Stage 0: Research Brief -- Comp-Core Production Map
Comp-Core is a monorepo at `Desktop/Comp-Core/` containing 73 components across 8 domain layers, 13 packages, ~30 applications, and 4 backend services. It started as a motion-intelligence system for computational choreography and has grown into Mohamed's full infrastructure backbone: retrieval (RAG++), semantic graph (Graph Kernel), agent orchestration, audio synthesis (Echelon), gateway connectors, and ML pipelines.
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Stage 0: Research Brief -- Comp-Core Production Map
What Is Comp-Core
Comp-Core is a monorepo at `Desktop/Comp-Core/` containing 73 components across 8 domain layers, 13 packages, ~30 applications, and 4 backend services. It started as a motion-intelligence system for computational choreography and has grown into Mohamed's full infrastructure backbone: retrieval (RAG++), semantic graph (Graph Kernel), agent orchestration, audio synthesis (Echelon), gateway connectors, and ML pipelines.
Version: 0.1.0. Last INDEX.md update: 2025-02-02. Actual development has continued aggressively through Q1 2026.
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The 8 Core Layers -- Real State
Layer 1: Runtime (core/runtime/) -- ~87K lines
| Project | Lang | Claimed Status | Real State |
|---|---|---|---|
| cc-core | Python | Complete | Python LIM-RPS algorithms. Has pyproject.toml + requirements.txt. Foundational. Works. |
| cc-core-rs | Rust/Py | Complete | DSP kernels, lock-free buffers. Has Cargo.toml + pyproject.toml (PyO3). |
| cc-kernel | Rust | Substantial | SMART execution kernel. Has Cargo.toml. No release binary found. |
| cc-protocol | Rust | Complete | Unified protocol definitions. Has Cargo.toml. |
| cc-migration-architect | TS | Present | Has package.json. Schema migration tooling. |
Honest assessment: Runtime layer is the most stable. cc-core and cc-core-rs are genuinely complete. cc-kernel has code but "substantial" means it compiles, not that it's battle-tested under load.
Layer 2: Motion (core/motion/) -- ~51K lines
| Project | Lang | Claimed Status | Real State |
|---|---|---|---|
| cc-types | Rust | FROZEN | Core motion types. Intentionally locked. |
| cc-anticipation | Rust/Py | Complete | Anticipation kernel with 7 scalars. Has target/ dir (was compiled). |
| cc-collection | Rust/Py | Complete | Extended Kalman Filter fusion. Has target/ dir. |
| cc-gesture | Rust | Partial | Has target/ dir but gesture recognition is incomplete. |
| cc-window-aligner | Rust | 99 | |
| cc-motion-utils | TS | Planned | Does not exist as real code. |
| sensor-pipeline | -- | Present | Listed in directory, not in INDEX.md. |
Honest assessment: The motion math works. The integration story between motion and audio (the whole point of computational choreography) has gaps, specifically cc-gesture and the window-aligner integration hole.
Layer 3: Semantic (core/semantic/) -- ~70K lines
| Project | Lang | Claimed Status | Real State |
|---|---|---|---|
| cc-semantic | Rust | FROZEN | Replay-stable semantic frames. Locked. |
| cc-semantic-language | Rust/Py | Complete | N'Ko operator-based processing. |
| cc-cognitivetwin-bridge | Rust | Complete | Conversation DAG bridge with FFI. |
| cc-graph-kernel | Rust | Complete | Deterministic context slicing. Has release binary (graph_kernel_service). Actually deployed as LaunchAgent on cloud-vm. Port :8001. |
| cc-inscription | Rust | Complete | N'Ko inscription compiler. Has target/ dir. |
Honest assessment: This is the strongest layer. Graph Kernel is genuinely production -- it has a compiled binary, a LaunchAgent plist, health check endpoints, and runs against Supabase PostgreSQL. cc-inscription powers the anticipation geometry research (validated with 40K records in Supabase).
Layer 4: Retrieval (core/retrieval/) -- ~6.7M lines (inflated by data/generated files)
| Project | Lang | Claimed Status | Real State |
|---|---|---|---|
| cc-rag-plus-plus | Rust/Py | Complete | FastAPI service at :8000. Has .venv. Actually deployed as LaunchAgent. 332K rows re-embedded with OpenAI text-embedding-3-small. pgvector search live. |
| cc-retrieval | Rust | Complete | Phrase selection contracts, ~2200 lines. |
| cc-context-recovery-mcp | Python | Complete | MCP server for context recovery. |
| cc-idea-vault | Rust/Py | Substantial | Research idea management. |
| cc-context-intelligence | -- | Present | Not in INDEX.md. Exists in directory. |
| cc-retrieval-indexer | -- | Present | Not in INDEX.md. Exists in directory. |
| cc-vault-mcp | -- | Present | Not in INDEX.md. Exists in directory. |
Honest assessment: RAG++ is genuinely production. It has a running service, LaunchAgent, health endpoint, 332K embedded rows. The line count is inflated by data files in the directory tree. The MCP servers (context-recovery, vault) are functional but not load-tested. Three projects in the directory aren't even listed in INDEX.md -- the index is stale.
