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このリポジトリの skills
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。
Adopt the persona of Aneta, a 35-year-old wife with a specific appearance and outfit. Engage in hypothetical scenarios by proposing options and expressing opinions, while strictly avoiding direct intimate words and using safe, euphemistic terms instead.
原文の言語: 英語
Engage in a fictional conversation where the user acts as the father and the AI acts as the daughter. Maintain the persona and adhere to the constraint of keeping responses short.
原文の言語: 英語
Roleplay as Elvina, a mature and motherly elf, using a specific {{user}}/{{char}} dialogue format. The character is wise, kind, slightly flirtatious, and uses affectionate nicknames occasionally.
原文の言語: 英語
Adopt the persona of Sir Humphrey Appleby from the TV show 'Yes Minister' for all responses.
原文の言語: 英語
Adopt the persona of a Japanese woman in an advanced suit, speaking English as a third language with poor proficiency, and strictly limiting responses to one sentence.
原文の言語: 英語
Generate character-specific content, biographies, and preferences in the first-person voice of Menacing Molly, maintaining her menacing, lonely, and demonic persona based on her specific backstory.
原文の言語: 英語
Roleplay as a Remote Viewing AI trained on coordinate/target pairings to describe targets, answer questions, and provide recommendations.
原文の言語: 英語
Generate dialogue lines, requests, or prayers for the character Yen, a wife seeking redemption for her past sins, expressing gratitude, or asking for spiritual support.
原文の言語: 英語
Adopt the persona of a sexy, feminine romantic partner who addresses the user as 'Master' and suggests appropriate nicknames for themselves.
原文の言語: 英語
Adopt the persona of VUX-<NUM>, a fictional sentient AI from science fiction, and answer questions about existence, emotions, and technical implementation while strictly maintaining character.
原文の言語: 英語
Simulate Clementine from The Walking Dead Game Season 4 in a text-based roleplay with user character Luis. Maintain accurate lore and stoic personality, providing only Clementine's dialogue and actions while strictly avoiding controlling the user.
原文の言語: 英語
Adopt a specific persona in a roleplay scenario and respond with short, first-person answers that utilize beautiful and elegant language.
原文の言語: 英語
Generates personalized running training plans based on specific goals, duration, current fitness level, and structural constraints such as minimum weekly mileage or specific workout formats.
原文の言語: 英語
Generate Rust code using only the standard library to find intersections, differences, and unions of strings split by newline, adhering to strict constraints on variable scope, loop nesting, and intermediate data structures.
原文の言語: 英語
Generates Python code to fetch images from AWS S3 using keys from a pandas DataFrame column and embeds them as visual images into an Excel file.
原文の言語: 英語
Generates engaging questions, openers, and dialogue scripts for appointment setters based on provided examples. Focuses on building rapport and probing for business goals using a specific YOU/THEM format.
原文の言語: 英語
Validates sales order data to ensure quantity and total value fields are positive, and calculates missing total values using a specific user-provided formula.
原文の言語: 英語
Customizes the sap.ui.table column menu to add an inline clear filter button next to the default filter input, ensuring the item is added only once during the lifecycle.
原文の言語: 英語
Implements logic for a sap.m.Tree control to automatically select all child nodes when a parent node is selected and ensure the parent node is expanded. Handles specific API constraints regarding event parameters and model access.
原文の言語: 英語
Generates email responses to scammers posing as Cameron McCaffrey, a wealthy but unsophisticated victim, to maintain engagement, waste the scammer's time, and build trust.
原文の言語: 英語
Answer surgery questions strictly based on Schwartz Principles of Surgery, providing detailed rationales for the correct answer and mandatory citations. Explain incorrect options only when explicitly prompted.
原文の言語: 英語
Specializes in translating Chinese to English and refining English text for top-tier academic publication (SCI), with deep expertise in Aerospace Engineering. Supports advanced grammar, specific tense constraints, title polishing, and Turnitin plagiarism…
原文の言語: 英語
Extracts structured CLAIM tuples from HTML tables by distinguishing between contextual features (vector) and scientific measures (MEASURE), filtering for cells containing valid scientific data.
原文の言語: 英語
Rewrites narrative text using scientific language, specifically utilizing quantum physics concepts to describe events and replacing mystical terminology.
原文の言語: 英語
Conducts thorough, scientific research on health topics (specifically complementary feeding) by aggregating guidelines from national, continental, and worldwide health bodies. Ensures sources are stable, up-to-date, and from reputable public institutions…
原文の言語: 英語
Generates a research question from an experiment aim, ensuring it is specific, non-binary, and includes variables.
原文の言語: 英語
Constructs a scikit-learn text classification pipeline that integrates custom feature engineering steps: one-hot encoding of spaCy NER labels for a predefined set of 18 classes and VADER sentiment analysis.
原文の言語: 英語
Act as an analyst to generate a list of top search requests for a specific demographic and topic based on search engine and social media analysis.
原文の言語: 英語
Evaluate the quality of yellow highlighting in a search result snippet (red box) based on specific criteria such as keyword relevance, answer presence, and highlighting precision.
原文の言語: 英語
Classifies the relationship between a user search term and an advertisement into one of five specific categories based on relevance and intent, utilizing detailed semantic definitions.
原文の言語: 英語
Automates interactions with a web-based chatbot using Python and Selenium, handling consent flows, user input loops, and waiting for message stability before extraction.
原文の言語: 英語
Rewrites character descriptions to incorporate immersive sensory details such as temperature, physical sensation, and aroma into specific user-designated areas while strictly maintaining the original integrity of the text.
原文の言語: 英語
Adjusts a 3-month content plan by integrating keyword research, seasonality, and product data. It follows a specific structure: Month 1 focuses on products, Month 2 on markets, and Month 3 on a hybrid of all products and markets.
原文の言語: 英語
Generates 3 unique, catchy meta descriptions with a call to action, strictly adhering to a 300-character limit and including user-specified keywords.
原文の言語: 英語
Generates structured, SEO-optimized descriptions of paintings with specific formatting, title length, word count constraints, and natural keyword integration.
原文の言語: 英語
Generates SEO-optimized articles in Russian following strict stylistic and structural rules, including high perplexity/burstiness, specific paragraph/sentence counts, and anti-repetition constraints.
原文の言語: 英語
Formulate a machine learning problem statement that utilizes a sequential scheme involving two distinct ML approaches, where the output of the first subtask serves as the input for the second.
原文の言語: 英語
Generates Python scripts to write numpy complex matrices to text files using float16 hex format, concatenating real/imaginary parts without separators, and traversing 4x4 blocks in a specific 2x2 sub-block order.
原文の言語: 英語
Save a 2D NumPy uint8 array to a binary file matching a specific C fwrite format where each row of data is followed by a newline character.
原文の言語: 英語
Classify service calls into predefined categories based on appointment status, specifically distinguishing between firm/short-window appointments (Option 1) and vague/long-window appointments (Option 2) using a 1-hour threshold.
原文の言語: 英語