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Found 286 Skills
Elliott Wave Theory Signal Engine — Detects swing points via Zigzag, matches 5-wave impulse structures (1-2-3-4-5) and 3-wave corrective structures (A-B-C), validates with Fibonacci relationships, and generates wave positions, target prices, and risk levels. Triggers: "艾略特波浪", "波浪理论", "推动浪", "调整浪", "斐波那契", "1浪", "3浪", "5浪", "abc浪", "艾略特", "波浪計數", "推動浪", "調整浪", "斐波那契", "Elliott wave", "wave theory", "impulse wave", "corrective wave", "fibonacci retracement", "wave count", "wave 3", "wave 5".
Perform comprehensive exploratory data analysis on scientific data files across 200+ file formats. This skill should be used when analyzing any scientific data file to understand its structure, content, quality, and characteristics. Automatically detects file type and generates detailed markdown reports with format-specific analysis, quality metrics, and downstream analysis recommendations. Covers chemistry, bioinformatics, microscopy, spectroscopy, proteomics, metabolomics, and general scientific data formats.
Find stocks with consensus sentiment across multiple finance YouTubers. Use when looking for stocks that multiple bloggers agree on (bullish or bearish).
Create a custom technical indicator using Numba JIT + NumPy. Generates production-grade, O(n) optimized indicator functions with charting and benchmarking.
Pragmatic qualitative analysis for interview data in sociology research. Guides you through systematic coding, interpretation, and synthesis with quality checkpoints. Supports theory-informed (Track A) or data-first (Track B) approaches.
Expert in high-performance CSV processing, parsing, and data cleaning using Python, DuckDB, and command-line tools. Use when working with CSV files, cleaning data, transforming datasets, or processing large tabular data files.
A fast, extensible progress bar for Python and CLI. Instantly makes your loops show a smart progress meter with ETA, iterations per second, and customizable statistics. Minimal overhead. Use for monitoring long-running loops, simulations, data processing, ML training, file downloads, I/O operations, command-line tools, pandas operations, parallel tasks, and nested progress bars.
Generate a pre-earnings briefing for any stock using Yahoo Finance data. Use this skill whenever the user wants to prepare for an upcoming earnings report, understand what analysts expect, review a company's beat/miss track record, or get a quick overview before an earnings call. Triggers include: "earnings preview for AAPL", "what to expect from TSLA earnings", "MSFT reports next week", "earnings preview", "pre-earnings analysis", "what are analysts expecting for NVDA", "earnings estimates for", "will GOOGL beat earnings", "earnings beat/miss history", "upcoming earnings", "before earnings", "earnings setup", "consensus estimates", "earnings whisper", "EPS expectations", "what's the street expecting", "earnings season preview", any mention of preparing for or previewing an earnings report, or any request to understand expectations ahead of a company's earnings date. Always use this skill when the user mentions a ticker in context of upcoming earnings, even if they don't say "preview" explicitly.
Use Crawl4AI for web crawling, markdown extraction, and LLM-powered structured extraction through OpenRouter. Use when the user mentions Crawl4AI, unclecode/crawl4ai, wants website data extracted with Crawl4AI, or needs an agent to crawl pages and turn them into structured JSON with OpenRouter-backed models.
TransForm integration. Manage data, records, and automate workflows. Use when the user wants to interact with TransForm data.
Compare sentiment and blogger opinions between two stocks. Use when users want to analyze NVDA vs AMD, or any two tickers side by side.
F# functional-first programming on .NET. Use for .fs files.