intellectia-stock-screener_skill

Overview

This skill fetches stock screener results from the Intellectia public API and produces compact summaries of the returned data. It retrieves screener metadata and paginated lists of instruments, then extracts key fields like price, change ratio, probability, and predicted profit. The skill is designed for quick integration into monitoring tools, dashboards, or automation scripts that need screener snapshots without authentication.

How this skill works

The skill calls GET /gateway/v1/stock/screener-list with optional query parameters (symbol_type, period_type, trend_type, profit_asc, market_cap, price, page, size). It parses the JSON response, validates top-level fields (ret, msg, data) and iterates data.list to collect instrument summaries and screener detail. The output highlights top rows, counts total results, and converts timestamps to human-friendly form if requested.

When to use it

• You want a lightweight, no-auth snapshot of Intellectia screener results for stocks, ETFs, or crypto.
• You need to embed screener data into a dashboard or alerting pipeline periodically.
• You want to compare model probability, predicted profit, and recent price change across a set.
• You need paginated access to large screener results with configurable filters and sorting.

Best practices

• Limit page size and add exponential backoff if you encounter rate limits.
• Filter by symbol_type, market_cap, price and trend_type to reduce payload and focus results.
• Validate ret == 0 and handle empty or partial data.list gracefully.
• Use probability and profit together to prioritize candidates; treat single-day signals as short-term.

Example use cases

• Daily job that fetches bullish screeners (trend_type=0) for small-cap stocks and alerts high-probability picks.
• Dashboard widget showing top 10 screener rows with price, change_ratio, probability, and profit.
• Automated comparator that pulls trend_list series to find similar instruments and cluster signals.
• Research export that pages through results and saves code, name, price series (klines) for backtesting.