Iris

ILR toolkit for apprenticeship data submission

Iris converts learner data from CSV exports into ILR-compliant XML for ESFA submission, with explicit validation and cross-submission consistency checking.

What It Does

• Parses CSV exports using header-based matching (tolerates column reordering)
• Generates ILR-compliant XML for ESFA submission
• Semantic validation beyond structural XML checks
• Cross-submission consistency checking using historical data
• Dual interface: CLI for automation, native desktop app for non-technical users

Quick Start

# Install dependencies
bun install

# Run CLI locally
bun run src/cli.ts

# Link CLI globally
bun link
iris --help

# Run desktop app in development
bun tauri dev

# Run tests
bun test

Architecture

Built on a shared TypeScript core with two interfaces:

• CLI: Bun runtime, direct filesystem access
• Desktop: Tauri + SvelteKit, native macOS app

Both interfaces use identical transformation and validation logic from src/lib/.

See docs/proposal.md for detailed context.

Project Structure

iris/
├── src/
│   ├── lib/           # Shared core (parser, validator, generator, storage)
│   ├── cli.ts         # CLI entry point
│   └── routes/        # SvelteKit desktop UI
├── src-tauri/         # Tauri Rust backend (generated)
├── docs/              # Documentation, roadmaps, ADRs
└── tests/             # Vitest tests

Development

See .claude/CLAUDE.md for detailed development conventions and commands.

License

MIT