb_squeeze": 0.5745
}

What it means

For MSFT on the session of 2026-10-30: Not true: Stacked averages: close > 20 EMA > 50 > 200; Trending (ADX above 25); MACD histogram rising; A typical day moves more than 3%. On the line: RSI above 50; Bollinger bands narrower than 6% of price. Fired: cache (Webhook → snapshot-cache).

The snapshot is deterministic for a given session; caching it per as_of date is safe.

Request JSON

{
  "model": "ora-fin-0.1.1",
  "state": {
    "symbol": "MSFT"
  },
  "questions": {
    "trend": {
      "type": "yes_no",
      "ask": "C > ema(C, 20) and ema(C, 20) > sma(C, 50) and sma(C, 50) > sma(C, 200)"
    },
    "adx": {
      "type": "yes_no",
      "ask": "adx(14) > 25"
    },
    "rsi": {
      "type": "yes_no",
      "ask": "rsi(C, 14) > 50"
    },
    "macd": {
      "type": "yes_no",
      "ask": "macdhist(C) > ref(macdhist(C), -1)"
    },
    "atr": {
      "type": "yes_no",
      "ask": "atr_pct(14) > 3"
    },
    "bb": {
      "type": "yes_no",
      "ask": "(bbupper(C, 20, 2) - bblower(C, 20, 2)) / bbmid(C, 20) < 0.06"
    }
  },
  "actions": [
    {
      "id": "cache",
      "when": "trend >= 0",
      "do": "webhook",
      "connection": "snapshot-cache",
      "body": {
        "symbol": "{{symbol}}",
        "as_of": "{{as_of}}",
        "stacked": "{{trend}}",
        "adx_over_25": "{{adx}}",
        "rsi_over_50": "{{rsi}}",
        "macd_hist_rising": "{{macd}}",
        "atr_over_3pct": "{{atr}}",
        "bb_squeeze": "{{bb}}"
      }
    }
  ],
  "dry_run": true
}

Response JSON (MSFT, real)

{
  "model": "ora-fin-0.1.1",
  "answers": {
    "trend": {
      "yes_no": 0.3192,
      "rule": "C > ema(C, 20) and ema(C, 20) > sma(C, 50) and sma(C, 50) > sma(C, 200)",
      "basis": "rule"
    },
    "adx": {
      "yes_no": 0.3124,
      "rule": "adx(14) > 25",
      "basis": "rule"
    },
    "rsi": {
      "yes_no": 0.4101,
      "rule": "rsi(C, 14) > 50",
      "basis": "rule"
    },
    "macd": {
      "yes_no": 0.2073,
      "rule": "macdhist(C) > ref(macdhist(C), -1)",
      "basis": "rule"
    },
    "atr": {
      "yes_no": 0.0563,
      "rule": "atr_pct(14) > 3",
      "basis": "rule"
    },
    "bb": {
      "yes_no": 0.5745,
      "rule": "(bbupper(C, 20, 2) - bblower(C, 20, 2)) / bbmid(C, 20) < 0.06",
      "basis": "rule"
    }
  },
  "context": {
    "symbol": "MSFT",
    "as_of": "2026-10-30"
  },
  "actions": [
    {
      "id": "cache",
      "fired": true,
      "status": "dry_run",
      "do": "webhook",
      "connection": "snapshot-cache",
      "preview": {
        "body": {
          "symbol": "MSFT",
          "as_of": "2026-10-30",
          "stacked": 0.3192,
          "adx_over_25": 0.3124,
          "rsi_over_50": 0.4101,
          "macd_hist_rising": 0.2073,
          "atr_over_3pct": 0.0563,
          "bb_squeeze": 0.5745
        }
      }
    }
  ]
}

adx atr_pct bblower bbmid bbupper ema macdhist ref rsi sma

Try it in the Playground

Data vendor / platform · example 5

Forecast overlay dataset: odds of moves for index ETFs

Offer clients a separate, clearly labeled forecast dataset next to the exact-signal feed.

ora-fin-0.1.14 symbols, one request each5 questions1 actionworkflow · Mon–Fri at 18:15 ET

ScheduleMon–Fri at 18:15 ET
State4 symbols
Questions5 asked
Answersreal, captured
Actions1 rule · dry run

State

{"symbol":"SPY"} then QQQ, IWM, DIA, one request each. The server fills in the latest completed session.

