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Found 2,039 Skills
Convert Markdown documents to professionally styled DOCX (Word) files with python-docx. Handles CJK/Latin mixed text, fenced code blocks, tables, blockquotes, cover pages, TOC field, watermarks, and page numbers. Supports multiple color themes matching any2pdf (Warm Academic, Nord, GitHub Light, etc.) and is battle-tested for Chinese technical reports. Use this skill whenever the user wants to turn a .md file into a styled Word document, generate an editable report from markdown, or create a DOCX from markdown content — especially if CJK characters, code blocks, or tables are involved. Also trigger when the user mentions "markdown to docx", "md2docx", "any2docx", "md转word", "md转docx", "生成word", or asks for an "editable document" from markdown source.
Generate Python code for Naver Open APIs (News Search, Blog Search, Web Search, Datalab Trends, Image Search, Book Search, and other openapi.naver.com APIs). Use this skill whenever the user wants to call Naver APIs, search Naver News/Blog/Web/Images, fetch Datalab keyword trends, or write Python scripts that interact with Naver's Open API platform. This includes requests for code examples, API integration, parameter explanations, endpoint lookup, or troubleshooting Naver Open API calls. Even if the user just mentions 'Naver API', 'Naver news data', 'search trends', or 'openapi.naver.com', activate this skill immediately.
gget CLI and Python workflow for quick genomic database queries, sequence lookup, BLAST-style searches, enrichment checks, and reproducible bioinformatics evidence logs.
Manage multiple Alibaba Cloud accounts and batch-export Security Center (SAS) baseline and vulnerability reports via the aliyun CLI and Python scripts. Supports account list refresh, enable/disable, concurrent batch export of cloud platform configuration check (baselineCspm), system baseline risk (exportHcWarning), Linux/Windows/application/emergency vulnerability results across all managed accounts. Use this skill when users need to manage SAS multi-account settings, export baseline or vulnerability compliance data, or merge multi-account security reports into a single file.
Pricing completo de opciones europeas y americanas. 9 metodos: Black-Scholes, Binomial CRR, Trinomial, Monte Carlo (antithetic) + Longstaff-Schwartz, Bjerksund-Stensland 2002 / BAW (American closed-form), Heston 1993 (vol estocastica, sonrisa via Fourier), Bates 1996 (Heston + Merton jumps, crash risk), greeks (BS), implied vol, P(ITM) y P(Profit). Disenado para backtesting: cada funcion es flat Python vectorizado con numpy (sin abstracciones), usa math.erfc (no scipy). BS 2.4 us/op, BS2 3.6 us, Heston 400 us, Binomial N=500 5.6 ms. CLI con 15 modos mas validate y bench. Time complexity O(1) para todos los closed-form.
Python data validation using type hints and runtime type checking with Pydantic v2's Rust-powered core for high-performance validation in FastAPI, Django, and configuration management.
Expert in high-performance CSV processing, parsing, and data cleaning using Python, DuckDB, and command-line tools. Use when working with CSV files, cleaning data, transforming datasets, or processing large tabular data files.
This skill should be used when the user requests to create professional business documents (proposals, business plans, or budgets) from templates. It provides PDF templates and a Python script for generating filled documents from user data.
Comprehensive ADB (Android Debug Bridge) automation skill for game bot development, device management, computer vision integration, and Tauri-Python orchestration. Provides modular expertise for building intelligent Android automation workflows.
Generates API documentation from code including OpenAPI specs, JSDoc, and Python docstrings. Use when documenting APIs, REST endpoints, or library functions.
The foundational library for creating static, animated, and interactive visualizations in Python. Highly customizable and the industry standard for publication-quality figures. Use for 2D plotting, scientific data visualization, heatmaps, contours, vector fields, multi-panel figures, LaTeX-formatted plots, custom visualization tools, and plotting from NumPy arrays or Pandas DataFrames.
Build LiveKit Agent backends in Python. Use this skill when creating voice AI agents, voice assistants, or any realtime AI application using LiveKit's Python Agents SDK (livekit-agents). Covers AgentSession, Agent class, function tools, STT/LLM/TTS models, turn detection, and multi-agent workflows.