agent: lumotia-rebrand — docs, scripts, root config, residuals

Phase 9 of the rebrand cascade. Sweep covers everything the Phase 8
frontend pass deliberately skipped: docs/, root markdown, scripts,
Cargo.toml descriptions, code comments that survived earlier
word-boundary sed, plus a handful of identifiers caught on the final
verify pass.

transcription-app changes:
- README.md, HANDOVER.md, KNOWN-ISSUES.md, run.sh — magnotia/Magnotia
  -> lumotia/Lumotia.
- docs/ — sweep across all subdirs except docs/handovers/ (preserved
  as immutable audit trail). Includes architecture-map references
  to magnotia_core::*, magnotia_storage::*, etc. now pointing at
  lumotia_*; dev-setup.md tracing output examples (lumotia_startup
  target); brief/ + superpowers/ + issues/ + whisper-ecosystem/ +
  audit/.
- Cargo.toml descriptions on 9 crates (core, audio, cloud-providers,
  hotkey, llm, mcp, plus referenced others).
- crates/core/src/{error,hardware,recommendation,paths}.rs +
  crates/audio/src/wav.rs + crates/llm/src/model_manager.rs +
  crates/cloud-providers/src/keystore.rs + crates/mcp/src/lib.rs —
  doc comments and a model-manager user-agent string.
- Caught on final pass: BroadcastChannel("magnotia_task_sync") -> ...
  ("lumotia_task_sync"); magnotia_locale i18n localStorage key
  renamed + migration shim added; CSS keyframe names
  magnotiaPulse / magnotiaBar / magnotiaFade renamed in the design-
  system kit; magnotia_viewer_item / magnotia_viewer_mode handoff
  keys renamed in HistoryPage + viewer/+page.svelte; src/assets/
  wordmark.svg text.
- src-tauri/src/lib.rs comment cleanup ("magnotia era" was sed'd
  to "lumotia era" earlier — restored).

Preserved (intentional):
- crates/core/src/paths.rs — keeps "magnotia" / "Magnotia" / ".magnotia"
  legacy detection strings in legacy_and_target_paths() so the
  migration shim can still find user data from the magnotia era.
- src/lib/stores/{page,focusTimer}.svelte.ts + src/lib/i18n/index.ts
  — migration call sites reference the legacy magnotia keys
  deliberately.
- docs/handovers/ — historical audit trail.

cargo build --workspace passes. npm run check: 0 errors / 0 warnings
(3958 files). cargo test --workspace: 339 pass / 0 fail.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

docs/brief/b2b-enterprise.md

@@ -1,4 +1,4 @@
-<!-- Source: Magnotia Master Brief — §19 B2B & Enterprise Angle -->
+<!-- Source: Lumotia Master Brief — §19 B2B & Enterprise Angle -->
 
 ## 19. B2B & Enterprise Angle
 
@@ -18,23 +18,23 @@
 - Explicitly covers ADHD and other neurodivergent conditions under the Equality Act 2010
 - Software subscriptions, planning apps, and coaching are all fundable
 - Deepwrk already operates as an Access to Work-approved service — employees claim subscriptions through their grant
-- **This is the single highest-leverage B2B action Magnotia can take.** Government effectively subsidises the sale.
+- **This is the single highest-leverage B2B action Lumotia can take.** Government effectively subsidises the sale.
 
 ### B2B requirements (if/when pursued)
 - Admin dashboard, SSO (SAML/OAuth), bulk provisioning
 - Anonymised usage analytics for HR (never individual-level data)
-- **Anonymised organisational dashboards.** While Magnotia processes all personal data locally, the B2B tier must output high-level, anonymised telemetry to satisfy enterprise buyers who need metrics to justify software purchases. Examples: "Your team saved 40 hours in task-planning this month", "Average time-to-capture across your organisation: 6 seconds", "82% of users returned after a gap of 3+ days." Critically, these metrics must be aggregated (minimum cohort size of 10 before any data is surfaced), never traceable to individuals, and opt-in at both the user and organisation level. The local-first architecture makes this possible: anonymised summaries can be generated on-device and transmitted as aggregate statistics only — raw data never leaves the machine.
+- **Anonymised organisational dashboards.** While Lumotia processes all personal data locally, the B2B tier must output high-level, anonymised telemetry to satisfy enterprise buyers who need metrics to justify software purchases. Examples: "Your team saved 40 hours in task-planning this month", "Average time-to-capture across your organisation: 6 seconds", "82% of users returned after a gap of 3+ days." Critically, these metrics must be aggregated (minimum cohort size of 10 before any data is surfaced), never traceable to individuals, and opt-in at both the user and organisation level. The local-first architecture makes this possible: anonymised summaries can be generated on-device and transmitted as aggregate statistics only — raw data never leaves the machine.
 - GDPR compliance documentation, zero-IT-lift deployment
 - Users must never be identifiable as neurodivergent to their employer
 - Position under "universal design" framing — beneficial for all employees
 
 ### Enterprise IT deployment
-Magnotia's local-first architecture is simultaneously its biggest B2B selling point and its biggest deployment challenge. Key considerations:
+Lumotia's local-first architecture is simultaneously its biggest B2B selling point and its biggest deployment challenge. Key considerations:
 
 - **Local AI model size.** Whisper models range from ~75MB (tiny) to ~1.5GB (large). Enterprise IT teams may flag large binaries or models downloaded to employee machines. Solution: bundle a smaller model by default (tiny/base) with optional upgrade to larger models. Document the model sizes and what they do for IT review.
-- **No cloud = no enterprise compliance headaches.** Because Magnotia processes everything on-device with no data transmitted externally, it bypasses the cloud security review, vendor risk assessment, and data processing agreements that typically delay enterprise software procurement by 3–6 months. This is a genuine competitive advantage — frame it explicitly in B2B sales materials.
-- **Installation permissions.** Enterprise-managed machines often restrict software installation. Magnotia must be deployable via MDM (Mobile Device Management) tools like Microsoft Intune or Jamf. Tauri's MSIX (Windows) and DMG (macOS) formats are compatible with standard enterprise deployment pipelines.
-- **No internet dependency.** Magnotia does not require network access for core functionality. This makes it deployable in air-gapped, high-security, or restricted-network environments — a strong selling point for defence, legal, and healthcare settings.
+- **No cloud = no enterprise compliance headaches.** Because Lumotia processes everything on-device with no data transmitted externally, it bypasses the cloud security review, vendor risk assessment, and data processing agreements that typically delay enterprise software procurement by 3–6 months. This is a genuine competitive advantage — frame it explicitly in B2B sales materials.
+- **Installation permissions.** Enterprise-managed machines often restrict software installation. Lumotia must be deployable via MDM (Mobile Device Management) tools like Microsoft Intune or Jamf. Tauri's MSIX (Windows) and DMG (macOS) formats are compatible with standard enterprise deployment pipelines.
+- **No internet dependency.** Lumotia does not require network access for core functionality. This makes it deployable in air-gapped, high-security, or restricted-network environments — a strong selling point for defence, legal, and healthcare settings.
 - **Automatic updates.** Enterprise IT will want to control update rollouts. Provide the option to disable auto-updates and instead distribute updates through enterprise channels.
 
 ### Channel partners