Questions

`up_week`	forecast	Will the stock be higher in a week? Higher in a week
`drop5`	forecast	Will it drop at least 5% at some point in the next month? A 5% drawdown within a month
`rally5`	forecast	Will it rally at least 5% at some point in the next month? A 5% rally within a month
`vol_up`	forecast	Will volatility be higher over the next month? Higher volatility next month
`big`	forecast	Will there be a big move in either direction in the next 5 days? A big move either way in 5 days

Answers

Symbol	`up_week`forecast	`drop5`forecast	`rally5`forecast	`vol_up`forecast	`big`forecast	Fired
`SPY`	0.598	0.203	0.229	0.69	0.425	`row`
`QQQ`	0.561	0.443	0.501	0.523	0.355	`row`
`IWM`	0.526	0.234	0.285	0.508	0.342	`row`
`DIA`	0.567	0.157	0.186	0.684	0.412	`row`

true false not known for rules; forecasts are odds. Hover a column for its question.

Actions

Rules on the answers decide what to send. Each symbol runs its own request, so each one can fire.

up_week >= 0→Webhookclient-feed

SPY 1 of 1 fired · dry run, nothing sent

rowwould send (dry run)Webhook → client-feed

{
  "dataset": "forecast_overlay_v1",
  "symbol": "SPY",
  "as_of": "2026-10-30",
  "p_up_week": 0.598,
  "p_drop5_month": 0.203,
  "p_rally5_month": 0.229,
  "p_vol_up_month": 0.69,
  "p_big_move_5d": 0.425
}

QQQ 1 of 1 fired · dry run, nothing sent

rowwould send (dry run)Webhook → client-feed

{
  "dataset": "forecast_overlay_v1",
  "symbol": "QQQ",
  "as_of": "2026-10-30",
  "p_up_week": 0.561,
  "p_drop5_month": 0.443,
  "p_rally5_month": 0.501,
  "p_vol_up_month": 0.523,
  "p_big_move_5d": 0.355
}

IWM 1 of 1 fired · dry run, nothing sent

rowwould send (dry run)Webhook → client-feed

{
  "dataset": "forecast_overlay_v1",
  "symbol": "IWM",
  "as_of": "2026-10-30",
  "p_up_week": 0.526,
  "p_drop5_month": 0.234,
  "p_rally5_month": 0.285,
  "p_vol_up_month": 0.508,
  "p_big_move_5d": 0.342
}

DIA 1 of 1 fired · dry run, nothing sent

rowwould send (dry run)Webhook → client-feed

{
  "dataset": "forecast_overlay_v1",
  "symbol": "DIA",
  "as_of": "2026-10-30",
  "p_up_week": 0.567,
  "p_drop5_month": 0.157,
  "p_rally5_month": 0.186,
  "p_vol_up_month": 0.684,
  "p_big_move_5d": 0.412
}

What it means

Session of 2026-10-30, 4 symbols: Highest odds for “Higher in a week”: SPY at 60%. row fired for SPY, QQQ, IWM, DIA.

Forecast fields are probabilities and are shipped in their own dataset so no client mistakes them for exact signals.

As a scheduled workflow (Mon–Fri at 18:15 ET)

Create it under Workflows in the console: it runs these questions for every symbol on the schedule and fires the actions per symbol. The answers above are what one run returned.

