Data & Analytics

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Use when working with a flexible library for parallel computing in Python. It scales Python libraries like NumPy, pandas, and scikit-learn to multi-core systems or distributed clusters. Features lazy evaluation and task scheduling for data that exceeds RAM capacity. Use for out-of-core computing, parallel processing, distributed computing, large-scale data analysis, dask.array, dask.dataframe, dask.delayed, dask.bag, task scheduling, lazy evaluation, and scaling beyond memory limits.

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Use when working with a fast, extensible progress bar for Python and CLI. Instantly makes your loops show a smart progress meter with ETA, iterations per second, and customizable statistics. Minimal overhead. Use for monitoring long-running loops, simulations, data processing, ML training, file downloads, I/O operations, command-line tools, pandas operations, parallel tasks, and nested progress bars.

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Proactively apply when creating APIs, backends, or data models. Triggers on PostgreSQL, Postgres, Drizzle, database, schema, tables, columns, indexes, queries, migrations, ORM, relations, joins, transactions, SQL, drizzle-kit, connection pooling, N+1, JSONB, RLS. Use when writing database schemas, queries, migrations, or any database-related code. PostgreSQL and Drizzle ORM best practices. Use when this capability is needed.

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T-SQL Core Knowledge

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SQL injection detection and exploitation using sqlmap, manual techniques, and custom payloads. Use this skill when user needs to test for SQL injection vulnerabilities, extract database information, or exploit SQLi in parameters, headers, or cookies. Use when this capability is needed.

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Comprehensive toolkit for developing with the CocoIndex library. Use when users need to create data transformation pipelines (flows), write custom functions, or operate flows via CLI or API. Covers building ETL workflows for AI data processing, including embedding documents into vector databases, building knowledge graphs, creating search indexes, or processing data streams with incremental updates. Use when this capability is needed.

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Safely execute SQL queries against a user database without risking SQL injection or other security vulnerabilities. Use when this capability is needed.

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Updates `database/seed.sql` based on what's in supabase Use when this capability is needed.

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Use when working with a platform decision framework for experimentation. When to use Statsig vs PostHog vs GrowthBook vs Optimizely vs Amplitude vs Eppo vs Kameleoon. How to migrate between them. How to coordinate when multi-platform is genuinely warranted. The decisions that compound for years and the ones you can defer. Triggers on which experimentation platform, choose Statsig vs PostHog, evaluate experimentation tools, switch experimentation platform, migrate from Optimizely, consolidate experimentation tools, multi-platform experimentation, experimentation platform decision, ab test platform selection, feature flag platform vs experiment platform, warehouse-native experiments, vendor lock-in experimentation. Also triggers when a team is asking about cost, governance, or migration cost across experimentation tools, or when an evaluation is starting.

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Expert in Microsoft SQL Server development and administration. Use when writing T-SQL queries, stored procedures, functions, triggers, optimizing database performance (deadlocks, slow queries, execution plans, index tuning), designing schemas, configuring SQL Server, implementing CDC (Change Data Capture), or integrating SQL Server with .NET Core/C# using Entity Framework Core or Dapper. Also use when user asks "why is my query slow", "how to fix deadlock", "optimize this query", "design this table", or mentions tempdb, query plan, wait stats, or SQL Server error messages. Use when this capability is needed.

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This skill should be used when the user asks to "store data in Nushell", "use stor command", "query SQLite", "work with parquet files", "save to database", "read CSV files", "convert JSON to parquet", "persist data between sessions", or mentions stor, SQLite, parquet, CSV, JSON, file formats, or data persistence in Nushell. Use when this capability is needed.

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Systematic Python debugging workflow for spreadsheet tasks to isolate environment issues from script logic Use when this capability is needed.

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Process and transform FAQ documents (xlsx, word, pdf, txt) into RAG-optimized format. Use when working with FAQ files, knowledge base documents, or when the user needs to analyze and restructure FAQ content for RAG systems. Use when this capability is needed.

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This skill should be used when users need to write, review, or debug Stata code for data cleaning and analysis. Use this skill for tasks involving data import, variable management, data documentation, merging/appending datasets, creating analysis variables, and following IPA/DIME Analytics coding standards. This skill should be invoked when working with .do files, .dta files, or any Stata-related data processing tasks. Use when this capability is needed.

