A股量化选股扫描器，模型驱动自适应因子评分。通过 Tushare 扫描全 A 股 5000+ 只股票，检测市场环境（波动率、动量、资金面、板块轮动），动态调整因子权重，输出选股榜/异动榜/行业分布的 HTML 报告。适用于 A 股选股、量化筛选、因子分析、市场环境诊断、板块轮动、动量策略、价值投资筛选。Use for Chinese A-share stock screening, quantitative stock picking, sector rotation, market regime detection.
3-layer personality system for AI agents: Yuan (base persona), Ishiki (private self-awareness), Public Ishiki (external behavior rules). Give your agent a consistent character, emotional depth, and safe guest interaction boundaries. Use when: (1) Want agent to have a consistent personality, (2) Agent needs different behavior for owner vs strangers, (3) Building a personal AI companion, (4) Agent responses feel generic and robotic, (5) User says 'be more like...', 'act as...', or wants to customize agent character.
Auto-snapshot workspace before dangerous commands (rm -rf, git clean, git reset --hard). Zero-cost hardlink dedup on macOS/Linux, robocopy mirror on Windows. Use when: (1) About to run destructive file operations, (2) User asks to protect workspace files, (3) Before bulk delete/move operations, (4) User mentions fear of losing files. Also provides snapshot listing and one-command restore.
Click-to-zoom lightbox for chat images, screenshots, and generated visuals. Scroll-wheel zoom (0.5x–5x), drag-to-pan, pinch gesture on mobile, keyboard shortcuts. Zero dependencies — pure CSS + vanilla JS. Use when: (1) Chat contains images the user wants to inspect, (2) Browser screenshots need closer examination, (3) Generated images are too small in the chat bubble, (4) User says 'zoom in' or 'enlarge' about an image.
Persistent cross-session memory system with fact extraction, semantic search, and compiled memory layers. Your agent remembers everything across sessions — user preferences, project context, past decisions, personal details. Use when: (1) User references something from a previous conversation, (2) Agent needs project context it learned before, (3) User says 'remember this' or 'do you remember when...', (4) Starting a new session that should inherit past knowledge, (5) Agent keeps forgetting things between sessions.
Quantitative stock scanner with model-driven adaptive factor scoring. Scans ~100 US large/mid-cap stocks via Finnhub API, detects market regime (volatility, momentum, breadth), dynamically adjusts factor weights, and produces ranked selection/anomaly lists with HTML reports. Use for US stock screening, quantitative stock picking, factor analysis, market regime detection, stock scoring, building a model portfolio, or finding momentum/value/quality plays.
Route different task types to the best-fit model automatically. Chat → fast small model, coding → strong reasoning model, images → vision model, long documents → large context model. Use when: (1) Agent handles mixed tasks (chat + code + vision), (2) Want to optimize speed and cost by matching task to model, (3) User sends an image but current model is text-only, (4) User asks for code review or complex reasoning, (5) User pastes long documents exceeding small model context.
Create distinctive, production-grade frontend interfaces with high design quality. Use this skill when the user asks to build web components, pages, artifacts, posters, or applications (examples include websites, landing pages, dashboards, React components, HTML/CSS layouts, or when styling/beautifying any web UI). Generates creative, polished code and UI design that avoids generic AI aesthetics.