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stock screener

by xanxustan · GitHub ↗ · v1.0.0
cross-platform ✓ Security Clean
1842
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Install in OpenClaw
/install ai-screener
Description
Intellectia stock/crypto screener for Bullish/Bearish Tomorrow/Week/Month presets. Calls /gateway/v1/stock/screener-list (no auth) and summarizes results.
README (SKILL.md)

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 \x3Cyour 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(\x3C300M) 2=small(300M-2B) 3=mid(2B-10B) 4=large(10B-200B) 5=mega(>200B)
price int Price filter: 0=any 1=\x3C5 2=\x3C50 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 - \x3C\x3C'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.
Usage Guidance
This skill is internally coherent: it simply makes unauthenticated requests to api.intellectia.ai and summarizes the JSON. Before installing, confirm you are comfortable with the agent making outbound HTTP calls to api.intellectia.ai and any CDNs linked in responses (logos/images). If you require stricter supply-chain controls, consider pinning the 'requests' version in the install spec. No credentials are requested, and the skill does not read local files per the provided instructions.
Capability Analysis
Type: OpenClaw Skill Name: ai-screener Version: 1.0.0 The OpenClaw AgentSkills skill bundle 'ai-screener' is designed to fetch stock/crypto screener data from the `https://api.intellectia.ai/gateway/v1/stock/screener-list` endpoint. The `SKILL.md` file clearly outlines its purpose, required tools (`curl`, `python3`, `requests`), and provides examples for API interaction. There is no evidence of data exfiltration, malicious execution (e.g., `curl|bash`), persistence mechanisms, or prompt injection attempts against the agent to perform actions outside its stated purpose. All instructions and code examples are directly related to querying the specified external API for financial data.
Capability Assessment
Purpose & Capability
The name/description say it will call Intellectia's /gateway/v1/stock/screener-list and summarize results. The declared binaries (curl, python3) and installing the Python requests package directly support that behavior and are proportionate.
Instruction Scope
SKILL.md instructs only to call the specified API endpoint, map presets to query parameters, and summarize fields from the returned JSON. It does not instruct reading local files, accessing unrelated environment variables, or exfiltrating data to third-party endpoints beyond the documented api.intellectia.ai (logos/images in responses may point to external CDNs).
Install Mechanism
Install uses pip to install the 'requests' package (no version pinned). This is a common, low-risk install for a Python-based HTTP client, but installing unpinned PyPI packages can introduce supply-chain changes; consider pinning a known-good version if you require stricter reproducibility.
Credentials
The skill declares no required environment variables, no credentials, and no config paths. That is appropriate given the documented behavior (unauthenticated GET calls to api.intellectia.ai).
Persistence & Privilege
The skill is not always-enabled and does not request persistent system-wide privileges. It does not modify other skills or agent-wide configs according to the provided instructions.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install ai-screener
  3. After installation, invoke the skill by name or use /ai-screener
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Initial release of Intellectia Stock Screener skill: - Fetches and summarizes stock/crypto screener results from Intellectia API with bullish/bearish presets for tomorrow, week, or month. - Offers easy-to-use preset pick-lists for common screening queries (e.g., "Stocks Bullish Tomorrow"). - Returns key financial fields such as probability, profit, price, and change ratio. - Supports both cURL and Python/requests for querying the API. - Includes example prompts and full API usage documentation for fast onboarding.
Metadata
Slug ai-screener
Version 1.0.0
License
All-time Installs 2
Active Installs 2
Total Versions 1
Frequently Asked Questions

What is stock screener?

Intellectia stock/crypto screener for Bullish/Bearish Tomorrow/Week/Month presets. Calls /gateway/v1/stock/screener-list (no auth) and summarizes results. It is an AI Agent Skill for Claude Code / OpenClaw, with 1842 downloads so far.

How do I install stock screener?

Run "/install ai-screener" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is stock screener free?

Yes, stock screener is completely free (open-source). You can download, install and use it at no cost.

Which platforms does stock screener support?

stock screener is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created stock screener?

It is built and maintained by xanxustan (@xanxustan); the current version is v1.0.0.

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