Skill UI

A comprehensive methodology for rigorous scientific research in operating systems and complex systems. This guide details how to pin environments (OS, firmware, hardware), automate data capture, and script all figures to ensure that experimental results are auditable and fully reproducible, protecting findings against review challenges.

A comprehensive guide for structuring the 'Related Work' section for top-tier HCI conferences (e.g., UIST). This document emphasizes that the section must function as a novelty proof, not a literature survey. It teaches authors to organize content by capability delta, utilize detailed comparison tables, and trace three critical lineages: technique, toolkit, and commercial practice, ensuring the work's unique contribution is clearly established.

SymPy is a powerful Python library designed for symbolic mathematics. Unlike numerical solvers, it performs exact calculations using mathematical symbols, allowing users to model and solve complex problems across various domains. Core capabilities include symbolic calculus (derivatives, integrals, limits), advanced algebra, solving systems of equations, linear algebra (determinants, eigenvalues), and specialized modules for physics and number theory. It can also generate executable code in languages like C and Fortran, making it invaluable for academic research and scientific computing.

This skill guides the creation of computable phenotypes and patient cohorts using the OHDSI/OMOP CDM standards. It allows users to define precise, executable criteria by combining standard concept sets (like PheKB) with advanced Natural Language Processing (NLP) features extracted from free clinical text. Use this when structured codes alone are insufficient to capture critical health information (e.g., symptoms, social context).

This skill automatically detects and extracts tabular laboratory panels from diverse sources, including scanned images, photos, and delimited files (CSV/TSV). It converts complex visual data into clean, structured rows, capturing the test name, measured value, unit, reference range, and abnormal flag. It is essential for preparing medical data for subsequent standardization using LOINC and UCUM, and for mapping into FHIR resources.

Reverse JavaScript-based custom DSL/VM interpreters, non-standard WASM-like runtimes, and risk-control engines. Use when analyzing IIFE or switch-based opcode dispatchers, extracting instruction tables, recovering bytecode semantics, capturing VM state at runtime, or reconstructing execution flow.

This skill estimates the download size and sync frequency cost of an offline profile before pushing it to users. It performs read-only diagnostics, verifying the profile, counting rows per table with scope filters, and calculating cache size. Useful for sanity checks before setup or assignment to prevent data cap surprises.

A robust, shell-free utility designed to launch executables and their arguments into a visible host terminal window. It supports multiple advanced modes including dry-run inspection, capability detection, detached fallback, and standalone recovery. Ideal for applications needing to securely execute interactive CLIs, SSH sessions, or local development processes in a reliable, non-interpolated manner.

A skill that captures Guixingren's AI technology media creation mindset, featuring Silicon Valley first-line perspectives, China-US dual-line narratives, rapid news aggregation structure, and AI community productization operations. Suitable for AI industry news writing, Silicon Valley reporting, China-US AI comparison analysis, developer tool reviews, and AI community operations, including hackathons, podcasts, and offline events.

This skill compiles user creative intent into executable image and video prompts for AI models. It specializes in character consistency, cinematic storyboards, and reference asset mapping for R2V/I2V/T2V tasks. It ensures visual contracts, narrative flow, and production-ready specifications without replacing model capabilities.

Measure reference videos into reusable style packs: 3D LUT grades, cut rhythm, stills, overlay plates, and specs for generative models. Use to capture looks, build repeatable grades, and match pacing.

Capture and retrieve durable artifact records with provenance and retention. Supports profiles like stdout, report, and receipt using immutable evidence. Use `yy ledger` CLI for secure evidence management without publishing or deploying.