Can I vibecode Napkin?

Build a usable personal replacement for the core loop of Napkin, a spatial/visual idea collection tool.
Use exactly this stack: Tauri 2 + React + TypeScript + SQLite.
Primary job: Build a local-first idea collection app that emphasizes extremely fast capture, full-text search, backlinks, tagging, and Markdown export, focused on organizing small snippets of thought.

Start from an empty folder and create the complete working project.
Make the default mode single-user and private. All data must live in a local SQLite database managed by Tauri's Rust backend.

Feature Requirements:
1. Fast Capture: Provide a global hotkey (via Tauri) that opens a quick-entry window regardless of what the user is doing. Hitting enter saves the snippet and closes the window.
2. The Canvas/Stream: The main UI should display snippets in a masonry or canvas layout. The interface must be minimal and fluid, encouraging exploration of past thoughts.
3. Organization: Automatically extract #tags from the content. Support wikilink-style [[backlinks]] to connect snippets.
4. Search: Implement fast, full-text search across all snippets.
5. Export: Include a robust Markdown export feature so the user is never locked in. Snippets should be exported with their tags as frontmatter and backlinks preserved.
6. UI/UX: Use accessible keyboard navigation, labels, focus states, and sensible contrast. Include clear empty, loading, validation, success, and failure states.

Constraints & Scope:
- Do not add analytics, telemetry, ads, or third-party accounts.
- Use realistic sample data that is clearly labelled and easy to delete to demonstrate the canvas view immediately.
- Deliberately exclude these paid-product advantages: conflict-safe multi-device sync, mobile apps, mature third-party importers, and collaborative editing. Do not fake integrations or AI auto-tagging.

Deliverables:
- Complete Tauri + React source code.
- Write focused unit tests for the SQLite data model and the markdown parsing logic (extracting tags/links).
- Add one end-to-end smoke test that proves the core loop works (creating a snippet, tagging it, and finding it in search).
- Create a README with setup, architecture, data location, backup instructions, and limitations.
- Add scripts for install, development, test, and build. Run tests and build before finishing.