xp-practices
Implement Extreme Programming (XP) practices including TDD, pair programming, and continuous integration to enhance team collaboration and technical excellence in software engineering.
Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
248 skills found
Implement Extreme Programming (XP) practices including TDD, pair programming, and continuous integration to enhance team collaboration and technical excellence in software engineering.
Architects enterprise AI agents from structured specs, generating production-ready code, data flow diagrams, and platform-specific logic for ServiceNow, Salesforce, and Snowflake.
Build distinctive, high-end React Native Expo interfaces using liquid glass design and iOS Human Interface Guidelines for production-grade mobile apps.
Standardize project scaffolding with pre-configured Claude Code directories, commands, and agents to ensure consistency across all your development templates.
Design and document REST or GraphQL APIs, including endpoint definitions, pagination, filtering, versioning, and OpenAPI/Swagger specifications.
Integrate, fix, and debug Duit/flutter_duit backend-driven UI (BDUI) in Flutter applications. Supports remote/static layouts, custom components, transport managers, and lifecycle debugging.
Frontend coding conventions for Preact and Tailwind. Use for web UI components in cluster applications.
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.
Train and manage neural networks in distributed E2B sandboxes using the Flow Nexus platform, supporting custom architectures like Transformers, LSTMs, and GANs.
Execute implementation plans in small, verifiable batches with pause-for-feedback checkpoints to prevent drift and ensure code quality.
Build AI agents with the OpenAI Agents SDK for Python. Supports multi-agent handoffs, function tools, stateful sessions, streaming, and Azure OpenAI integration via LiteLLM.
Standardizes project context by managing artifacts (product, tech-stack, workflow, tracks) in a conductor/ directory. Supports project scaffolding, artifact synchronization, and AI alignment for greenfield and brownfield projects.