Discover codebase conventions and generate project-specific rule templates and seed data.
npx skills add https://github.com/easingthemes/dx-aem-flow --skill dx-scan
Please help me install this Agent Skill. Skill: dx-scan Source: https://github.com/easingthemes/dx-aem-flow/tree/main/plugins/dx-core/skills/dx-scan Command: npx skills add https://github.com/easingthemes/dx-aem-flow --skill dx-scan
Discovers conventions in a codebase and generates concrete, project-specific rule templates and seed data to bootstrap AI-assisted development pipelines.
Run /dx-scan after /dx-init and /dx-adapt to generate rules and seed data for your project.
High-intent search queries and answers about installing and using this skill.
To generate project-specific rules, scan your codebase to discover frontend and backend conventions, which automatically populates concrete rule templates for AI-assisted development. This process also creates seed data describing your architecture and file patterns.
Codebase scanning for AI-assisted development is a process that discovers your project's structural conventions and generates seed data. This provides accurate architectural context, components, and file patterns to bootstrap AI pipelines.
Yes, you need an initialized .ai/config.yaml and a detected project.type before scanning project conventions. You should run initial setup steps like /dx-init and /dx-adapt first to prepare the environment for rule generation.
You should run a codebase scan to generate seed data and rules when setting up new projects or after making significant structural changes. This ensures your AI-assisted development pipeline has accurate, up-to-date architectural context and customized rules.
Scanning your codebase to generate rules preserves idempotency by prompting you before overwriting customized files. This ensures your existing project-specific configurations and templates remain safe during automated seed data generation.
Yes, codebase convention scanning supports AEM considerations if applicable to your repository. It detects your project type and applies AEM-specific logic when generating rule templates and seed data for AI-assisted development.
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