Create project scaffolds with context, memory, and architecture templates.
npx skills add https://github.com/wendeus0/AI-dotfiles --skill onboard-project
Please help me install this Agent Skill. Skill: onboard-project Source: https://github.com/wendeus0/AI-dotfiles/tree/main/core/skills/onboard-project Command: npx skills add https://github.com/wendeus0/AI-dotfiles --skill onboard-project
Initializes a new repository with a complete project scaffold, ensuring essential context, memory, and architecture files exist before the first work session.
Initialize a fresh project structure with a single execution, generating all required files and folders, then start the first session.
High-intent search queries and answers about installing and using this skill.
Project scaffolding generates essential context, memory, and architecture templates like AGENTS.md, CLAUDE.md, and memory/MEMORY.md before opening the first session.
A fresh project architecture requires essential files including AGENTS.md, CLAUDE.md, ERROR_LOG.md, PENDING_LOG.md, memory/MEMORY.md, and docs/architecture templates to manage context and logs.
Creating a project memory and architecture template structure involves generating memory/MEMORY.md alongside docs/architecture/SPEC_FORMAT.md and TDD.md templates, then resolving them in order.
Yes, you can initialize scaffolding for new projects across different tech stacks, as the process generates stack-agnostic context files and architecture templates before triggering the session-open.
The best way to start a new project session is to initialize the repository scaffold first, ensuring required files like ERROR_LOG.md and PENDING_LOG.md are populated, then trigger the session-open.
mdmagnuson-creatorTransform scaffold templates into a ready project structure with configuration and docs.
JZKK720Implement a Test-Driven Development workflow with red-green-refactor cycles.
FFCfelps1Plan, execute, and ship software features with code review and CI/CD integration.
brandonavantLog manual observations with predefined categories to a JSONL case study file.
