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Found 819 Skills
Generate an Information Architecture (IA) document from a service plan, PRD, or product idea. Outputs a structured screen hierarchy as Markdown nested lists and saves to SCREENS.md.
Look up and read Hugging Face paper pages in markdown, and use the papers API for structured metadata such as authors, linked models/datasets/spaces, Github repo and project page. Use when the user shares a Hugging Face paper page URL, an arXiv URL or ID, or asks to summarize, explain, or analyze an AI research paper.
Look up and read Hugging Face paper pages in markdown, and use the papers API for structured metadata such as authors, linked models/datasets/spaces, Github repo and project page. Use when the user shares a Hugging Face paper page URL, an arXiv URL or ID, or asks to summarize, explain, or analyze an AI research paper.
Create professional CVs and resumes with perfect typography using RenderCV (v2.8). Users write content in YAML, and RenderCV produces publication-quality PDFs via Typst typesetting. Full control over every visual detail: colors, fonts, margins, spacing, section title styles, entry layouts, and more. 6 built-in themes with unlimited customization. Any language supported (22 built-in, or define your own). Outputs PDF, PNG, HTML, and Markdown. Use when the user wants to create, edit, customize, or render a CV or resume.
CrewAI task design and configuration. Use when creating, configuring, or debugging crewAI tasks — writing descriptions and expected_output, setting up task dependencies with context, configuring output formats (output_pydantic, output_json, output_file), using guardrails for validation, enabling human_input, async execution, markdown formatting, or debugging task execution issues.
Publish and manage research papers on Hugging Face Hub. Supports creating paper pages, linking papers to models/datasets, claiming authorship, and generating professional markdown-based research articles.
Retrieve ALL information from a Jira ticket (description, comments, subtasks, attachments metadata, labels, sprint, status, assignee, reporter, linked issues, custom fields, acceptance criteria) and persist it as a single Markdown file. Use whenever the user says "fetch ticket", "retrieve Jira", "pull ticket info", "get ticket details", "look up ticket", "grab the Jira", "what does ticket X say", "check the ticket", "read the ticket", "show me the ticket", or provides a Jira ticket URL or key like PROJECT-1234. Also triggered by the orchestrating-jira-workflow skill as Phase 1 of the end-to-end pipeline. Trigger even if the user only pastes a ticket key with no other context — that alone means "fetch this ticket." This skill ONLY retrieves — it never modifies the ticket or starts implementation.
Convert a PDF (research paper, report, or any document) into a polished multi-slide HTML presentation with a structured outline JSON and summary markdown. Trigger this skill when the user mentions making slides or a PPT from a PDF — in Chinese or English.
Write a textual content based on given document(s) and requirements, using ZhiPu GLM-V multimodal model. Read and comprehend one or multiple documents (PDF/DOCX), write a content in Markdown format according to the specified requirements. Use when the user wants to draft a paper/article/essay/report/review/post/brief/proposal/plan, etc.
A step-by-step practice tool for LeetCode medium-difficulty interview questions. It is triggered when users want to practice algorithm problems, brush up on LeetCode, prepare for technical interviews, or say "Give me a problem", "Next problem", "Generate scaffold", "Start practicing". It supports categorized practice by problem type (DP, Linked List, Tree, Graph, Sliding Window, Two Pointers, Hash Table, Binary Search, Stack, Heap, Backtracking, Interval, String, Union Find), generates Python scaffolds with test cases for each problem, tracks learning progress via Markdown tables, and guides users to think independently before providing solutions. It supports the goal of 3 problems per day, counts progress via `git diff README.md` and submits to Git.
Search markdown knowledge bases, notes, and documentation using QMD. Use when users ask to search notes, find documents, or look up information.
Parse documents into clean markdown or structured JSON via the xparse-cli. Use this skill when the user provides a PDF, image, Office file, HTML, OFD, or other supported document and wants it read, converted, summarized, or prepared for downstream agent use. Handles encrypted PDFs, page ranges, markdown/text output, and detailed structured extraction. Prefer this skill whenever the task starts from a local file or document URL and the first step is to turn it into agent-friendly content rather than manually inspect the raw file.