Total 55,606 skills
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Complete mass spectrometry analysis platform. Use for proteomics workflows feature detection, peptide identification, protein quantification, and complex LC-MS/MS pipelines. Supports extensive file formats and algorithms. Best for proteomics, comprehensive MS data processing. For simple spectral comparison and metabolite ID use matchms.
Multi-objective optimization framework. NSGA-II, NSGA-III, MOEA/D, Pareto fronts, constraint handling, benchmarks (ZDT, DTLZ), for engineering design and optimization problems.
Process-based discrete-event simulation framework in Python. Use this skill when building simulations of systems with processes, queues, resources, and time-based events such as manufacturing systems, service operations, network traffic, logistics, or any system where entities interact with shared resources over time.
Statistical models library for Python. Use when you need specific model classes (OLS, GLM, mixed models, ARIMA) with detailed diagnostics, residuals, and inference. Best for econometrics, time series, rigorous inference with coefficient tables. For guided statistical test selection with APA reporting use statistical-analysis.
An Instagram API alternative on fetcher.sh — pay-per-call in USDC via x402, or prepaid credits with a Bearer key, no login and no session cookies. Use when the user wants to resolve an Instagram profile by @handle, search users by keyword, pull a profile's posts, reels, stories, tagged posts, followers, or followings, look up a single post by its shortcode, read a post's comments, fetch posts under a hashtag or reel-only hashtag feed, pull posts from a location, or pull posts using a specific audio/music track. Also covers Instagram follower export, hashtag and location monitoring, influencer discovery, competitor content tracking, and Instagram data pipelines without an official Graph API business verification or a headless browser.
Comprehensive toolkit for survival analysis and time-to-event modeling in Python using scikit-survival. Use this skill when working with censored survival data, performing time-to-event analysis, fitting Cox models, Random Survival Forests, Gradient Boosting models, or Survival SVMs, evaluating survival predictions with concordance index or Brier score, handling competing risks, or implementing any survival analysis workflow with the scikit-survival library.
Manage and trigger pre-built Zapier workflows and MCP tool orchestration. Use when user mentions workflows, Zaps, automations, daily digest, research, search, lead tracking, expenses, or asks to "run" any process. Also handles Perplexity-based research and Google Sheets data tracking.
A TikTok API alternative on fetcher.sh — pay-per-call in USDC via x402, or prepaid credits with a Bearer key, no login and no app review. Use when the user wants to search TikTok posts by keyword and sort by most-liked or most recent within a date range, look up a post by its share URL or ID, scrape a TikTok profile by @username, pull a user's posts, followers, or followings, fetch a hashtag's posts, pull posts using a specific sound/music track, get posts from a location, or read a post's comments and comment replies. Also covers TikTok trend tracking, hashtag monitoring, influencer discovery, competitor content analysis, and TikTok data pipelines without official TikTok API access or a scraping browser.
Implements animated effects, transitions, and motion in a Flutter app. Use when adding visual feedback, shared element transitions, or physics-based animations.
Parse FCS (Flow Cytometry Standard) files v2.0-3.1. Extract events as NumPy arrays, read metadata/channels, convert to CSV/DataFrame, for flow cytometry data preprocessing.
Scrape e-commerce data for pricing intelligence, customer reviews, and seller discovery across Amazon, Walmart, eBay, IKEA, and 50+ marketplaces. Use when user asks to monitor prices, track competitors, analyze reviews, research products, or find sellers.
Infer gene regulatory networks (GRNs) from gene expression data using scalable algorithms (GRNBoost2, GENIE3). Use when analyzing transcriptomics data (bulk RNA-seq, single-cell RNA-seq) to identify transcription factor-target gene relationships and regulatory interactions. Supports distributed computation for large-scale datasets.