{
  "name": "Forecast overlay dataset: odds of moves for index ETFs",
  "symbols": "SPY QQQ IWM DIA",
  "days": [
    1,
    2,
    3,
    4,
    5
  ],
  "at_time": "18:15",
  "model": "ora-fin-0.1.1",
  "questions": {
    "up_week": {
      "type": "yes_no",
      "instructions": "Will the stock be higher in a week?"
    },
    "drop5": {
      "type": "yes_no",
      "instructions": "Will it drop at least 5% at some point in the next month?"
    },
    "rally5": {
      "type": "yes_no",
      "instructions": "Will it rally at least 5% at some point in the next month?"
    },
    "vol_up": {
      "type": "yes_no",
      "instructions": "Will volatility be higher over the next month?"
    },
    "big": {
      "type": "yes_no",
      "instructions": "Will there be a big move in either direction in the next 5 days?"
    }
  },
  "actions": [
    {
      "id": "row",
      "when": "up_week >= 0",
      "do": "webhook",
      "connection": "client-feed",
      "body": {
        "dataset": "forecast_overlay_v1",
        "symbol": "{{symbol}}",
        "as_of": "{{as_of}}",
        "p_up_week": "{{up_week}}",
        "p_drop5_month": "{{drop5}}",
        "p_rally5_month": "{{rally5}}",
        "p_vol_up_month": "{{vol_up}}",
        "p_big_move_5d": "{{big}}"
      }
    }
  ]
}

Request JSON (SPY; the others differ only in the symbol)

{
  "model": "ora-fin-0.1.1",
  "state": {
    "symbol": "SPY"
  },
  "questions": {
    "up_week": {
      "type": "yes_no",
      "instructions": "Will the stock be higher in a week?"
    },
    "drop5": {
      "type": "yes_no",
      "instructions": "Will it drop at least 5% at some point in the next month?"
    },
    "rally5": {
      "type": "yes_no",
      "instructions": "Will it rally at least 5% at some point in the next month?"
    },
    "vol_up": {
      "type": "yes_no",
      "instructions": "Will volatility be higher over the next month?"
    },
    "big": {
      "type": "yes_no",
      "instructions": "Will there be a big move in either direction in the next 5 days?"
    }
  },
  "actions": [
    {
      "id": "row",
      "when": "up_week >= 0",
      "do": "webhook",
      "connection": "client-feed",
      "body": {
        "dataset": "forecast_overlay_v1",
        "symbol": "{{symbol}}",
        "as_of": "{{as_of}}",
        "p_up_week": "{{up_week}}",
        "p_drop5_month": "{{drop5}}",
        "p_rally5_month": "{{rally5}}",
        "p_vol_up_month": "{{vol_up}}",
        "p_big_move_5d": "{{big}}"
      }
    }
  ],
  "dry_run": true
}

Response JSON (SPY, real)

{
  "model": "ora-fin-0.1.1",
  "answers": {
    "up_week": {
      "yes_no": 0.598
    },
    "drop5": {
      "yes_no": 0.203
    },
    "rally5": {
      "yes_no": 0.229
    },
    "vol_up": {
      "yes_no": 0.69
    },
    "big": {
      "yes_no": 0.425
    }
  },
  "context": {
    "symbol": "SPY",
    "as_of": "2026-10-30"
  },
  "actions": [
    {
      "id": "row",
      "fired": true,
      "status": "dry_run",
      "do": "webhook",
      "connection": "client-feed",
      "preview": {
        "body": {
          "dataset": "forecast_overlay_v1",
          "symbol": "SPY",
          "as_of": "2026-10-30",
          "p_up_week": 0.598,
          "p_drop5_month": 0.203,
          "p_rally5_month": 0.229,
          "p_vol_up_month": 0.69,
          "p_big_move_5d": 0.425
        }
      }
    }
  ]
}

Try it in the Playground

Data vendor / platform · example 6

Corporate-action alerts for split adjustments

Tell downstream clients when a symbol split recently or has one announced, so they re-adjust history.

ora-fin-0.1.13 symbols, one request each4 questions1 action

State3 symbols
Questions4 asked
Answersreal, captured
Actions1 rule · dry run

State

{"symbol":"NVDA"} then WMT, AAPL, one request each. The server fills in the latest completed session.

