What problem does it solve?
New users of a generated AI-assisted project often face ambiguity about where to start, which environment and editor to use, and which configuration choices were made during bootstrap. This Skill centralizes setup discovery, prevents redundant questions by reading on-disk bootstrap artifacts, and produces a durable onboarding report that captures decisions and next steps.
Core Features & Use Cases
- Bootstrap reconciliation: Reads .aidd/bootstrap-config.json and execution-plan artifacts to reconcile declared preferences with runtime state and silently apply authoritative bootstrap values where required.
- Tool and environment assessment: Detects local tooling availability, maps it to recommended environment/editor paths, and surfaces explicit installation steps and trade-offs when alternatives exist.
- Guided decisioning and state updates: Presents one clear recommended path with progressive disclosure of alternatives, updates execution-plan/project-state.yaml (next_action), and enforces human review gates for documentation.
- Durable reporting: Renders a consistent onboarding report (execution-plan/reports/onboarding/onboarding-report.md) from a template, acknowledges provenance of fields, and points to the single next AI-driven command.
Quick Start
Run the core-onboarding skill to reconcile bootstrap state, check local tool readiness, and generate execution-plan/reports/onboarding/onboarding-report.md.