This GitHub repository provides a collection of best practices for designing and implementing agent skills, focusing on provider-neutral approaches compatible with tools like Codex and Claude Code. It covers agentic workflows, prompt engineering, and the use of MCP (Multi-Modal Controller Protocol). The project aims to help developers build more robust and versatile AI agents.
A starter prompt for Claude Code, what you'll need, and how to reach them.
You are an expert AI agent developer. I need you to create a new agent skill example following the 'agents-best-practices' GitHub repository's guidelines (DenisSergeevitch/agents-best-practices). This skill should be a 'unit test generator' that takes a user-provided JavaScript function and generates appropriate unit tests for it. The core agent logic should be provider-neutral and demonstrate how to integrate with a generic LLM interface, specifically using AI SDK v6 with Gemini. The front-end should be a simple Next.js 16 App Router application (React 19, Tailwind v4) where users can input their function and view the generated tests. Host this on Vercel with Neon Postgres (though the database won't be heavily used for this MVP, set up for future scalability).
Your task is to:
1. Set up a new Next.js project with the specified stack.
2. Implement the AI SDK v6 integration for Gemini to act as the test-generating agent.
3. Design a `provider-neutral` skill interface for the unit test generation within the agent logic.
4. Create a user interface with input fields for the JavaScript function and a display area for the generated tests.
5. Include basic error handling and loading states.
6. Provide clear `README.md` documentation for setting up and running the example, emphasizing how it adheres to the 'agents-best-practices' principles.
Focus on the MVP: just generating tests for one function at a time. Do not implement complex state management or user authentication for this first iteration. Assume the user provides valid JavaScript. Verify by running `npm run dev` and ensuring the UI appears and test generation works for a simple function like `function add(a,b){return a+b;}`.Reach out to AI engineers and developers interested in agentic workflows by contributing concrete, provider-neutral agent skill examples to this repo and promoting Lumivara's MCP starter and agent evaluation tools.
Provider-neutral Agent Skill for Codex, Claude Code, and agentic harness design. Topics: agent-skill, agent-skills, agentic-workflows, agents, ai-agents, anthropic, claude, claude-code, codex, codex-skill, mcp, prompt-engineering.
Open a detailed issue on the GitHub repository, then open a draft pull request with your initial implementation, referencing the issue.
“I've implemented a new 'unit test generator' agent skill example for your `agents-best-practices` repo, designed to be provider-neutral using AI SDK v6 with Gemini. Here's a link to the draft PR and a brief demo; I believe it significantly enhances the practical examples of agent skill design.”
Open the original ↗