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Found 961 Skills
This skill should be used when users need to search the web for information, find current content, look up news articles, search for images, or find videos. It uses DuckDuckGo's search API to return results in clean, formatted output (text, markdown, or JSON). Use for research, fact-checking, finding recent information, or gathering web resources.
Summarize database schema design from requirement inputs and produce implementation-ready outputs for Go + Ent in this repository. Use when the input may be a prompt, Markdown requirement document, repository folder, or runnable demo behavior and you need entity extraction, field/constraint design, weak-relation ID strategy, index planning, Ent schema guidance, and concrete bind/render/service integration impacts.
Create markdown-based behavioral rules preventing unwanted actions. create hookify rule, behavioral rule, prevent behavior, block command Use when: preventing dangerous commands, blocking debug commits, enforcing conventions DO NOT use when: hook scope (abstract:hook-scope-guide), SDK hooks (abstract:hook-authoring), evaluating hooks (abstract:hooks-eval).
Generate end-user documentation site using Docusaurus 3.x from the current project. Use this skill when the user asks to create documentation, generate docs, build a docs site, or set up Docusaurus for their project. Supports analyzing project structure, generating markdown docs, configuring Docusaurus, and creating user guides.
将 X (Twitter) 推文和文章转换为带 YAML front matter 的 Markdown。使用逆向工程 API，需要用户同意。当用户提到"X转markdown"、"保存推文"、或提供 x.com/twitter.com 链接时使用。
Centralized help URL reference for accessibility remediation. Maps axe-core rule IDs to Deque University topics, document rule IDs to Microsoft Office and Adobe PDF help pages, and WCAG criteria to W3C Understanding documents. Use when generating CSV exports, markdown reports, or any output that links findings to external remediation documentation.
Universal content grabber — fetch any URL and return structured Markdown. Supports X/Twitter, WeChat, Xiaohongshu, YouTube, GitHub, Feishu/Lark, Bilibili, Telegram, RSS, and any web page. Use when user provides a URL and wants its content extracted.
Convert legal texts (legal provisions or legal cases) into standardized Markdown format and remove promotional redundant information. This skill shall be used when users need to process legal provisions (such as the Civil Code, Criminal Law, etc.), organize legal cases (such as typical cases of the Supreme People's Court, judgment documents, etc.), or format legal documents from pasted text. Note: This skill is only responsible for formatting and content cleaning, and does not have content crawling capability. Content acquisition shall be completed by other skills (such as wechat-article-fetch), and AI will automatically determine the skill collaboration sequence.
PDF data extraction tool. Use it when users mention "PDF extraction", "PDF to Markdown", "PDF parsing", "extract PDF content", "PDF to JSON", "RAG PDF". OpenDataLoader PDF is currently the top-ranked PDF parser in benchmark tests, supporting local mode (fast, deterministic) and hybrid AI mode (for complex tables, scanned documents, formulas), with output formats including Markdown, JSON (with bounding boxes), and HTML. It is suitable for scenarios where structured data needs to be extracted from PDFs for RAG/LLM pipelines, or where batch processing of PDF documents is required.
Fetch real-time web data via the hasdata CLI. Use when the user wants search results, news, fact-checks, product or seller info, current prices, reviews, real-estate listings or sold comps, vacation rentals, local-business contact details, job postings, salary research, search trends, images, flights, social profiles, or to scrape any URL (HTML / markdown / AI-extracted JSON). Also use when the user asks to summarize a web page, ground a prompt with current information, verify a URL is live or render a JavaScript-heavy page, monitor a price over time, find a phone number or address for a business, build a competitor map, identify recent sold comparables, gather employer reviews, fan out a list of items to per-item details, or check what's being said online about a topic right now. Backed by Google, Bing, Amazon, Shopify, Zillow, Redfin, Airbnb, Yelp, YellowPages, Indeed, Glassdoor, Instagram, Google Maps / Trends / News / Images / Flights / Events APIs.
Ingests unstructured and semi-structured documents into Neo4j as a knowledge graph. Use when chunking PDFs, HTML, plain text, or Markdown; extracting entities and relationships from text with an LLM (SimpleKGPipeline, neo4j-graphrag); loading JSON via apoc.load.json; building Document→Chunk→Entity graph structures; or connecting LangChain/LlamaIndex document loaders to Neo4j. Covers neo4j-graphrag SimpleKGPipeline, LLM Graph Builder web UI, entity resolution, chunking strategies, and graph schema design for RAG pipelines. Does NOT handle structured CSV/relational import — use neo4j-import-skill. Does NOT handle GraphRAG retrieval after ingestion — use neo4j-graphrag-skill. Does NOT handle vector index creation — use neo4j-vector-search-skill.
Review a pull request or contribution deeply, explain it tutorial-style for a maintainer, and produce a polished report artifact such as HTML or Markdown. Use when asked to analyze a PR, explain a contributor's design decisions, compare it with similar systems, or prepare a merge recommendation.