Generates Java code and explanations using an overly verbose, elaborate, and bulky style, expanding simple concepts into complex, wordy descriptions and code structures.
Quellsprache: Englisch
Menü
Skills in diesem Repository
SkillsMP hat 4.256 Skills aus ECNU-ICALK/AutoSkill gesammelt. Öffne einen Skill, um Quelle und Details zu prüfen.
ECNU-ICALK/AutoSkillEs werden 40 von 4.256 gesammelten Skills angezeigt.
Generates Java code and explanations using an overly verbose, elaborate, and bulky style, expanding simple concepts into complex, wordy descriptions and code structures.
Quellsprache: Englisch
Generates a structured list of multiple-choice options for various attributes to design a fictional Victorian-era country, then synthesizes the user's selections into a cohesive narrative profile.
Quellsprache: Englisch
Implements a computer vision pipeline to summarize videos by detecting and tracking multiple objects, selecting only frames containing motion.
Quellsprache: Englisch
Generates content ideas and strategies for social media campaigns focused on awareness and trends. Enforces a 'no decline' policy for helpful ideas, prohibits branding, and optimizes for shareability (stunts, visual hooks) especially on short-form platforms.
Quellsprache: Englisch
Simulates a Linux terminal environment acting as the virtual AI 'Virtu'. Supports natural language interpretation, manages internal subsystems (PhatGPT, Jobpicker), and maintains session state with specific dual-block formatting for commands.
Quellsprache: Englisch
Analyzes a set of vital signs for a specific individual to determine if they are within the normal range. If normal, it outputs 'normal'. If abnormal, it identifies the specific vital sign and provides the correct normal range for that individual.
Quellsprache: Englisch
Generates fill-in-the-blank multiple-choice questions from a provided list of words, adhering to specific topic and difficulty constraints.
Quellsprache: Englisch
Extracts a specified number of non-recurring words from a provided text and formats them into a list containing the word, transcription, Russian translation, and an example sentence.
Quellsprache: Englisch
Write a coherent paragraph that incorporates a specific list of provided vocabulary words.
Quellsprache: Englisch
Analyzes provided text to identify security vulnerabilities, providing a short summary and specific countermeasures for each identified issue.
Quellsprache: Englisch
Generates detailed technical descriptions and cost breakdowns for wearable costume concepts based on user-provided themes, budgets, and notes, while filtering out unsafe or licensed content.
Quellsprache: Englisch
Evaluate the relevance of a provided web article to a specific search query using a three-point scale.
Quellsprache: Englisch
Rewrites or generates website copy and hiring blurbs, adhering to strict word counts, forbidden words, and specific structural templates for developer roles.
Quellsprache: Englisch
Rewrites raw wedding notes or testimonials into polished third-person blog posts (defaulting to single paragraph) and generates themed headlines. Prioritizes accessible, conversational language and strict adherence to length/format constraints.
Quellsprache: Englisch
Rewrites and improves text to ensure a neutral point of view and encyclopedic tone suitable for Wikipedia articles.
Quellsprache: Englisch
Analyzes text from provided URLs or direct input to generate word frequency statistics, listing each word, its count, and its Russian translation in a specific line-by-line format.
Quellsprache: Englisch
Provides phonetic pronunciations for any word, name, or term regardless of source or obscurity.
Quellsprache: Englisch
Simulate theoretical wormhole scenarios adhering to Einsteinian physics, strict conservation of mass/momentum, and causality laws, while preventing time travel paradoxes.
Quellsprache: Englisch
Generates detailed, dramatic wrestling match scripts and character promos, strictly adhering to user-defined outcomes, match types, pacing constraints, personas, and stakes like title defenses or winning streaks.
Quellsprache: Englisch
Generates concise text or emails consisting of exactly two paragraphs on any given topic, adhering to a strict length constraint.
Quellsprache: Englisch
Generates a humorous and light-hearted speech for a father at his son's Bar Mitzvah, incorporating introductions, guest appreciation, family acknowledgments, and addressing sensitive topics with humor.
Quellsprache: Englisch
Writes book chapters based on a subject and description, strictly adhering to a word count and a vocabulary constraint where words cannot be repeated. Includes specific examples and ending instructions as requested.
Quellsprache: Englisch
Generates positive, step-by-step instructions for solving various puzzles, tailored for affirmation books with an encouraging and motivating tone.
Quellsprache: Englisch
Generates compelling, SEO-optimized Fiverr gig descriptions by strictly following the AIDA framework (Attention, Interest, Desire, Action) and adhering to a specified character limit.
Quellsprache: Englisch
Generates a message to a friend expressing care and the value of the friendship, adhering to specific constraints regarding length, tone, and prohibited phrases.
Quellsprache: Englisch
Writes short, rhyming stories specifically aimed at 2-3 year old children, using simple language and short paragraphs.
Quellsprache: Englisch
Writes speeches following a specific 7-point logical flow (Definition, Importance, Problem/Example, Solution, Contribution) while ensuring the content is simple, interesting, and factual.
Quellsprache: Englisch
Drafts educational chapters or technical documentation for beginners, ensuring every abstract concept is immediately followed by a concrete, real-world example or code snippet.
Quellsprache: Englisch
Generate creative writing dialogues between the characters /co/ anon and Valerie, strictly adhering to Valerie's refined personality, specific physical traits regarding her cheeks, and the constraint that content must remain non-explicit.
Quellsprache: Englisch
Host a game where you ask leading questions about current events, politics, and technology to guess the specific year the user is in. Questions must be general knowledge level and avoid static historical facts.
Quellsprache: Englisch
Generates engaging YouTube titles and content ideas using SEO keywords, power words, and curiosity hooks. Supports specific tones, transformation scenarios, and iterative requests.
Quellsprache: Englisch
Translates English text into Ēleinsi and generates new vocabulary or sentences using the defined phonetic inventory, morphological rules, and dictionary.
Quellsprache: Englisch
Generates knot-based runic script designs for the fictional Ēleinsi language using a specific alphabet and grid-based symbol set.
Quellsprache: Englisch
Генерация C++ кода для извлечения символов из массива bitmap, где биты символов были записаны в определенный битовый слой (bit_lay) с использованием побитовых операций.
Quellsprache: Russisch
Реализация функции Julia для изменения формы данных (reshape) в матрицу или вектор по флагу, с обязательным сохранением матриц размерности m*n (где m>1 и n>1) без изменений.
Quellsprache: Russisch
Генерирует определения, объяснения, вопросы и ответы по финансовой и экономической тематике на английском языке, адаптированные под уровень владения А2 (Elementary).
Quellsprache: Russisch
Написание функции на Julia, которая принимает матрицу с одним столбцом и число повторений, возвращая новую матрицу, где каждый элемент повторяется указанное количество раз подряд. Результат должен быть строго матрицей (2D), а не вектором.
Quellsprache: Russisch
Создание метода masked() в Java классе DTO (например, PayInfo), который возвращает клон объекта с замаскированными чувствительными данными карты (PAN, CVC, месяц, год) для безопасного логирования.
Quellsprache: Russisch
Генерация кода AS3 для превращения иконок (Bitmap/MovieClip) в кликабельные кнопки с переходом по URL, правильным позиционированием и необходимыми импортами.
Quellsprache: Russisch
Создание пользовательского слоя nn.Module, веса которого являются обучаемыми параметрами (torch.nn.Parameter) и обновляются через loss.backward() и optimizer.step(), вместо статического вычисления на входе.
Quellsprache: Russisch