Questions

`recent`	rule	`days_since_split <= 30` split in the last 30 days
`announced`	rule	`days_to_split <= 365` A split is announced
`ratio`	English → rule	Was the last split at least 2-for-1?
`reverse`	rule	`reverse_split_last > 0.5` Last split was a reverse split

Answers

Symbol	`recent`rule	`announced`rule	`ratio`rule	`reverse`rule	Fired
`NVDA`	0.0537	0.0537	0.9463	0.1409	none
`WMT`	0.0537	0.0537	0.9317	0.1409	none
`AAPL`	0.0537	0.0537	0.9463	0.1409	none

true false not known for rules; forecasts are odds. Hover a column for its question.

Actions

Rules on the answers decide what to send. Each symbol runs its own request, so each one can fire.

recent >= 0.6 or announced >= 0.6→Emailclient-ops

NVDA 0 of 1 fired · dry run, nothing sent

WMT 0 of 1 fired · dry run, nothing sent

AAPL 0 of 1 fired · dry run, nothing sent

What it means

Session of 2026-10-30, 3 symbols: split in the last 30 days: true for none of 3. A split is announced: true for none of 3. Was the last split at least 2-for-1: true for NVDA, WMT, AAPL of 3. Last split was a reverse split: true for none of 3. adjust fired for none.

The notice only goes out when a split is recent or announced, and it says which; quiet symbols need no action.

Request JSON (NVDA; the others differ only in the symbol)

{
  "model": "ora-fin-0.1.1",
  "state": {
    "symbol": "NVDA"
  },
  "questions": {
    "recent": {
      "type": "yes_no",
      "ask": "days_since_split <= 30"
    },
    "announced": {
      "type": "yes_no",
      "ask": "days_to_split <= 365"
    },
    "ratio": {
      "type": "yes_no",
      "instructions": "Was the last split at least 2-for-1?"
    },
    "reverse": {
      "type": "yes_no",
      "ask": "reverse_split_last > 0.5"
    }
  },
  "actions": [
    {
      "id": "adjust",
      "when": "recent >= 0.6 or announced >= 0.6",
      "do": "email",
      "connection": "client-ops",
      "subject": "Split adjustment notice: {{symbol}}",
      "message": "{{symbol}} ({{as_of}}): split in the last 30 days {{recent|pct}}, split announced {{announced|pct}}. Re-adjust stored history."
    }
  ],
  "dry_run": true
}

Response JSON (NVDA, real)

{
  "model": "ora-fin-0.1.1",
  "answers": {
    "recent": {
      "yes_no": 0.0537,
      "rule": "days_since_split <= 30",
      "basis": "rule"
    },
    "announced": {
      "yes_no": 0.0537,
      "rule": "days_to_split <= 365",
      "basis": "rule"
    },
    "ratio": {
      "yes_no": 0.9463,
      "rule": "last_split_ratio >= 2",
      "basis": "pattern"
    },
    "reverse": {
      "yes_no": 0.1409,
      "rule": "reverse_split_last > 0.5",
      "basis": "rule"
    }
  },
  "context": {
    "symbol": "NVDA",
    "as_of": "2026-10-30"
  },
  "actions": [
    {
      "id": "adjust",
      "fired": false,
      "status": "skipped"
    }
  ]
}

days_since_split days_to_split last_split_ratio reverse_split_last

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Data vendor / platform · example 7

Market regime labels: trend and volatility for SPY

Publish a daily regime label (trend up or down, volatility calm or high) that clients use to condition their models.

ora-fin-0.1.1SPY5 questions1 action

StateSPY
Questions5 asked
Answersreal, captured
Actions1 rule · dry run

State

{"symbol":"SPY"} The server fills in the latest completed session.

