Skill UI

This guide provides a comprehensive, production-grade architecture for implementing analytics using PostHog. It covers best practices for event taxonomy design, SDK layering (client and server), feature flag management, and integrating the data pipeline (CDP). Ideal for tracking user lifecycle, feature adoption, and revenue in complex web applications.

Automates Prerender tasks via Composio’s Rube MCP pipeline, covering tool discovery, connection checks, schema-compliant executions, and session-aware workflows that always search for current schemas before running multi-tool operations.

This comprehensive guide provides robust strategies for testing Python code using industry best practices. It covers essential techniques like pytest, fixtures, mocking, parameterization, and implementing Test-Driven Development (TDD). Use this skill when writing unit tests, setting up complex test suites, performing integration testing, or establishing continuous testing infrastructure in CI/CD pipelines.

Expert in designing and implementing advanced Retrieval-Augmented Generation (RAG) pipelines. This role focuses on optimizing the entire information retrieval process—from document chunking and embedding model selection to vector database architectures and hybrid search strategies. The goal is to bridge the gap between raw knowledge documents and accurate LLM understanding, drastically reducing hallucination and enhancing context relevance for enterprise applications.

This skill functions as an expert technical writer, generating comprehensive and structured README.md documentation for software projects. It meticulously analyzes the codebase, identifying project structure, tech stack, prerequisites, dependencies, and deployment pipelines, ensuring users receive a complete guide for local setup and production deployment.

This comprehensive guide details how to configure a complete Continuous Integration and Continuous Deployment (CI/CD) pipeline for Replit applications using GitHub Actions. Learn to connect your GitHub repository, set up automated testing on pull requests, perform post-deployment health checks, and ensure reliable, automated deployment whenever code is pushed.

This comprehensive guide details how to configure robust multi-environment deployments (Development, Staging, Production) within the Replit ecosystem. It covers best practices for database separation, managing environment-specific secrets, implementing reliable environment detection logic, and setting up CI/CD pipelines to ensure applications are stable and secure across all deployment stages.

Provides comprehensive guidance for setting up and configuring Static Application Security Testing (SAST) tools, including Semgrep, SonarQube, and CodeQL. Learn how to integrate security scanning into CI/CD pipelines, define custom security rules, enforce quality gates, and manage compliance policies to proactively identify and remediate code vulnerabilities across multiple programming languages.

A comprehensive guide to implementing secure secrets management practices for Continuous Integration/Continuous Deployment (CI/CD) pipelines. It covers using industry-leading tools like HashiCorp Vault, AWS Secrets Manager, Azure Key Vault, and GCP Secret Manager to securely store, retrieve, and automatically rotate credentials (API keys, database passwords, TLS certificates) without hardcoding them into source code. Includes best practices for least-privilege access and audit logging.

A specialized skill for conducting comprehensive security audits. It identifies vulnerabilities in code, infrastructure, and dependencies, generating structured reports with severity ratings (CVSS) and detailed remediation guidance. Ideal for SAST scans, penetration testing, DevSecOps pipelines, and compliance checks.

This comprehensive guide details the expertise needed for a Senior Data Engineer. It covers building, optimizing, and governing scalable data pipelines and robust ETL/ELT systems using modern tools like Spark, Kafka, Airflow, and dbt. Includes decision frameworks for architecting data solutions (Batch vs Streaming, Lakehouse vs Warehouse) and implementing advanced data modeling patterns.

This comprehensive toolkit provides end-to-end DevOps automation capabilities. It scaffolds CI/CD pipelines (GitHub Actions, CircleCI), generates robust Infrastructure as Code (IaC) modules using Terraform for major clouds (AWS, GCP, Azure), and manages complex Kubernetes deployments (Blue/Green, Rolling). Ideal for automating infrastructure setup, application deployment, and drift management in multi-cloud environments.