agentready
Assess code repository readiness for AI-assisted development
Install & Use
Copy this prompt and send it to your AI assistant (Claude / Cursor / TRAE / Codex / WorkBuddy etc.) to auto-install:
Help me install this AI Skill: agentready. It is used for: Assess code repository readiness for AI-assisted development Full Skill content: https://321skill.com/skills/agentready/raw/index.md Read that page and install it.
The prompt includes a link to the full Skill content. You can also view the full content.
AgentReady is a research-based code repository assessment tool designed to help developers measure how well their projects are adapted for AI-assisted development workflows. It evaluates a repository's "AI readiness" by analyzing multiple dimensions such as code quality, documentation, testing, and infrastructure.
The tool scans your codebase and generates an overall score (Platinum/Gold/Silver/Bronze tier), an interactive HTML report, and a version-controlled Markdown report. The report not only identifies issues but also provides specific remediation tools, commands, and examples to help you systematically improve your project.
It is ideal for developers, technical leads, and project managers who want to enhance team development efficiency, introduce AI coding assistants (such as GitHub Copilot, Cursor), or ensure their codebase is AI-tool friendly. For open-source project maintainers, it is also an effective tool to demonstrate project maturity and contributor-friendliness.
We recommend starting by evaluating your own project, focusing on the "Actionable Remediations" section in the report. For large repositories, please note any warnings the tool may issue during the first assessment. Running regular assessments helps track improvement progress.
Key Features
Its evaluation framework is not based on subjective experience but on comprehensive research from over 50 authoritative sources (including Anthropic, Microsoft, Google, and academic institutions). Each evaluation attribute is supported by peer-reviewed research or industry best practices.
Limitations
Primarily focuses on assessing the static attributes and structure of a codebase; it does not directly evaluate the actual performance of AI models on specific coding tasks or the dynamic interaction capabilities of agents.
FAQ
How is AgentReady different from traditional code quality scanning tools?
Traditional tools (e.g., SonarQube) focus on code defects and security vulnerabilities, while AgentReady specifically evaluates whether a codebase has the structure, documentation, and patterns that facilitate AI understanding and collaboration, aiming to optimize human-machine collaboration efficiency.
How long does it take to evaluate a large repository?
The time depends on the repository's size and complexity, but it is typically fast. The tool provides a confirmation prompt for large repositories; when using a container runtime, interactive confirmation can be performed via the `-i` flag.
Installation guide for AI assistants
If your AI coding assistant (Claude Code, Cursor, TRAE etc.) can see this page, send it this message to auto-install:
Visit https://321skill.com/skills/agentready/raw/index.md to read the original Skill definition (Markdown format) for agentready, and install it according to the instructions.
Raw Markdown URL for AI: /skills/agentready/raw/index.md