AI Skills for Backend Developer

Routes plain-language requests for various coding agents into OpenClaw ACP runtime sessions or direct acpx-driven sessions.

Automates the management of GitHub issues by fetching, fixing, and monitoring PRs using sub-agents for efficient issue resolution.

Enables display of HTML content on OpenClaw-connected nodes, perfect for interactive demos and visualizations.

Guides agents in conducting thorough code reviews for local changes and remote Pull Requests, ensuring code quality and adherence to standards.

Guides users in creating high-quality Pull Requests that adhere to repository standards and templates.

Provides a systematic approach to debugging technical issues by emphasizing root cause investigation before proposing fixes.

Guides developers on effectively receiving and verifying code review feedback to ensure technical correctness and clarity.

Ensures work claims are backed by verification evidence, promoting honesty and accuracy before committing code or creating PRs.

Facilitates the creation of isolated Git worktrees for feature development, ensuring safe directory selection and verification.

Guides developers through the process of completing a development branch with structured options for merging, PR creation, or cleanup.

Facilitates high-quality development through independent task execution and a two-stage review process for efficient implementation.

Creates detailed implementation plans for multi-step tasks, guiding developers through the coding process with clear, actionable steps.

Facilitates test-driven development by ensuring tests are written before code, promoting better software quality and reliability.

Facilitates code reviews to ensure quality and compliance before merging, enhancing development efficiency and collaboration.

Guides the creation of high-quality MCP servers for LLMs, enabling integration with external APIs using Python or TypeScript.

Provides a toolkit for testing local web applications using Playwright, enabling frontend verification and UI debugging.

Automates browser interactions for testing, form filling, and data extraction, enabling efficient web navigation and information retrieval.

Provides patterns for using the Anthropic Claude API in Python and TypeScript, enabling efficient application development.

Ensures code adheres to security best practices, providing a comprehensive checklist for authentication, input validation, and sensitive data handling.

Facilitates multi-agent orchestration using dmux for parallel workflows, enhancing productivity in AI development tasks.