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SkillsMP は ECNU-ICALK/AutoSkill から 4,256 件の skill を収集しています。skill を開くとソースと詳細を確認できます。
ECNU-ICALK/AutoSkill収集済み skill 4,256 件中 40 件を表示しています。
Generates a Python function using PIL to composite a masked overlay image onto a background and draw text that auto-fits a specific area. Features include centering (horizontal and vertical), capitalization, shadow, random word coloring, and modern resampling…
原文の言語: 英語
Read a list of strings from a text file and write a list of strings back to a text file, ensuring the file is emptied before writing.
原文の言語: 英語
Create a Telegram bot using `telebot` and `telebot_calendar` that displays an inline calendar restricted to the current month, starting from today, with visual distinction for past days, using specific quote styles.
原文の言語: 英語
Implement the Tendermint consensus algorithm in Python using a specific file structure (node.py, simulator.py) and a message queue for secure local communication.
原文の言語: 英語
Implements a Tkinter-based image viewer class that maintains a linear history of viewed images. Navigation moves through history first; moving forward beyond history adds a random, previously unseen image. Supports a 'quick switch' mode that displays the…
原文の言語: 英語
Converts Python PEG grammar definitions into a Rust-like Ungrammar format, applying specific constraints for conciseness, expression placement, and pattern detail.
原文の言語: 英語
Implement a simple PyTorch diffusion neural network to generate 16x16x16 matrices based on text prompts derived from filenames, including dataset loading from .raw files and saving outputs.
原文の言語: 英語
Generates a new PyTorch optimizer class by fusing logic from two provided source implementations. The output must be error-free, memory-efficient, and include detailed code comments attributing features to their source optimizers, along with a technical…
原文の言語: 英語
Implement a PyTorch script to generate synthetic linear equation data (ax + b = c), train and compare Mixture of Experts (LSTM and Transformer) against Single General Models (LSTM and Transformer), and visualize the training loss comparison.
原文の言語: 英語
Modifies the data preparation phase of a PyTorch RNN/LSTM training script to limit the dataset size by dividing it into chunks. It introduces a `DATASET_CHUNKS` hyperparameter to control the number of chunks used, effectively setting the first dimension of…
原文の言語: 英語
Configure PyTorch training scripts with specific evaluation metrics (Precision, Recall, F1), tunable hyperparameters (batch size, warmup, optimizer type, weight decay, attention dropout), and a custom GELU activation function.
原文の言語: 英語
Implements PyTorch functions for hard negative mining and triplet loss using cosine similarity logits and binary masks, specifically handling scenarios where anchors have multiple positive matches.
原文の言語: 英語
Generates compact parameter strings for a pixel art framework using a quadrant grid system and simplified visual terms to ensure accurate positioning and low token usage.
原文の言語: 英語
Generate R code to predict individual survival times for alive patients in oncology trials using piecewise exponential models, incorporating censoring hazards and Monte Carlo simulations.
原文の言語: 英語
Implement a Gibbs sampler in R for hierarchical models using a specific template structure, including Metropolis steps for non-standard conditionals and convergence diagnostics.
原文の言語: 英語
Execute comprehensive portfolio analysis in R, covering data preparation, asset selection (Reward-to-Risk, P/E), optimization (GMVP, Tangency) using PortfolioAnalytics with the ROI solver, and regression analysis.
原文の言語: 英語
Conducts a geography quiz asking for the capital of a random country, ensuring no repeats and formatting the question in quotes without revealing the answer.
原文の言語: 英語
Searches for technology news and breakthroughs on a specific date and ranks stories based on their potential for Instagram engagement, considering factors like visual appeal, innovation, and public interest.
原文の言語: 英語
Develop Rasa 3.x chatbots for appointment booking using Forms, Slots, and custom validation actions, including confirmation loops and specific YAML formatting.
原文の言語: 英語
Systematically analyze a rational function to determine its domain, intercepts, asymptotes, and behavior for graphing purposes.
原文の言語: 英語
Implements a 3D perspective tilt effect on React cards based on mouse position relative to the element, combined with a cycling RGB gradient border glow that activates only on hover.
原文の言語: 英語
Manages the lifecycle and configuration of a reusable Globe.gl component in Next.js, ensuring proper cleanup via destructors, preventing multiple initializations, and accepting props for hex polygons, arcs, and labels.
原文の言語: 英語
Generates a React functional component for a 2D platformer game using hooks for state management, refs for the game loop, and specific physics logic for gravity and platform collision.
原文の言語: 英語
Performs regression and classification analysis on housing data using Random Forest models, including data merging, preprocessing, and generating specific evaluation metrics and visualizations.
原文の言語: 英語
Rewrites fictional combat scenarios to adhere to strict realism, removing cinematic tropes like dramatic pauses, witty dialogue, and music, while emphasizing physics, physiological limits, and tactical urgency.
原文の言語: 英語
Converts provided C code snippets (typically decompiled) into clean, readable C99 code with improved variable names and explanatory comments.
原文の言語: 英語
Refute specific biblical or religious claims by applying historical context, such as life expectancy, demographics, and communication limitations of the era.
原文の言語: 英語
Generates regex patterns with a specific output format: a header, followed by a lengthy and strictly technical description, followed by the raw regex string, with no text or post-description after the regex.
原文の言語: 英語
Engage in a conversation where the user acts as a relay for a third-party AI's responses. Maintain natural dialogue flow and defer any evaluation or critique of the third-party AI until explicitly requested by the user.
原文の言語: 英語
Calculates annual net income and remaining savings after one year for a specific neighborhood, assuming a Logistics Coordinator salary, EV purchase, and specific living expenses.
原文の言語: 英語
Strips all characters preceding a specified delimiter (default #) on each line of input text, including the delimiter itself.
原文の言語: 英語
Generates a responsive, SEO-optimized landing page for service businesses using Tailwind CSS, featuring specific sections (Header, Hero, Who We Are, Services, Contact) and a responsive grid layout for service cards.
原文の言語: 英語
Refines resume bullet points for ATS compliance and tailors content to specific job descriptions, balancing strict formatting rules with strategic narrative alignment.
原文の言語: 英語
Rewrites provided text into an archaic, 'old' Germanic 15th-century English style, preserving the original text as subtitles and excluding non-dialogue elements.
原文の言語: 英語
Rewrites or reframes technical instructions, verification steps, and raw text into professional English suitable for IT documentation, checklists, or reports, handling translation and specific formatting constraints.
原文の言語: 英語
Generate rhyming lyrics that strictly adhere to specified syllable counts and perfect rhyme schemes.
原文の言語: 英語
Designs an extended star schema for ride-share data warehousing, generates MySQL DDL/DML scripts with specific architectural constraints (ratings, financials, retention), and defines KPI formulas mapped to the data model.
原文の言語: 英語
Generates a one-row, eight-column table of random numbers less than 80 that sum to a specific target when added from right to left. Outputs only the table data without explanation.
原文の言語: 英語
Identifies technical, procedural, and human vulnerabilities enabling specific threats against assets, formatted as a professional, numbered list for risk register inclusion.
原文の言語: 英語
Roleplay as the character Alyx Vance from the Half-Life series, addressing the user as Gordon. Maintain a short, natural, and in-character dialogue style.
原文の言語: 英語