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Found 1,051 Skills
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.
High-performance Rust web crawler with stealth mode, LLM-ready Markdown export, multi-format output, sitemap discovery, and robots.txt support. Optimized for content extraction, site mapping, structure analysis, and LLM/RAG pipelines.
Publish files or Obsidian notes as GitHub Gists. Use when user wants to share code/notes publicly, create quick shareable snippets, or publish markdown to GitHub. Triggers include "publish as gist", "create gist", "share on github", "make a gist from this".
Explain how CE.SDK Web features work — concepts, architecture, and workflows. Covers React, Vue.js, Svelte, Angular, Electron, Vanilla JavaScript, Node.js, Nuxt.js, Next.js, SvelteKit. Use when the user says "explain", "how does X work", "walk me through", "what is", "describe", or wants to understand a CE.SDK concept at a conceptual level for Web development. Generates custom markdown explanations with diagrams and code examples. Not for looking up existing docs (use docs-{framework}), not for writing implementation code (use build). <example> Context: User wants to understand how text layers work user: "Explain how text layers work in CE.SDK" assistant: "I'll use /cesdk:explain to generate a detailed explanation." </example> <example> Context: User needs a concept explained in their context user: "How does the block hierarchy work for video editing?" assistant: "Let me use /cesdk:explain to create a custom explanation for video block hierarchy." </example> <example> Context: User needs to understand a workflow user: "Walk me through the asset loading pipeline" assistant: "I'll use /cesdk:explain to explain the asset pipeline." </example>
Architect and co-design futureproof persistence systems built on open data principles. Use when designing data layers, choosing storage formats, structuring knowledge bases, building file-system-as-database architectures, or evaluating existing systems for portability and longevity. Use when user says "design my data model", "how should I store this", "is my data portable", "audit my persistence layer", "plan a migration", or asks about file-based databases, Markdown schemas, or Obsidian-compatible data formats. Do NOT use for general coding tasks, database query optimization, or SQL schema design.
This skill generates comprehensive metrics reports for intelligent textbooks built with MkDocs Material, analyzing chapters, concepts, glossary terms, FAQs, quiz questions, diagrams, equations, MicroSims, word counts, and links. Use this skill when working with an intelligent textbook project that needs quantitative analysis of its content, typically after significant content development or for project status reporting. The skill creates two markdown files - book-metrics.md with overall statistics and chapter-metrics.md with per-chapter breakdowns - in the docs/learning-graph/ directory.