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.
253 skills found
Implement production-grade data quality validation using Great Expectations, dbt tests, and data contracts to ensure reliable pipelines.
Deploy specialized AI swarms to perform comprehensive, multi-domain GitHub pull request reviews covering security, performance, architecture, and style.
Automated code quality validation tool for pre-commit and pre-deploy checks, covering TypeScript, builds, and linting.
Analyzes OpenAPI specifications to generate TypeScript interfaces, API service patterns, and implementation guidance for backend-integrated frontend development.
A comprehensive configuration suite for Claude Code, featuring production-grade agents, skills, hooks, and automated workflows optimized for high-intensity development.
Audit and synchronize the supported LLM model list in assets.py against the authoritative litellm registry.
Expert Swift code review for macOS/iOS. Detects memory leaks, threading bugs, concurrency issues, and accessibility gaps using parallel analysis agents.
Convert PRDs, API docs, and requirements into structured acceptance, testing, integration, and launch checklists.
A structured development process for Python projects using TDD, the uv package manager, and automated testing workflows.
Gate 2 development cycle skill that validates observability implementation, including structured logging, OpenTelemetry tracing, and instrumentation coverage, without modifying code.
PostgreSQL schema and migration expert for Diddit. Manages idempotent SQL files, tables, indexes, and constraints following strict camelCase conventions and transactional safety.
Mutation testing patterns for JS/TS using Stryker. Analyze branch code to find weak or missing tests, verify test effectiveness, and strengthen Node.js test suites.