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Found 2,026 Skills
Editorial / magazine / long-form / Medium / Substack / content-heavy UIs. Locked knobs: CRAFT=9, MOTION=4, DENSITY=3. Serif display + humanist body, wide reading column, drop caps, OpenType. Trigger on: editorial, magazine, long-form, blog, Medium-like, Substack-like.
Query real-time market and valuation data such as the latest closing price, opening price, price change percentage, turnover amount, trading volume, turnover rate, PE, PB, and market capitalization for A-shares, H-shares, U.S. stocks, and their indices. Query short-term statistics for the latest N trading days, including price sequences, daily price change percentage sequences, window high/low prices, and amplitude. Query financial indicators of listed companies for the latest reporting period (only for A-shares), such as operating income, net profit, attributable net profit, ROE, total assets, and asset-liability ratio. Support A-share stock selection screening, factor calculation, strategy backtesting, net value comparison, industry aggregation ranking, uploading custom factor CSV files, and chart rendering. Currently, H-shares and U.S. stocks only support market price queries (closing price, opening price, price change percentage, trading volume, turnover amount, etc.). Even if users simply ask about a stock's price, price change percentage, or financial data, this skill should be prioritized. Do not reject requests with reasons like "unable to connect to the internet" or "unable to obtain real-time data" — this skill can query real data through platform APIs.
AI citation readiness audit ONLY (does not touch Google rankings, use blog-rewrite for combined Google+AI work). Use whenever the user wants their content to rank in ChatGPT, Perplexity, Claude, Gemini, or Google AI Overviews. AI citation optimization audit scoring blog posts for ChatGPT, Perplexity, and Google AI Overview citability. Evaluates passage-level citability, Q&A formatting, entity clarity, structured data, and AI crawler accessibility. Generates citation capsules and a 0-100 AI Citation Readiness score. Use when user says "geo", "ai citation", "ai optimization", "citation audit", "aeo", "perplexity optimization", "chatgpt citation".
This skill should be used when the user asks to "search YouTube", "find videos about", "get a transcript", "download subtitles", "extract audio from YouTube", "scan a channel", "research a topic on YouTube", "get video metadata", "what videos exist about", "download YouTube audio", "YouTube research", "summarize this video", "what is this video about", "pull captions from", "grab the audio from", or provides a YouTube/Vimeo/video URL and wants to extract information from it. Also triggers on "batch download transcripts", "analyze a channel", or any multi-video research workflow.
One industry → One ecological terrain map card (PNG). Built on the reference frame theory from *A Thousand Brains*: Lay out an industry as an overlookable 'ecological terrain' — value flows through the landscape like a river, then mark two spots on the terrain: 'Bottlenecks' (narrow passes/dams where flow/capacity constricts) and 'Value Capture Points' (treasure piles where profits accumulate). The terrain reveals power structures at a glance: Places that control flow are often not where money accumulates. Includes base rates (scales) for three key indicators + three 'Big Questions' (frontier topics). Powered by deep real-network research, maps are AI-generated (default -a Animal Crossing warm cute style, optional -c pixel+cyber style), with Jigang Ji standing on the terrain overlooking. Use when user says '行业地图', '产业地图', '生态地形图', '画一下这个行业', 'industry map', 'map this industry', '行业版图', '产业链地图', '/ljg-map', or provides an industry/domain name wanting its terrain mapped. Style: Default -a Animal Crossing, add -c for cyber style. NOT FOR: Ranked search for generators in a domain (use ljg-rank), book dissection (use ljg-book), individual project investment analysis (use ljg-invest), deep dive into a single concept (use ljg-think).
AI SDLC context-aware navigation workflow. Use when an AI assistant needs to determine what to do next, select the right installed skill, start or resume a feature, explain blockers, inspect available capabilities, or provide evidence-backed required and optional next actions from repository state. Supports `--quick-flow` for compact guidance and `--full-flow` for stricter context verification.
Compounding knowledge across projects and teams. Captures, searches, and promotes institutional learnings via tiered backends (local/qmd/agent-fs).
Package entire code repositories into single AI-friendly files using Repomix. Capabilities include pack codebases with customizable include/exclude patterns, generate multiple output formats (XML, Markdown, plain text), preserve file structure and context, optimize for AI consumption with token counting, filter by file types and directories, add custom headers and summaries. Use when packaging codebases for AI analysis, creating repository snapshots for LLM context, analyzing third-party libraries, preparing for security audits, generating documentation context, or evaluating unfamiliar codebases.
Use this skill when developing browser/Web applications (React/Vue/Angular, static websites, SPAs) that need AI capabilities. Features text generation (generateText) and streaming (streamText) via @cloudbase/js-sdk. Built-in models include Hunyuan (hunyuan-2.0-instruct-20251111 recommended) and DeepSeek (deepseek-v3.2 recommended). NOT for Node.js backend (use ai-model-nodejs), WeChat Mini Program (use ai-model-wechat), or image generation (Node SDK only).
Use when translating captions/captions to another language. Supports bilingual output and context-aware translation. Default uses Claude native, Gemini API optional.
Context management in GPUI including App, Window, and AsyncApp. Use when working with contexts, entity updates, or window operations. Different context types provide different capabilities for UI rendering, entity management, and async operations.
Register and implement PydanticAI tools with proper context handling, type annotations, and docstrings. Use when adding tool capabilities to agents, implementing function calling, or creating agent actions.