Intellectia Stock Screener

Fetch and summarize Intellectia “Screener List” results for stock/crypto screening.

When to use this skill

Use this skill when you want to:

Get the latest bullish/bearish screener candidates for stocks or crypto
Use the built-in preset pick-lists (below) as your “stock/crypto picking tools”
Convert a preset into exact API query parameters (symbol_type, period_type, trend_type)
Summarize/compare results using probability, profit, price, change_ratio, klines, and trend_list

Presets (UI list mapping)

Pick one preset name and run it (this is the easiest way to use the skill):

|---|---:|---:|---:|

| Stocks Bullish Tomorrow | 0 | 0 | 0 |

| Stocks Bearish Tomorrow | 0 | 0 | 1 |

| Stocks Bullish for a Week | 0 | 1 | 0 |

| Stocks Bearish for a Week | 0 | 1 | 1 |

| Stocks Bullish for a Month | 0 | 2 | 0 |

| Stocks Bearish for a Month | 0 | 2 | 1 |

| Cryptos Bullish Tomorrow | 2 | 0 | 0 |

| Cryptos Bearish Tomorrow | 2 | 0 | 1 |

| Cryptos Bullish for a Week | 2 | 1 | 0 |

| Cryptos Bearish for a Week | 2 | 1 | 1 |

| Cryptos Bullish for a Month | 2 | 2 | 0 |

| Cryptos Bearish for a Month | 2 | 2 | 1 |

Preset descriptions (copy-ready)

Stocks Bullish Tomorrow: This list highlights stocks expected to rise, identified by our AI algorithm. It analyzes market-wide price data to spot those most likely to continue an uptrend, based on similarity to proven bullish patterns.
Stocks Bearish Tomorrow: This list highlights stocks expected to fall, identified by our AI algorithm. It analyzes market-wide price data to spot those most likely to continue a downtrend, based on similarity to proven bearish patterns.

How to ask (high hit-rate)

If you want OpenClaw to automatically pick this skill, include:

The word Intellectia or screener (or “bullish/bearish”, “stock screener”, “crypto screener”)
One preset name from the table above (recommended)
Your output requirements (top N, sort, fields)

If you want to force it, use:

/skill intellectia-stock-screener <your request>

Copy-ready prompts:

“Intellectia screener: Stocks Bullish Tomorrow. Top 10 by probability desc. Output: symbol,name,price,change_ratio,probability,profit.”
“Intellectia screener: Stocks Bearish for a Week. Explain what probability and profit mean, then return a table.”
“Intellectia screener: Cryptos Bullish for a Month. Page 1 size 50. Filter probability >= 70.”
“Call Intellectia /gateway/v1/stock/screener-list with symbol_type=0 period_type=0 trend_type=0 page=1 size=20 and return raw JSON.”

Tool configuration

| Tool | Purpose | Configuration |

|---|---|---|

| curl | Quick one-off requests | Use the full URL + query string |

| python3 | Repeatable scripts | Use requests and parse data.list |

| requests | HTTP client library | pip install requests |

Using this skill in OpenClaw

Install into the current workspace:

clawhub install intellectia-stock-screener

Start a new OpenClaw session so the agent picks it up (skills are snapshotted at session start).

Verify it is visible/eligible:

openclaw skills list
openclaw skills info intellectia-stock-screener
openclaw skills check

Endpoint

Base URL: https://api.intellectia.ai
GET /gateway/v1/stock/screener-list

Query parameters

| Name | Type | Meaning |

|---|---|---|

| symbol_type | int | Asset type: 0=stock 1=etf 2=crypto |

| period_type | int | Period: 0=day 1=week 2=month |

| trend_type | int | Trend: 0=bullish 1=bearish |

| profit_asc | bool | Sort by profit ascending (true = small → large) |

| market_cap | int | Market cap filter: 0=any 1=micro(<300M) 2=small(300M-2B) 3=mid(2B-10B) 4=large(10B-200B) 5=mega(>200B) |

| price | int | Price filter: 0=any 1=<5 2=<50 3=>5 4=>50 5=5-50 |

| page | int | Page number (example: 1) |

| size | int | Page size (example: 20) |

Response (200)

