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Found 286 Skills
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.
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.
Analyze, describe, read, or extract content from any screenshot, image, photo, picture, pic, snap, screen grab, or screen capture the user shares. Triggers when users ask about images ("what's in this", "what can you see", "what does this show", "what am I looking at", "tell me about this", "can you read this"), request review ("check this", "look at this", "review these", "analyze this"), request extraction ("extract text", "convert to markdown", "transcribe this", "parse this", "pull the data"), or describe attachments ("here's a screenshot", "I pasted this", "see attached"). Works with single or multiple images. Converts UI data into clean, structured markdown.
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.
Find incomplete records, normalize field values in bulk, dedupe with `hubspot objects merge`, and audit custom properties. Builds on `bulk-operations` for JSONL piping and dry-run/digest/confirm.
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.
Shuffle repetitive JSON objects safely by validating schema consistency before randomising entries.
Generate standup talking points from One Horizon task data. Supports personal and team scope. Use when asked "prep my standup", "what should I say", "give me my standup update", "team standup summary", or "what should we cover in standup". Requires One Horizon MCP.