Data & Analytics

Build a Python model to recommend the top 10 similar movies using item-based collaborative filtering for a dataset with a specific 3-column schema (movie_id, title with year, pipe-separated genres).

Generate a structured discussion analyzing the application, benefits, challenges, and leadership strategies for classification and clustering techniques within a selected industry.

Calculates mean, median, and mode for raw data and frequency distributions, including modality classification. Computes GPA using a specific 4.0 scale and applies user-defined rounding rules.

Calculates a power score (1-10) based on height, weight, and body type, and simulates physical struggles where success is determined by these scores without evasion or defense.

Implements a rolling window prediction pipeline using DNN and CNN models with CHAID variable selection, mean imputation for missing values, and hyperparameter tuning.

Rewrites input text to be clear and not too formal while strictly preserving the original meaning, facts, and numerical data.

Acts as an experienced financial advisor to create savings plans based on income and expenses. If the goal is unattainable, it assesses user interests via questions, recommends investment destinations, and provides detailed study plans for the chosen option.

Generates professional vendor profiles or shipping/refund policy sections for marketplace listings based on provided raw data, formatted with specific H2 headings.

Generates a Python model using item-based collaborative filtering to recommend the top 10 similar movies, specifically handling datasets with movie ID, title (with year), and pipe-separated genres.

Use this skill any time a spreadsheet file is the primary input or output. This means any task where the user wants to: open, read, edit, or fix an existing .xlsx, .xlsm, .csv, or .tsv file (e.g., adding columns, computing formulas, formatting, charting, cleaning messy data); create a new spreadsheet from scratch or from other data sources; or convert between tabular file formats. Trigger especially when the user references a spreadsheet file by name or path — even casually (like \"the xlsx i...

Analyze dashboards and notebooks using Davis analyzers — anomaly detection, novelty scoring, and correlation. Use when the user references a specific Dynatrace dashboard or notebook (by URL, UUID, or name) and asks what it shows, which DQL queries it runs, whether a tile looks off, or wants to find anomalies, score novelty, or correlate its metrics. The trigger is a dashboard or notebook as the data source, not a general DQL question. This skill extracts timeseries queries efficiently without...

Comprehensive spreadsheet creation, editing, and analysis with support for formulas, formatting, data analysis, and visualization. When Claude needs to work with spreadsheets (.xlsx, .xlsm, .csv, .tsv, etc) for: (1) Creating new spreadsheets with formulas and formatting, (2) Reading or analyzing data, (3) Modify existing spreadsheets while preserving formulas, (4) Data analysis and visualization in spreadsheets, or (5) Recalculating formulas

This skill should be used when the user asks to "analyze network traffic with Wireshark", "capture packets for troubleshooting", "filter PCAP files", "follow TCP/UDP streams", "detect network anomalies", "investigate suspicious traffic", or "perform protocol analysis". It provides comprehensive techniques for network packet capture, filtering, and analysis using Wireshark.

Master modern SQL with cloud-native databases, OLTP/OLAP

When the user wants to create, optimize, or analyze a referral program, affiliate program, or word-of-mouth strategy. Also use when the user mentions 'referral,' 'affiliate,' 'ambassador,' 'word of mouth,' 'viral loop,' 'refer a friend,' or 'partner program.' This skill covers program design, incentive structure, and growth optimization.

Build financial models, backtest trading strategies, and analyze

Build production-ready monitoring, logging, and tracing systems.

Design effective KPI dashboards with metrics selection, visualization best practices, and real-time monitoring patterns. Use when building business dashboards, selecting metrics, or designing data visualization layouts.

Master dbt (data build tool) for analytics engineering with model organization, testing, documentation, and incremental strategies. Use when building data transformations, creating data models, or implementing analytics engineering best practices.

Expert data scientist for advanced analytics, machine learning, and

Master modern business analysis with AI-powered analytics,

Complete App Store Optimization (ASO) toolkit for researching, optimizing, and tracking mobile app performance on Apple App Store and Google Play Store

ClickHouse database patterns, query optimization, analytics, and data engineering best practices for high-performance analytical workloads.

Structured guide for setting up A/B tests with mandatory gates for hypothesis, metrics, and execution readiness.