Add THE CANONICAL 100: Complete Lucidia language definition through examples

This commit introduces the foundational specification for Lucidia v1.0 - a set
of 100 working example programs that DEFINE the language through demonstration
rather than formal grammar.

Key Philosophy:
- Examples ARE the spec (not documentation OF the spec)
- AI systems learn by reading all 100 examples and extracting patterns
- Humans learn by working through examples sequentially
- No feature exists unless demonstrated in these examples

Structure:
- 001-010: Fundamentals (hello world → functions)
- 011-020: Data & Collections (lists, maps, sets)
- 021-030: Control Flow (if, loops, pattern matching)
- 031-040: Functions & Composition (map, filter, reduce, closures)
- 041-050: UI Basics (forms, inputs, validation)
- 051-060: Reactive Programming (state, watchers, events)
- 061-070: Consent & Privacy (permission system - CORE DIFFERENTIATOR)
- 071-080: Storage & Sync (local-first, cloud-optional)
- 081-090: AI Integration (intent → code, learning user style)
- 091-100: Complete Applications (todo, notes, chat, e-commerce)

Core Language Features Demonstrated:
✓ Intent over ceremony (write WHAT, not HOW)
✓ Consent as syntax (ask permission for: resource)
✓ Local-first storage (store locally, sync to cloud optional)
✓ AI-collaborative (### Intent comments become code)
✓ Reactive by default (state, watch, computed)
✓ Zero setup (runs in browser via WASM)
✓ Multi-paradigm (functional, OOP, reactive, agent-based)
✓ Gradual complexity (hello world → production apps)

Files Created:
- README.md - Learning philosophy and path
- INDEX.md - Complete reference table
- 001-100.lucidia - All example programs

Total: 102 files, ~3,500+ lines of example code

Why This Matters:
This is not just documentation. This IS Lucidia. Every parser, compiler,
AI assistant, and developer tool will be trained on these examples. They
are the permanent, immutable foundation of the language.

Next Steps:
1. Build parser that learns from these examples
2. Train AI to recognize and generate Lucidia patterns
3. Create browser playground with these as gallery
4. Use for academic paper and conference presentations

Designed by: Cece (Principal Language & Runtime Architect)
For: BlackRoad Operating System / Lucidia Programming Language
Status: Complete foundation for implementation

docs/examples/canonical/098-image-gallery.lucidia

@@ -0,0 +1,149 @@
+# 098: Image Gallery
+# Photo gallery with local storage and albums
+
+state images = load "images" locally or []
+state current_album = "all"
+state selected_image = null
+
+# Upload images
+button "Add Photos" -> upload_images()
+
+upload_images():
+  ask permission for: [filesystem.read, storage]
+    purpose: "Upload and save photos"
+
+  if granted:
+    files = open_file_picker(accept: "image/*", multiple: true)
+
+    for file in files:
+      image = {
+        id: generate_id(),
+        name: file.name,
+        data: file.read_as_data_url(),
+        size: file.size,
+        uploaded_at: now(),
+        album: current_album,
+        tags: [],
+        favorite: false
+      }
+
+      images.append(image)
+
+    store images locally as "images"
+    show "Uploaded {files.length} photos"
+
+# Create album
+form create_album:
+  input album_name -> new_album
+
+  button "Create Album" -> create_album_action(new_album)
+
+create_album_action(name):
+  # Albums are derived from image data
+  current_album = name
+  show "Album '{name}' created"
+
+# Move to album
+move_to_album(image_id, album):
+  images = images.map(img => {
+    if img.id == image_id:
+      { ...img, album: album }
+    else:
+      img
+  })
+
+  store images locally as "images"
+
+# Toggle favorite
+toggle_favorite(id):
+  images = images.map(img => {
+    if img.id == id:
+      { ...img, favorite: not img.favorite }
+    else:
+      img
+  })
+
+  store images locally as "images"
+
+# Delete image
+delete_image(id):
+  ask "Delete this image?" -> confirm
+
+  if confirm == "yes":
+    images = images.filter(img => img.id != id)
+    store images locally as "images"
+    selected_image = null
+
+# Filter by album
+computed filtered_images = images.filter(img => {
+  current_album == "all" or img.album == current_album
+})
+
+# Get unique albums
+computed albums = images
+  .map(img => img.album)
+  .unique()
+  .sort()
+
+# Album switcher
+show "Albums:"
+button "All ({images.length})" -> current_album = "all"
+
+for album in albums:
+  count = images.filter(img => img.album == album).length
+  button "{album} ({count})" -> current_album = album
+
+# Gallery grid
+show_gallery_grid:
+  for image in filtered_images:
+    show_thumbnail:
+      src: image.data
+      name: image.name
+      favorite: image.favorite
+      on_click: () => selected_image = image
+      on_favorite: () => toggle_favorite(image.id)
+
+# Lightbox view
+if selected_image != null:
+  show_lightbox:
+    image: selected_image.data
+    name: selected_image.name
+    size: format_file_size(selected_image.size)
+    uploaded: format_date(selected_image.uploaded_at)
+
+    button "Close" -> selected_image = null
+    button "Delete" -> delete_image(selected_image.id)
+    button "Previous" -> show_previous()
+    button "Next" -> show_next()
+
+show_previous():
+  index = filtered_images.find_index(img => img.id == selected_image.id)
+  if index > 0:
+    selected_image = filtered_images[index - 1]
+
+show_next():
+  index = filtered_images.find_index(img => img.id == selected_image.id)
+  if index < filtered_images.length - 1:
+    selected_image = filtered_images[index + 1]
+
+# Auto-tag with AI
+button "Auto-Tag All" -> auto_tag_images()
+
+auto_tag_images():
+  for image in images:
+    if image.tags.length == 0:
+      tags = ai.classify(image.data, {
+        categories: ["nature", "people", "food", "architecture", "animals"],
+        multiple: true
+      })
+
+      image.tags = tags
+
+  store images locally as "images"
+  show "Images auto-tagged"
+
+generate_id():
+  return now() + Math.random()
+
+format_file_size(bytes):
+  return "{(bytes / 1024).toFixed(1)} KB"