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Found 961 Skills
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.
Generate professional presentations with AI-generated images. Use when asked to create a deck, presentation, pitch deck, or slides. Supports style presets (whiteboard, corporate, minimalist, etc). Uses Imagen 4.0 API for image generation and Google Slides API for assembly. Produces full decks from markdown content specs in minutes.
Set up Jetty for the first time. Guides the user through account creation, API key configuration, and introduces runbooks — human-readable markdown files that tell an agent how to accomplish multi-step tasks with measurable outcomes. Use this skill whenever the user wants to set up, configure, or get started with Jetty — including 'set up jetty', 'configure jetty', 'jetty setup', 'get started with jetty', 'install jetty', 'connect to jetty', 'jetty onboarding', 'I am new to jetty', 'how do I start with jetty', or even just 'jetty' if they do not appear to have a token yet. Also trigger if the user mentions needing an API key for Jetty or storing their OpenAI/Gemini key in Jetty.
GPU Code to Ascend NPU Adaptation Review Expert. When users need to migrate GPU-based code (especially deep learning and model inference-related code) to Huawei Ascend NPU, this skill must be used for comprehensive review. This skill can identify bottlenecks in GPU-to-NPU migration, write adaptation scripts, generate verification plans, and output a complete Markdown review report. Trigger scenarios include: users mentioning keywords such as "NPU adaptation", "Ascend migration", "GPU to NPU", "Ascend", "CANN", "model migration", "operator adaptation", or users requesting to review GPU code repositories and migrate to the NPU platform.
Polish and elevate MBA thesis/dissertation to the quality of National Excellent Thesis. Conduct comprehensive enhancements in academic language, argument structure, logical rigor, innovation highlights, and formatting. Input: Markdown-formatted thesis text. Output: fully polished complete text. This service is also triggered when the user mentions terms such as "thesis polishing", "MBA thesis", "excellent thesis", "thesis polish", "dissertation improvement", "academic polishing".
Use Parallel's parallel-cli to do live web search, URL extraction (clean markdown), deep research reports, bulk data enrichment (CSV/JSON), FindAll entity discovery, and web monitoring. Use when the user asks to look something up online, needs current sources/citations, provides URLs to read or summarise, requests deep/exhaustive research, wants to enrich a dataset with web-sourced fields, wants a list of entities (companies/people/places), or wants to monitor the web for changes over time.
Review content files against a project's voice and style guidelines. Use when reviewing written content (MDX, markdown, copy) for tone, sentence structure, word choice, and bilingual policy compliance before committing. Triggers on "review voice", "check tone", "voice review", "content review", "does this match our voice", or after writing loop/ritual/article content.
Create final Chinese handdrawn technical article/PPT-style page images from articles, Markdown, PDFs, DOCX files, existing slide decks, course notes, scripts, outlines, or rough ideas. Use when the user asks to turn content into PPT/PPTX/slides/courseware/课件/演示稿/配图/效果图 in a refined Chinese handdrawn technical explanation style, to plan such pages, to choose page layouts from semantic content, or to generate complete image-model pages with Chinese text baked into the final visual. Default article outputs use 21:9 covers and 16:9 body illustrations.
Answer Engine Optimization (AEO) skill — optimize content to be cited by AI language models (ChatGPT, Perplexity, Claude, Gemini, Mistral) as authoritative sources. Distinct from SEO — AEO optimizes for citation in LLM-generated responses, not search rankings. Use when planning content for AI-first search audiences, auditing existing content for E-E-A-T signals, tracking which pages get cited by which LLMs, or building a citation-friendly content strategy. Triggers — 'AEO audit', 'optimize for ChatGPT', 'get cited by Perplexity', 'LLM citation strategy', 'answer engine optimization', 'content for AI search', 'E-E-A-T audit'. Output is a markdown audit report (default) or JSON for pipeline integration. Stdlib-only Python tools.
Repository-grounded threat modeling that enumerates trust boundaries, assets, attacker capabilities, abuse paths, and mitigations, and writes a concise Markdown threat model. Use when the user asks to threat model a codebase or path, enumerate threats or abuse paths, or perform AppSec threat modeling. Do NOT use for general architecture summaries, code review, security best practices (use security-best-practices), or non-security design work.
Get OpenAI Codex documentation pages in Markdown. Use when you need to reference Codex CLI features, configuration options, or any other Codex functionality.
Build fast, SEO-optimized static sites with Docusaurus v3.9.2 using Markdown/MDX, SEO metadata, and plugins. Helps with setup, docs, SEO optimization, plugin integration, and GitHub Pages deployment.