Questions

`trend`	English → rule	Is the stock above its 200-day moving average?
`sma_up`	rule	`sma(C, 200) > ref(sma(C, 200), -20)` The 200-day average is rising
`vol_high`	English → rule	Is 20-day historical volatility above 25%?
`vol5`	English → rule	Is 5-day volatility higher than 20-day volatility?
`vol_next`	forecast	Will volatility be higher over the next month? Higher volatility next month

Answers

Question	Answer	Reading
`trend` Is the stock above its 200-day moving average compiled to `C > sma(C, 200)`	0.9451	true
`sma_up` The 200-day average is rising	0.9463	true
`vol_high` Is 20-day historical volatility above 25% compiled to `std(log(C / C[-1]), 20) * sqrt(20 / 19) * sqrt(252) > 0.25`	0.0537	false
`vol5` Is 5-day volatility higher than 20-day volatility compiled to `std(log(C / C[-1]), 5) * sqrt(5 / 4) > std(log(C / C[-1]), 20) * sqrt(20 / 19)`	0.8872	true
`vol_next` Higher volatility next month	0.69	69% · likely

Actions

Rules on the answers decide what to send.

trend >= 0→Webhookclient-feed

What each action would send 1 of 1 fired · dry run, nothing sent

labelwould send (dry run)Webhook → client-feed

{
  "dataset": "regime_labels_v1",
  "symbol": "SPY",
  "as_of": "2026-10-30",
  "trend_up": 0.9451,
  "sma200_rising": 0.9463,
  "vol_high": 0.0537,
  "vol_expanding": 0.8872,
  "p_vol_up_month": 0.69
}

What it means

For SPY on the session of 2026-10-30: True now: Is the stock above its 200-day moving average; The 200-day average is rising; Is 5-day volatility higher than 20-day volatility. Not true: Is 20-day historical volatility above 25%. Forecasts: Higher volatility next month 69%. Fired: label (Webhook → client-feed).

Clients map the probabilities to labels with their own cutoffs; the vendor ships the raw values so nothing is lost.

Request JSON

{
  "model": "ora-fin-0.1.1",
  "state": {
    "symbol": "SPY"
  },
  "questions": {
    "trend": {
      "type": "yes_no",
      "instructions": "Is the stock above its 200-day moving average?"
    },
    "sma_up": {
      "type": "yes_no",
      "ask": "sma(C, 200) > ref(sma(C, 200), -20)"
    },
    "vol_high": {
      "type": "yes_no",
      "instructions": "Is 20-day historical volatility above 25%?"
    },
    "vol5": {
      "type": "yes_no",
      "instructions": "Is 5-day volatility higher than 20-day volatility?"
    },
    "vol_next": {
      "type": "yes_no",
      "instructions": "Will volatility be higher over the next month?"
    }
  },
  "actions": [
    {
      "id": "label",
      "when": "trend >= 0",
      "do": "webhook",
      "connection": "client-feed",
      "body": {
        "dataset": "regime_labels_v1",
        "symbol": "{{symbol}}",
        "as_of": "{{as_of}}",
        "trend_up": "{{trend}}",
        "sma200_rising": "{{sma_up}}",
        "vol_high": "{{vol_high}}",
        "vol_expanding": "{{vol5}}",
        "p_vol_up_month": "{{vol_next}}"
      }
    }
  ],
  "dry_run": true
}

Response JSON (SPY, real)

{
  "model": "ora-fin-0.1.1",
  "answers": {
    "trend": {
      "yes_no": 0.9451,
      "rule": "C > sma(C, 200)",
      "basis": "comparison"
    },
    "sma_up": {
      "yes_no": 0.9463,
      "rule": "sma(C, 200) > ref(sma(C, 200), -20)",
      "basis": "rule"
    },
    "vol_high": {
      "yes_no": 0.0537,
      "rule": "std(log(C / C[-1]), 20) * sqrt(20 / 19) * sqrt(252) > 0.25",
      "basis": "pattern"
    },
    "vol5": {
      "yes_no": 0.8872,
      "rule": "std(log(C / C[-1]), 5) * sqrt(5 / 4) > std(log(C / C[-1]), 20) * sqrt(20 / 19)",
      "basis": "pattern"
    },
    "vol_next": {
      "yes_no": 0.69
    }
  },
  "context": {
    "symbol": "SPY",
    "as_of": "2026-10-30"
  },
  "actions": [
    {
      "id": "label",
      "fired": true,
      "status": "dry_run",
      "do": "webhook",
      "connection": "client-feed",
      "preview": {
        "body": {
          "dataset": "regime_labels_v1",
          "symbol": "SPY",
          "as_of": "2026-10-30",
          "trend_up": 0.9451,
          "sma200_rising": 0.9463,
          "vol_high": 0.0537,
          "vol_expanding": 0.8872,
          "p_vol_up_month": 0.69
        }
      }
    }
  ]
}

