AI Agent Workflow Collection

Replace real PII in a dataset with realistic synthetic equivalents while preserving row counts, column types, and statistical distributions. Detects names, emails, phones, SSNs, addresses, credit cards, and user-identifying columns via name heuristics + value patterns. Use this skill when the user wants to "anonymize this dataset", "scrub PII", "make this data safe to share", "de-identify real data", "create a synthetic copy", or needs a sharable version of production data without exposing individuals.

Compute derived, aggregated, or transformed tables from existing datasets. Use this skill when the user needs to "compute monthly scores", "aggregate by month", "create a summary table", "derive risk scores", "compute percentile ranks", "roll up events", "create benchmarks from raw data", "add a computed column", or bridge the gap between raw generated tables and downstream analytics. Works on xlsx, csv, or json input. Claude writes the computation logic; the script handles data I/O.

Extend an existing synthetic dataset by adding more rows or new columns while preserving FK integrity, ID continuity, and column distributions. Use this skill when the user wants to "add more rows", "append data", "extend this dataset", "add a new column", "grow my dataset", or needs a larger version of an existing synthetic dataset without regenerating from scratch.

Extract tabular data from Excel workbooks (.xlsx) to JSON files, one per sheet. Auto-detects whether a sheet has a title-banner row above the headers (synthdata-generate convention) or starts with headers directly. Use this skill when the user wants to convert an Excel file to JSON, extract spreadsheet data, parse an xlsx file, prepare data for downstream analysis tools that don't read Excel natively, or set up a dataset for the other synthdata skills. Also trigger on "extract the data", "parse this spreadsheet", "convert to JSON", or "read this xlsx file".

Generate synthetic tabular datasets from YAML schemas. Use this skill when the user wants to create sample data, mock data, test data, synthetic datasets, or demo data for any domain — HR directories, e-commerce orders, SaaS metrics, healthcare records, financial transactions, security events, application logs, IoT sensor readings, CRM pipelines, survey responses, or custom schemas. Ships with 10+ domain templates and supports custom YAML schemas with Faker-backed fields, statistical distributions (normal/lognormal/zipf/poisson), foreign-key integrity, behavioral profiles, and temporal event generation. Also trigger when user says "generate synthetic data", "create fake data", "mock dataset", "test data", or names a specific domain like "e-commerce data" or "HR data".

Help users plan multi-step synthetic data generation workflows. Use this skill when the user describes a complex data scenario ("I need healthcare risk data with monthly scores and peer benchmarks"), asks "what data do I need", "how should I generate this", "plan my dataset", "help me formulate a prompt", or wants to understand what synthdata-generate can and cannot produce directly. Also trigger on "prompt builder", "data planning", "generation plan", "what tables do I need", or "help me set up data for [tool/product/demo]".

Spin up a read-only MCP server from a synthetic dataset, making tables queryable by Claude. Use this skill when the user wants to "serve data as an MCP server", "make this dataset queryable", "create an MCP server from my data", "expose this data to Claude", "let Claude query this dataset", "export a data server", "serve this xlsx", or "start a data API from my generated data". Works with xlsx, csv, json, or parquet input — or generates fresh data via synthdata-generate first.

Guided interactive walkthrough of the synthdata plugin's capabilities. Use this skill whenever the user asks for a "synthdata tutorial", "walkthrough", "demo", "guided tour", "show me what synthdata can do", "how does synthdata work", "getting started with synthdata", or wants to explore the synthetic-data skills step by step. Also trigger on "onboarding", "product tour", "feature overview", or "teach me how to generate fake data" in the context of synthdata / synthetic data generation.