7.2 KiB
7.2 KiB
ByteLyst Workspace Inventory
Purpose: Workspace-level inventory for the active multi-repo ByteLyst development environment. Workspace Root:
~/code/mygh/Canonical Repo List:.windsurf/workflows/repos.txtLast Updated: 2026-03-11
1. Active Workspace Repositories
| Repository | Product / Role | Primary Stack | Current Scope |
|---|---|---|---|
learning_ai_common_plat |
Shared platform | TypeScript, Fastify, Next.js, Swift, Kotlin | 36 shared packages, 4 services, 3 dashboards, MCP/A2A orchestration |
learning_voice_ai_agent |
LysnrAI | Python 3.12, Fastify, Next.js, Swift, Kotlin | Desktop app, product backend, user dashboard, mobile apps |
learning_multimodal_memory_agents |
MindLyst | Kotlin Multiplatform, SwiftUI, Jetpack Compose, Next.js | Shared KMP core, iOS, Android, web dashboard |
learning_ai_clock |
ChronoMind | Next.js, SwiftUI, Kotlin, Fastify | Timer/focus product across web, Apple, Android, backend |
learning_ai_fastgap |
NomGap | React Native (Expo), Fastify | Fasting engine, mobile UI, product backend |
learning_ai_jarvis_jr |
JarvisJr | SwiftUI, Next.js, Kotlin, Fastify | Voice-first coaching apps, marketplace/backend |
learning_ai_peakpulse |
PeakPulse | SwiftUI, Fastify | Sensor-driven tracking app and backend |
learning_ai_notes |
NoteLett | Fastify, Next.js, React Native (Expo) | Structured notes platform across backend, web, and mobile |
learning_ai_flowmonk |
FlowMonk | Fastify, Next.js, React Native (Expo) | Agent-first planning platform across backend, web, and mobile |
2. Shared Platform Repo Role
learning_ai_common_plat is the shared infrastructure layer for the whole workspace.
2.1 Shared Packages
@bytelyst/config,@bytelyst/cosmos,@bytelyst/errors,@bytelyst/logger,@bytelyst/testing@bytelyst/auth,@bytelyst/auth-client,@bytelyst/api-client,@bytelyst/platform-client,@bytelyst/react-auth@bytelyst/blob,@bytelyst/blob-client,@bytelyst/datastore,@bytelyst/storage,@bytelyst/sync,@bytelyst/offline-queue@bytelyst/telemetry-client,@bytelyst/diagnostics-client,@bytelyst/swift-diagnostics@bytelyst/feature-flag-client,@bytelyst/feedback-client,@bytelyst/broadcast-client,@bytelyst/survey-client,@bytelyst/kill-switch-client@bytelyst/design-tokens,@bytelyst/dashboard-components@bytelyst/extraction,@bytelyst/llm,@bytelyst/speech@bytelyst/swift-platform-sdk,@bytelyst/kotlin-platform-sdk,@bytelyst/react-native-platform-sdk
2.2 Services
| Service | Purpose |
|---|---|
platform-service |
Product-agnostic platform APIs: auth, flags, telemetry, diagnostics, jobs, analytics, A/B testing, changelog, webhooks, marketplace, predictive analytics, and more |
extraction-service |
LangExtract-based extraction tasks with Python sidecar |
mcp-server |
MCP tool registry, tool execution, product/operator tools, and A2A orchestration pipelines |
monitoring |
Loki/Grafana and health-check infrastructure |
2.3 Dashboards
| Dashboard | Purpose |
|---|---|
admin-web |
Platform admin console |
tracker-web |
Tracker and public roadmap dashboard |
ux-lab |
Internal UX and ops prototyping workspace |
3. Product Repos and Shared Platform Consumption
| Product | Shared Platform Dependencies |
|---|---|
| LysnrAI | shared packages, platform-service, extraction-service, dashboards integration |
| MindLyst | shared packages, extraction integration, design tokens, platform-service patterns |
| ChronoMind | shared packages, design token flow, platform-service patterns |
| NomGap | React Native platform SDK, shared packages, platform-service patterns |
| JarvisJr | shared SDKs, platform-service, marketplace patterns |
| PeakPulse | Swift platform SDK, shared platform wrappers, design/system patterns |
| NoteLett | shared packages, platform-service, extraction-service, mobile/web client patterns |
| FlowMonk | shared packages, platform-service, offline queue, planning-platform patterns |
4. Workspace Operating Model
- Common platform changes land first when shared packages or shared services change.
- Product repos consume
workspace:*orfile:references during local development. - Repo workflows use
.windsurf/workflows/repos.txtas the source of truth. - Backup, sync, and workspace commit workflows operate across all active repos.
- MCP/A2A capabilities in
learning_ai_common_plat/services/mcp-server/provide cross-product orchestration and operator tooling.
5. Recommended Source-of-Truth Docs
| Scope | Document |
|---|---|
| Common platform repo inventory | docs/learning_ai_common_plat_INVENTORY.md |
| Whole active workspace | docs/WORKSPACE_INVENTORY.md |
| Agent implementation guidance | AGENTS.md |
| High-level architecture | docs/architecture/ECOSYSTEM_ARCHITECTURE.md |
| Canonical active repo list | .windsurf/workflows/repos.txt |
6. Notes
- This document reflects the currently active nine-repo workspace rather than the earlier three-repo migration model.
- Product-specific backends now live in their product repositories, while
learning_ai_common_platremains product-agnostic. mcp-serverandux-labare active capability surfaces and should be included in future inventory updates.