log offset ref sma sqrt std

Try it in the Playground

Data vendor / platform · example 8

Sector breadth proxy across four sector ETFs

Build a breadth number for clients: how many sectors are above their 50-day average today.

ora-fin-0.1.14 symbols, one request each3 questions

State4 symbols
Questions3 asked
Answersreal, captured
Actionsnone

State

{"symbol":"XLK"} then XLF, XLE, XLV, one request each. The server fills in the latest completed session.

Questions

`above50`	rule	`C > sma(C, 50)` Above the 50-day average
`above200`	English → rule	Is the stock above its 200-day moving average?
`momentum`	rule	`C > C[-63]` Higher than three months ago

Answers

Symbol	`above50`rule	`above200`rule	`momentum`rule
`XLK`	0.0776	0.92	0.6105
`XLF`	0.6692	0.919	0.3514
`XLE`	0.9432	0.9463	0.9463
`XLV`	0.9447	0.9463	0.9463

true false not known for rules; forecasts are odds. Hover a column for its question.

What it means

Session of 2026-10-30, 4 symbols: Above the 50-day average: true for XLF, XLE, XLV of 4. Is the stock above its 200-day moving average: true for XLK, XLF, XLE, XLV of 4. Higher than three months ago: true for XLK, XLE, XLV of 4.

Counting true answers across sectors gives breadth; the vendor publishes the count and the per-sector answers behind it.

Request JSON (XLK; the others differ only in the symbol)

{
  "model": "ora-fin-0.1.1",
  "state": {
    "symbol": "XLK"
  },
  "questions": {
    "above50": {
      "type": "yes_no",
      "ask": "C > sma(C, 50)"
    },
    "above200": {
      "type": "yes_no",
      "instructions": "Is the stock above its 200-day moving average?"
    },
    "momentum": {
      "type": "yes_no",
      "ask": "C > C[-63]"
    }
  }
}

Response JSON (XLK, real)

{
  "model": "ora-fin-0.1.1",
  "answers": {
    "above50": {
      "yes_no": 0.0776,
      "rule": "C > sma(C, 50)",
      "basis": "rule"
    },
    "above200": {
      "yes_no": 0.92,
      "rule": "C > sma(C, 200)",
      "basis": "comparison"
    },
    "momentum": {
      "yes_no": 0.6105,
      "rule": "C > C[-63]",
      "basis": "rule"
    }
  },
  "context": {
    "symbol": "XLK",
    "as_of": "2026-10-30"
  }
}

offset sma

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Data vendor / platform · example 9

Unusual volume feed for large caps

Ship a list of symbols with unusual volume today, with the direction of the day.

ora-fin-0.1.13 symbols, one request each5 questions1 action

State3 symbols
Questions5 asked
Answersreal, captured
Actions1 rule · dry run

State

{"symbol":"AAPL"} then TSLA, AMD, one request each. The server fills in the latest completed session.

Questions

`spike`	rule	`V > 2 * ref(avg(V, 20), -1)` Volume more than twice the previous 20-day average
`rank`	rule	`percentrank(V, 50) > 90` Volume in the top tenth of 50 sessions
`up_vol`	rule	`C > C[-1] and V > 1.5 * ref(avg(V, 20), -1)` Up on heavy volume
`down_vol`	rule	`C < C[-1] and V > 1.5 * ref(avg(V, 20), -1)` Down on heavy volume
`median`	rule	`V > 2 * median(V, 20)` volume over twice its 20-day median

Answers

Symbol	`spike`rule	`rank`rule	`up_vol`rule	`down_vol`rule	`median`rule	Fired
`AAPL`	0.2473	0.6232	0.127	0.7841	0.2151	none
`TSLA`	0.0589	0.219	0.1309	0.1309	0.0586	none
`AMD`	0.5394	0.6546	0.0537	0.882	0.6441	`unusual`

true false not known for rules; forecasts are odds. Hover a column for its question.

