intellectia-stock-screener
✓Verified·Scanned 2/19/2026
Intellectia stock/crypto screener for Bullish/Bearish Tomorrow/Week/Month presets. Calls /gateway/v1/stock/screener-list (no auth) and summarizes results.
from clawhub.ai·vcb111ca·8.3 KB·0 installs
Scanned from 1.0.0 at cb111ca · Transparency log ↗
$ vett add clawhub.ai/xanxustan/intellectia-stock-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, andtrend_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
probabilitydesc. Output:symbol,name,price,change_ratio,probability,profit.” - “Intellectia screener: Stocks Bearish for a Week. Explain what
probabilityandprofitmean, then return a table.” - “Intellectia screener: Cryptos Bullish for a Month. Page 1 size 50. Filter
probability >= 70.” - “Call Intellectia
/gateway/v1/stock/screener-listwithsymbol_type=0 period_type=0 trend_type=0 page=1 size=20and 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 (typically0means success)msg(string): Message (empty string when OK)data(object): Payload
data:
data.list(array): Result rowsdata.total(int): Total number of rowsdata.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 namelogo(string): Logo URLpre_close(number): Previous close priceprice(number): Current pricechange_ratio(number): Percent change vs previous closetimestamp(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 seriesklines[].close(number): Close priceklines[].timestamp(string): Unix seconds
trend_list(array): Trend comparison seriestrend_list[].symbol(string): Symbol for the series (may be empty for non-main series)trend_list[].symbol_type(int): Asset typetrend_list[].is_main(bool): Whether this is the main seriestrend_list[].list(array): Time pointstrend_list[].list[].change_ratio(number): Percent change at that pointtrend_list[].list[].timestamp(string): Unix secondstrend_list[].list[].close(number): Close price at that point
update_time(string): Last update time (Unix seconds)
data.detail:
cover_url(string): Cover image URLname(string): Screener titlescreener_type(int): Screener type IDparams(string): Serialized params (often JSON string)desc(string): Screener descriptionnum(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
sizeand add backoff/retry in client code.