data-quality-frameworks
Implement production-grade data quality validation using Great Expectations, dbt tests, and data contracts to ensure reliable pipelines.
Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
207 skills found
Implement production-grade data quality validation using Great Expectations, dbt tests, and data contracts to ensure reliable pipelines.
Pragmatic AI-assisted coding standards focused on clean code, simplicity, and maintainability. Enforces best practices like SRP, DRY, and KISS to prevent over-engineering.
Automated quality gate using 5 parallel AI agents to review code changes for correctness, style, and consistency.
Create structured specifications for platform changes including GitHub issues, SDD templates, and automated type inference for infrastructure and security.
Expert code reviewer for Rust projects. Performs comprehensive quality, security, performance, and architectural analysis using Bazel and project-specific conventions.
Manage, run, and update JS framework benchmarks for the Gea framework, including reporting, HTML result generation, and performance comparisons.
Python coding assistant providing best practices, PEP 8 enforcement, automated testing with pytest, and dependency management using uv.
Automated quality assurance system that validates markdown deliverables against defined checklists for PB-000 market research workflows.
Write high-quality user stories and requirement documents following the INVEST criteria.
A specialized skill for surgical code refactoring. Improves maintainability, reduces technical debt, and applies design patterns without altering external behavior.
IDE-grade project scaffolding wizard for 70+ types of web, mobile, desktop, and backend projects, featuring interactive setup for SDKs, databases, and DevOps configurations.
Implements UI components from Figma/mockups with pixel-perfect accuracy, intelligent design validation, and adaptive agent switching.