Example response (shape):

{
  "ret": 0,
  "msg": "",
  "data": {
    "list": [
      {
        "code": "BKD.N",
        "symbol": "BKD",
        "symbol_type": 0,
        "name": "Brookdale Senior Living Inc",
        "logo": "https://intellectia-public-documents.s3.amazonaws.com/image/logo/BKD_logo.png",
        "pre_close": 14.5,
        "price": 15,
        "change_ratio": 3.45,
        "timestamp": "1769749200",
        "simiar_num": 10,
        "probability": 80,
        "profit": 5.27,
        "klines": [{ "close": 15, "timestamp": "1769749200" }],
        "trend_list": [
          {
            "symbol": "BKD",
            "symbol_type": 0,
            "is_main": true,
            "list": [{ "change_ratio": 5.27, "timestamp": "1730260800", "close": 16 }]
          }
        ],
        "update_time": "1769806800"
      }
    ],
    "total": 3,
    "detail": {
      "cover_url": "https://d159e3ysga2l0q.cloudfront.net/image/cover_image/stock-1.png",
      "name": "Stocks Bullish Tomorrow",
      "screener_type": 1011,
      "params": "{}",
      "desc": "..."
    }
  }
}

Field reference

Top-level:

ret (int): Status code (typically 0 means success)
msg (string): Message (empty string when OK)
data (object): Payload

data:

data.list (array): Result rows
data.total (int): Total number of rows
data.detail (object): Screener metadata

Each item in data.list:

code (string): Full instrument code (may include exchange suffix, e.g. BKD.N)
symbol (string): Ticker symbol (e.g. BKD)
symbol_type (int): Asset type (0=stock 1=etf 2=crypto)
name (string): Display name
logo (string): Logo URL
pre_close (number): Previous close price
price (number): Current price
change_ratio (number): Percent change vs previous close
timestamp (string): Quote timestamp (Unix seconds)
simiar_num (int): Similarity count (as returned by API; spelling kept as-is)
probability (int): Model confidence (0-100)
profit (number): Predicted/expected return (as returned by API)
klines (array): Price series

- klines[].close (number): Close price

- klines[].timestamp (string): Unix seconds

trend_list (array): Trend comparison series

- trend_list[].symbol (string): Symbol for the series (may be empty for non-main series)

- trend_list[].symbol_type (int): Asset type

- trend_list[].is_main (bool): Whether this is the main series

- trend_list[].list (array): Time points

- trend_list[].list[].change_ratio (number): Percent change at that point

- trend_list[].list[].timestamp (string): Unix seconds

- trend_list[].list[].close (number): Close price at that point

update_time (string): Last update time (Unix seconds)

data.detail:

cover_url (string): Cover image URL
name (string): Screener title
screener_type (int): Screener type ID
params (string): Serialized params (often JSON string)
desc (string): Screener description
num (int, optional): As returned by API (may be absent)

Examples

cURL

curl -sS "https://api.intellectia.ai/gateway/v1/stock/screener-list?symbol_type=0&period_type=0&trend_type=0&profit_asc=false&market_cap=0&price=0&page=1&size=20"

Python (requests)

python3 - <<'PY'
import requests

base_url = "https://api.intellectia.ai"
params = {
  "symbol_type": 0,
  "period_type": 0,
  "trend_type": 0,
  "profit_asc": False,
  "market_cap": 0,
  "price": 0,
  "page": 1,
  "size": 20,
}

r = requests.get(f"{base_url}/gateway/v1/stock/screener-list", params=params, timeout=30)
r.raise_for_status()
payload = r.json()

print("ret:", payload.get("ret"))
print("msg:", payload.get("msg"))
data = payload.get("data") or {}
rows = data.get("list") or []
print("total:", data.get("total"))
for row in rows[:10]:
  print(row.get("symbol"), row.get("price"), row.get("change_ratio"), row.get("probability"), row.get("profit"))
PY

Notes

No authentication required.
If you see rate limits, reduce size and add backoff/retry in client code.