test-data-management
Strategic test data generation, management, and privacy compliance for scalable, secure, and realistic quality engineering workflows.
Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
134 skills found
Strategic test data generation, management, and privacy compliance for scalable, secure, and realistic quality engineering workflows.
Search, analyze, and audit GeminiClaw session logs and memory. Use to investigate past interactions, track token usage, debug tool calls, and monitor agent performance.
Create publication-quality plots and visualizations using matplotlib and seaborn. Works locally with any LLM.
Create, register, and manage custom agent tools and MCP servers to extend AI agent capabilities with external APIs and custom logic.
Automates the lifecycle management of ephemeral Neon PostgreSQL databases for testing, CI/CD, and rapid prototyping workflows.
Development and maintenance of the PWAFire library: build PWA API modules, handle feature detection, manage testing, and contribute to codebase following strict sync/async patterns and error handling requirements.
Autonomous multi-agent orchestration framework for Claude Code with memory-driven workflows, parallel-first task execution, Aristotle-based deconstruction, and multi-stage quality gates.
CLI interface for Gemini AI, enabling one-shot model inference, text generation, and JSON-formatted data extraction for OpenClaw users.
World-class senior data engineering skill for building scalable data pipelines, ETL/ELT systems, and modern data infrastructure using Python, Spark, dbt, and Kafka.
Standardized Java development guidelines including naming conventions, exception handling, Spring Boot best practices, and concurrency patterns.
Full-stack SDLC agent workflow managing the entire production lifecycle from intake and planning to automated testing, CI/CD, and infrastructure deployment using MCP tools.
Automated single-cell RNA-seq quality control pipeline following scverse best practices. Performs MAD-based outlier detection, cell filtering, and diagnostic visualization for .h5ad and .h5 datasets.