Skill: xanxustan/ai-screener (version 1.0.0)

--- name: intellectia-stock-screener description: Intellectia stock/crypto screener for Bullish/Bearish Tomorrow/Week/Month presets. Calls /gateway/v1/stock/screener-list (no auth) and summarizes results. metadata: {"openclaw":{"requires":{"bins":["curl","python3"]},"install":[{"id":"python","kind":"pip","package":"requests","bins":[],"label":"Install requests (pip)"}]}} --- # 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: ```bash 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: ```bash 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): ```json { "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 ```bash 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) ```bash 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.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)