Actions

Rules on the answers decide what to send. Each symbol runs its own request, so each one can fire.

spike >= 0.6 or median >= 0.6→Webhookclient-feed

AAPL 0 of 1 fired · dry run, nothing sent

TSLA 0 of 1 fired · dry run, nothing sent

AMD 1 of 1 fired · dry run, nothing sent

unusualwould send (dry run)Webhook → client-feed

{
  "dataset": "unusual_volume_v1",
  "symbol": "AMD",
  "as_of": "2026-10-30",
  "spike_vs_mean": 0.5394,
  "spike_vs_median": 0.6441,
  "up_on_volume": 0.0537,
  "down_on_volume": 0.882
}

What it means

Session of 2026-10-30, 3 symbols: Volume more than twice the previous 20-day average: true for none of 3. Volume in the top tenth of 50 sessions: true for AAPL, AMD of 3. Up on heavy volume: true for none of 3. Down on heavy volume: true for AAPL, AMD of 3. unusual fired for AMD.

Only symbols with a true spike rule are delivered; using both mean and median avoids one outlier day hiding the next.

Request JSON (AAPL; the others differ only in the symbol)

{
  "model": "ora-fin-0.1.1",
  "state": {
    "symbol": "AAPL"
  },
  "questions": {
    "spike": {
      "type": "yes_no",
      "ask": "V > 2 * ref(avg(V, 20), -1)"
    },
    "rank": {
      "type": "yes_no",
      "ask": "percentrank(V, 50) > 90"
    },
    "up_vol": {
      "type": "yes_no",
      "ask": "C > C[-1] and V > 1.5 * ref(avg(V, 20), -1)"
    },
    "down_vol": {
      "type": "yes_no",
      "ask": "C < C[-1] and V > 1.5 * ref(avg(V, 20), -1)"
    },
    "median": {
      "type": "yes_no",
      "ask": "V > 2 * median(V, 20)"
    }
  },
  "actions": [
    {
      "id": "unusual",
      "when": "spike >= 0.6 or median >= 0.6",
      "do": "webhook",
      "connection": "client-feed",
      "body": {
        "dataset": "unusual_volume_v1",
        "symbol": "{{symbol}}",
        "as_of": "{{as_of}}",
        "spike_vs_mean": "{{spike}}",
        "spike_vs_median": "{{median}}",
        "up_on_volume": "{{up_vol}}",
        "down_on_volume": "{{down_vol}}"
      }
    }
  ],
  "dry_run": true
}

Response JSON (AAPL, real)

{
  "model": "ora-fin-0.1.1",
  "answers": {
    "spike": {
      "yes_no": 0.2473,
      "rule": "V > 2 * ref(avg(V, 20), -1)",
      "basis": "rule"
    },
    "rank": {
      "yes_no": 0.6232,
      "rule": "percentrank(V, 50) > 90",
      "basis": "rule"
    },
    "up_vol": {
      "yes_no": 0.127,
      "rule": "C > C[-1] and V > 1.5 * ref(avg(V, 20), -1)",
      "basis": "rule"
    },
    "down_vol": {
      "yes_no": 0.7841,
      "rule": "C < C[-1] and V > 1.5 * ref(avg(V, 20), -1)",
      "basis": "rule"
    },
    "median": {
      "yes_no": 0.2151,
      "rule": "V > 2 * median(V, 20)",
      "basis": "rule"
    }
  },
  "context": {
    "symbol": "AAPL",
    "as_of": "2026-10-30"
  },
  "actions": [
    {
      "id": "unusual",
      "fired": false,
      "status": "skipped"
    }
  ]
}

avg median offset percentrank ref

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Data vendor / platform · example 10

Support and resistance proximity flags for TSLA

Deliver whether price sits near its last swing high or low, computed from confirmed pivots only.

ora-fin-0.1.1TSLA5 questions

StateTSLA
Questions5 asked
Answersreal, captured
Actionsnone

State

{"symbol":"TSLA"} The server fills in the latest completed session.

