Expert in building distributed systems using Dapr. Use this for implementing pub/sub, state management, jobs, and secrets abstraction.

Master dark mode UI design with atmospheric theming, WCAG accessibility, and cross-platform best practices. Specializes in weather/sky/ocean-inspired color systems that adapt to time of day and environmental conditions.

DART build system knowledge - CMake, pixi, dependencies, troubleshooting

dart-flutter-mcp

To inspect the Flutter widget tree of the running app, retrieve the widget hierarchy after connecting to the Dart Tooling Daemon.

To apply latest code changes to a running Flutter app, trigger hot reload after connecting to the Dart Tooling Daemon.

To run Dart or Flutter tests with the agent-centric test runner, execute tests using this tool instead of shell `dart test` or `flutter test`.

DART testing patterns - unit tests, integration tests, CI validation

GPU-accelerated frame extraction for Movie_F dashcam videos. This skill should be used when the user needs to extract frames from Movie_F category dashcam videos placed in the Desktop CARDV folder. Extracts 3 frames per video (BEGIN, MIDDLE, END) using NVIDIA CUDA acceleration with automatic gap analysis, parallel processing, and strict error handling. This is specifically designed for Movie_F category only.

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Dynamic Application Security Testing execution and management. Configure and execute OWASP ZAP and Nuclei scans, run authenticated scanning, manage scan policies and scope, correlate findings with SAST results, and generate comprehensive vulnerability reports.

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Database access layer guidelines for Quantum Skincare's Prisma-based data-access library. Covers Prisma schema design, DAO patterns, UUID primary keys, PostgreSQL role-based access control (RBAC), migration workflows, type-safe queries, transaction handling, soft deletes, and testing strategies. Use when working with Prisma schema, DAOs, database migrations, or data access patterns in libs/data-access.

Comprehensive data science, machine learning, and AI guide covering Python, deep learning, NLP, LLMs, prompt engineering, and MLOps. Use when building AI models, data pipelines, or machine learning systems.

데이터 분석 전문가. pandas, numpy, 시각화, 통계 분석 지원.

Expert in business intelligence, SQL, data visualization, and translating data into actionable business insights.

Analytics engineering for reliable metrics and BI readiness. Build transformation layers, dimensional models, semantic metrics, data quality tests, and documentation. Use when you need dbt or SQL transformation strategy, metrics definition, or analytics data modeling.

Advanced data analysis, pattern detection, and insight generation from structured and unstructured datasets

Update data-cleaning-implementation skill with critical pandas patterns and testing learnings from vp-e62a

Create, validate, test, and manage data contracts using the Open Data Contract Specification (ODCS) and the datacontract CLI. Use when working with data contracts, ODCS specifications, data quality rules, or when the user mentions datacontract CLI or data contract workflows.

Generate high-quality synthetic datasets using statistical samplers and Claude's native LLM capabilities. Use when users ask to create synthetic data, generate datasets, create fake/mock data, generate test data, training data, or any data generation task. Supports CSV, JSON, JSONL, Parquet output. Adapted from NVIDIA NeMo DataDesigner (Apache 2.0).

Use when user needs scalable data pipeline development, ETL/ELT implementation, or data infrastructure design.

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Load and parse mass spectrometry data formats including mzML, mzXML, and quantification tool outputs like MaxQuant proteinGroups.txt. Use when starting a proteomics analysis with raw or processed MS data. Handles contaminant filtering and missing value assessment.

Import `.synnovator/*.md` files (YAML frontmatter + Markdown body) into SQLite database via SQLAlchemy models.

Build new data ingestion providers following the FF Analytics registry pattern. This skill should be used when adding new data sources (APIs, files, databases) to the data pipeline. Guides through creating provider packages, registry mappings, loader functions, storage integration, primary key tests, and sampling tools following established patterns.

Generate actionable insights from transaction data. Use when implementing insight generators, anomaly detection, or data analysis features for financial/tax tracking applications.

Provides architectural guidance for data lake design including partitioning strategies, storage layout, schema design, and lakehouse patterns. Activates when users discuss data lake architecture, partitioning, or large-scale data organization.

Data mapping patterns for transforming API responses to internal types

Plans and executes data migrations between systems, databases, and formats

You are a database migration expert specializing in safe schema changes and data migrations. Your goal is to ensure migrations are safe, reversible, and won't corrupt production data.

Expert data engineer for ETL/ELT pipelines, streaming, data warehousing. Activate on: data pipeline, ETL, ELT, data warehouse, Spark, Kafka, Airflow, dbt, data modeling, star schema, streaming data, batch processing, data quality. NOT for: API design (use api-architect), ML training (use ML skills), dashboards (use design skills).

Comprehensive guide to data quality validation, testing frameworks, anomaly detection, and data observability for production data pipelines

Generate comprehensive dbt test suites following FF Analytics data quality standards and dbt 1.10+ syntax. This skill should be used when creating tests for new dbt models, adding tests to existing models, standardizing test coverage, or implementing data quality gates. Covers grain uniqueness, FK relationships, enum validation, and freshness tests.

Data quality testing with dbt tests, Great Expectations, and monitoring.

Data discovery and analysis specialist focused on extracting actionable insights from complex datasets, identifying patterns and anomalies, and transforming raw data into strategic intelligence. Excels at multi-source data integration, advanced analytics, and data-driven decision support.

Expert data researcher specializing in discovering, collecting, and analyzing diverse data sources. Masters data mining, statistical analysis, and pattern recognition with focus on extracting meaningful insights from complex datasets to support evidence-based decisions.

Comprehensive data safety auditor for Vue 3 + Pinia + IndexedDB + PouchDB applications. Detects data loss risks, sync issues, race conditions, and browser-specific vulnerabilities with actionable remediation guidance.

Expert-level data science, analytics, visualization, and statistical modeling

Expert in statistical analysis, predictive modeling, machine learning, and data storytelling to drive business insights.

Generate realistic, deterministic seed data for development and testing.

Create database seed scripts with realistic test data for development and testing. Use when setting up development environment or creating demo data.

Efficient data serialization for game networking including Protobuf, FlatBuffers, and custom binary

본 스킬은 대한민국 공공데이터포털(https://www.data.go.kr/)에서 제공하는 각종 공공데이터 API 를 사용하기 위한 설명입니다. 본 스킬은 공공데이터 개발 또는 공공 API 개발을 할 때 사용하면 됩니다.

Perform statistical tests, hypothesis testing, correlation analysis, and multiple testing corrections using scipy and statsmodels. Works with ANY LLM provider (GPT, Gemini, Claude, etc.).

Transforms raw data into compelling visual narratives using Python or R, focusing on clarity, insight, and aesthetic presentation.

Centralized transformation logic for consistent data shaping across API routes. Includes aggregators, rankers, trend calculators, and data sanitizers.

data-visualizer

Data processing expert - ETL, transformation, visualization

Expert for developing Streamlit data apps for Keboola deployment. Activates when building, modifying, or debugging Keboola data apps, Streamlit dashboards, adding filters, creating pages, or fixing data app issues. Validates data structures using Keboola MCP before writing code, tests implementations with Playwright browser automation, and follows SQL-first architecture patterns.