SkillHub

ai-screener

v1.0.0

Intellectia stock/crypto screener for Bullish/Bearish Tomorrow/Week/Month presets. Calls /gateway/v1/stock/screener-list (no auth) and summarizes results.

Sourced from ClawHub, Authored by xanxustan

Installation

Please help me install the skill `ai-screener` from SkillHub official store. npx skills add xanxustan/ai-screener

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):

Preset (UI name) symbol_type period_type trend_type
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.