Questions

`near_res`	rule	`C <= swinghigh(5) and C >= 0.97 * swinghigh(5)` Within 3% under the last swing high
`near_sup`	rule	`C >= swinglow(5) and C <= 1.03 * swinglow(5)` Within 3% above the last swing low
`break_res`	rule	`C > swinghigh(5) and C[-1] <= ref(swinghigh(5), -1)` Closed above the last swing high today
`hh_hl`	rule	`(swinghigh(3) > swinghigh(3, 2)) and (swinglow(3) > swinglow(3, 2))` Higher swing highs and higher swing lows
`lower_sh`	rule	`swinghigh(3, 1) < swinghigh(3, 2)` latest swing high lower than the one before

Answers

Question	Answer	Reading
`near_res` Within 3% under the last swing high	0.3262	false
`near_sup` Within 3% above the last swing low	0.0751	false
`break_res` Closed above the last swing high today	0.2918	false
`hh_hl` Higher swing highs and higher swing lows	0.5414	on the line (true)
`lower_sh` latest swing high lower than the one before	0.4586	on the line (false)

What it means

For TSLA on the session of 2026-10-30: Not true: Within 3% under the last swing high; Within 3% above the last swing low; Closed above the last swing high today. On the line: Higher swing highs and higher swing lows; latest swing high lower than the one before.

Pivots are confirmed bars later, so the feed never contains a level that only hindsight could see.

Request JSON

{
  "model": "ora-fin-0.1.1",
  "state": {
    "symbol": "TSLA"
  },
  "questions": {
    "near_res": {
      "type": "yes_no",
      "ask": "C <= swinghigh(5) and C >= 0.97 * swinghigh(5)"
    },
    "near_sup": {
      "type": "yes_no",
      "ask": "C >= swinglow(5) and C <= 1.03 * swinglow(5)"
    },
    "break_res": {
      "type": "yes_no",
      "ask": "C > swinghigh(5) and C[-1] <= ref(swinghigh(5), -1)"
    },
    "hh_hl": {
      "type": "yes_no",
      "ask": "(swinghigh(3) > swinghigh(3, 2)) and (swinglow(3) > swinglow(3, 2))"
    },
    "lower_sh": {
      "type": "yes_no",
      "ask": "swinghigh(3, 1) < swinghigh(3, 2)"
    }
  }
}

Response JSON (TSLA, real)

{
  "model": "ora-fin-0.1.1",
  "answers": {
    "near_res": {
      "yes_no": 0.3262,
      "rule": "C <= swinghigh(5) and C >= 0.97 * swinghigh(5)",
      "basis": "rule"
    },
    "near_sup": {
      "yes_no": 0.0751,
      "rule": "C >= swinglow(5) and C <= 1.03 * swinglow(5)",
      "basis": "rule"
    },
    "break_res": {
      "yes_no": 0.2918,
      "rule": "C > swinghigh(5) and C[-1] <= ref(swinghigh(5), -1)",
      "basis": "rule"
    },
    "hh_hl": {
      "yes_no": 0.5414,
      "rule": "(swinghigh(3) > swinghigh(3, 2)) and (swinglow(3) > swinglow(3, 2))",
      "basis": "rule"
    },
    "lower_sh": {
      "yes_no": 0.4586,
      "rule": "swinghigh(3, 1) < swinghigh(3, 2)",
      "basis": "rule"
    }
  },
  "context": {
    "symbol": "TSLA",
    "as_of": "2026-10-30"
  }
}

offset ref swinghigh swinglow

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Information, not investment advice. Rules answer from the latest completed daily session; forecasts are probabilities. Actions ran as dry runs: nothing was sent. More in Builders: Quant developer, Fintech app builder, Robo-advisor, Broker app, Algo / bot developer, Trading educator / newsletter.

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