setup-project-skills

You can standardize AI agent workflows by defining issue tracking, triage vocabulary, and domain documentation layouts in configuration files like CLAUDE.md or AGENTS.md. This ensures consistent agent behavior and eliminates configuration drift across monorepos or standalone projects.

Configuring AI repository assistants for issue triage involves setting up standardized workflows for GitHub, local markdown, or flat-file tracking. This establishes a common understanding of triage labels so all AI assistants interact with issues uniformly.

Onboarding a new repository for consistent AI assistant behavior requires scaffolding repository configuration files. This process generates or updates the Agent skills block in CLAUDE.md or AGENTS.md to define where to read ADRs and track issues.

Yes, repository scaffolding works with flat-file issue tracking. It configures standardized workflows for GitHub, local markdown, or flat-file formats, ensuring AI agents understand the issue tracking system and triage states regardless of the platform.

Configuration drift happens when repository management lacks standardized definitions for issue trackers, triage states, and domain documentation. Without standardized configuration files, AI assistants interpret repository workflows ambiguously, leading to inconsistent behavior.

You need access to repository root files and the ability to propose and write configuration documentation. This allows you to define domain documentation layouts and architecture decision records locations for AI agent interaction.