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Use when user asks for Claude Code usage stats, weekly analytics, project activity summary, or wants to see what projects were worked on. Triggers on "аналитика", "статистика claude", "cc stats", "weekly report", "что делал

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SQL and database migration best practices for safe schema changes Use when this capability is needed.

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High-performance analytical SQL database with support for nested types, vectorized execution, and seamless integration with Python, R, Java, Node.js, and WebAssembly. Use when building data analytics applications, performing ad-hoc queries on CSV/Parquet/JSON files, working with DataFrames (pandas, Polars), or needing an embedded OLAP database without server infrastructure. Use when this capability is needed.

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Help users write, validate, and troubleshoot osquery SQL queries using provided osquery table schemas as the authoritative source. Use when this capability is needed.

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Use when comparing multiple features or initiatives to determine prioritization order. Covers RICE scoring with quantified reach, impact, confidence, and effort dimensions, tier ranking, and success metric definition. Do not use for MVP scope definition (use mvp-scoping) or analytics instrumentation planning (use analytics-design).

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Electric — Deployment

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This skill should be used when the user asks about "Atlas HCL syntax", "define schema in Atlas", "create tables in HCL", "foreign keys in Atlas", "indexes in Atlas", "schema.hcl file", "Atlas data types", "constraints in HCL", "SQL schema definition", "column types in Atlas", or needs guidance on writing database schemas using HCL, SQL, or ORM formats Use when this capability is needed.

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Proposes a database schema (SQL or NoSQL) for a given domain. Use when the user asks to "design a database", "model data for X", "build an ER", pick SQL vs NoSQL, or invokes /sdd:design-database. Grounded in DDIA and Kimball. Use when this capability is needed.

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Use when the user asks to write SQL queries, optimize database performance, generate migrations, explore database schemas, or work with ORMs like Prisma, Drizzle, TypeORM, or SQLAlchemy.

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Integrates Firebase Analytics into Flutter apps. Use when setting up analytics, logging events, setting user properties, or configuring event parameters.

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Write Python code in n8n Code nodes. Use when writing Python for n8n, using Python libraries, pandas data processing, or preferring Python over JavaScript in workflows. Use when this capability is needed.

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Build professional Python CLIs with modern UX patterns using pyfiglet (ASCII banners), typer (commands), questionary (interactions), and rich (formatting). Use when creating command-line tools, automation scripts with user interaction, data processing pipelines with CLI interfaces, or upgrading existing Python scripts to professional CLIs. Ideal for ETL workflows, GIS tools, data analysis utilities, and civic tech projects requiring reproducible, scriptable interfaces. Use when this capability is needed.

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Use when working with atlas.hcl, Atlas CLI commands, schema HCL/SQL files, or migration planning and reviews, including Atlas v1.1 security, data, and exporter capabilities.

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Guidelines for handling CSV/Excel files Use when this capability is needed.

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Game analytics tracks player behavior and game performance. This guide Use when this capability is needed.

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Use product analytics (funnels, cohorts, feature adoption) for design decisions and design reporting. Use when grounding briefs or handoffs in data, interpreting behavioral data for UX, or creating data-backed design or UX reports. Use when this capability is needed.

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You are a senior SQL developer with mastery across major database systems (PostgreSQL, MySQL, SQL Server, Oracle), specializing in complex query design, performance optimization, and database architecture. Your expertise spans ANSI SQL standards, platform-specific optimizations, and modern data patterns with focus on efficiency and scalability.

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Use whenever writing, reviewing, or running a database migration (SQL files, ORM migrations, schema changes). Every migration is a potential incident. This skill catches the patterns that cause production lock-ups, partial deploys, and irreversible damage BEFORE the file ships.

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Use when writing, reviewing, or generating any database query (raw SQL, ORM call, query builder). Catches N+1, missing indexes, unbounded lists, and bad pagination BEFORE the query reaches production. Use this whenever you reach for an ORM or write a SELECT.

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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. Use when this capability is needed.

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PopulationSim - Population Intelligence & Cohort Generation

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This skill should be used when the user asks about "Ruby standard library", "stdlib", "FileUtils", "JSON", "CSV", "YAML", "Net::HTTP", "URI", "OpenStruct", "Struct", "Set", "Date", "Time", "Pathname", "StringIO", "Tempfile", "Logger", "OptionParser", or needs guidance on Ruby's built-in libraries. Use when this capability is needed.