Layer 5: Audio-Media (core/audio-media/) -- ~107K lines
| Project | Lang | Claimed Status | Real State |
|---|---|---|---|
| cc-echelon | Rust | Partial | 19 nested crates. Has release binary (libmotion_bridge). Biggest codebase in the monorepo. The canonical gap: Layer 4 Temporal Intelligence not built (phase extraction, soft tempo, adaptive bar boundaries). |
| cc-dj | Rust/Py | Substantial | DJ control with Gemini integration. Has target/ dir. |
| cc-speak | Rust/Py | Complete | Audio capture engine. Has target/ dir. SpeakFlow V2 evolved from this. |
| cc-stream | Rust | Partial | Streaming infrastructure. Has target/ dir. |
| cc-cinematographer | Rust | Substantial | Video processing (beat-sync, Ken Burns). Has target/ dir. FFmpeg/HLS export stubs only. |
| cc-event-bus | Rust | Complete | Event routing, pub/sub. Has target/ dir. |
Honest assessment: This is the most ambitious and most incomplete layer. Echelon alone is 19 crates, but the critical gap (temporal intelligence -- what makes "performer = clock" true) is explicitly unbuilt. cc-cinematographer has stubs where real FFmpeg calls should be. cc-stream is partial. The event-bus works. cc-speak works. But the integrative vision of "motion drives audio in real-time" is not production-ready.
Layer 6: Agents (core/agents/) -- ~44K lines
| Project | Lang | Claimed Status | Real State |
|---|---|---|---|
| cc-agent | Rust | Complete | Multi-provider agent client. Has Cargo.toml. |
| cc-agent-daemon | TS | Complete | Task polling daemon. Has node_modules, actually installed. |
| cc-agent-sdk | TS | Complete | TypeScript agent presets. |
| cc-conductor | Rust | Complete | Control-theoretic policy layer. Has target/ dir (no release binary). |
| cc-orchestrator-agent | Rust | Complete | Multi-agent task orchestrator. |
| cc-training-orchestrator | Python | Complete | ML training pipeline. Has requirements.txt. |
| cc-project-spawner | TS | Partial | Has node_modules. Project scaffolding. |
| cc-spawn-test | TS | Partial | Agent spawn testing. |
Honest assessment: The agent layer is well-coded but redundant with external systems. meshd (Rust PTY daemon at :9451) and the pane orchestrator have largely replaced what cc-conductor and cc-orchestrator-agent were designed to do. The agent-daemon polls Supabase for tasks -- it works, but the multi-agent mesh has moved to tmux injection + NATS, not this polling model. There's overlap that needs resolution.
Layer 7: Gateways (core/gateways/) -- ~28K lines
| Project | Lang | Claimed Status | Real State |
|---|---|---|---|
| cc-relay | Rust | Complete | Mocopi UDP relay with TLV parsing. |
| cc-gemini | Rust | Complete | Gemini API client. Has target/ dir. |
| cc-sms-gateway | Rust | Substantial | Twilio SMS webhooks. |
| cc-telegram-gateway | Rust | Stub | Not implemented. |
| cc-claude-code-gateway | Rust | Stub | Not implemented. |
| cc-bridged | Rust | Deployed | 4MB arm64 binary. 3 adapters (OSC :9462, WS :9463, Supabase). Actually deployed. |
| cc-discord-gateway | -- | Present | In directory but not in INDEX.md. |
| clawdbot-integration | -- | Present | In directory but not in INDEX.md. |
Honest assessment: cc-bridged is the winner here -- it's compiled, deployed, and replaces 15+ Python/Node bridges. cc-relay works for Mocopi. The SMS gateway is substantial. Two stubs (telegram, claude-code) are dead weight. Two projects aren't in the INDEX. The INDEX is stale again.
Layer 8: ML (core/ml/) -- ~96K lines
| Project | Lang | Claimed Status | Real State |
|---|---|---|---|
| cc-ml | Python | Substantial | Motion synthesis, diffusion models. |
Honest assessment: One project, ~96K lines of Python. This is the training pipeline for motion synthesis. Separate from KARL (which lives in Desktop/karl/) and Thunder-Train (distributed MLX). The ML work has fragmented across the mesh -- Mac4/Mac5 do the actual compute, this directory has the pipeline definitions. Whether it runs end-to-end without manual intervention is unclear.
Additional Layers (Not in CLAUDE.md's 8-layer table)
| Layer | Path | Real State |
|---|---|---|
| orchestrators | core/orchestrators/ | cc-pulse-orchestrator (Rust, partial), beyond (Rust, has release binary) |
| vision | core/vision/ | cc-perception-mesh (0 lines currently) |
| mesh-compute | core/mesh-compute/ | Rust workspace, 543 lines. Cargo.toml present. |
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The Packages Layer (packages/) -- 13 packages
| Package | Lang | Lines | State |
|---|---|---|---|
| admissibility-kernel-py | Rust/Py | 205K | PyO3 bindings. The line count includes generated/compiled artifacts. |
| cognitive-twin | Python | 32K | User pattern learning, DPO. V3.0.0. Substantial. |
| cc-voice-unified | TS | 5.3K | Voice command grammar. Has vitest tests. |
| cc-event-sourcing | TS | 2.9K | CQRS/DDD patterns. |
| cc-cognitive-pulse | TS | 2.4K | CognitiveTwin for Pulse. |
| anticipation-geometry | Python | 2.2K | Research package. Validated with Supabase data. |
| cc-evolution-framework | TS | 827 | Creative evolution. |
| cc-voice-pipeline | TS | 636 | Voice processing. package.json present. |
| admissibility-kernel | Rust | -- | DAG context slicing. |
| rag-plusplus-core | Rust | -- | SIMD vector search core. |
| rag-plusplus-py | Rust/Py | -- | PyO3 bindings for RAG++. |
| shared | -- | 61 | Shared utilities. |
---
Applications -- ~30 apps across 5 platforms
Trajectory Suite: 11 apps (search, orbit, analytics, desktop, mobile, walk, ios, latent-browser, novel, dream-studio, kinetic-theater, research-browser). trajectory-search and trajectory-orbit have compiled Rust binaries.
Web Apps: 9 Next.js apps. cc-dashboard is the main one. learnnko, skills-graph, cc-rag-viz are active.
iOS: 3 apps in Comp-Core (EchelonCapture, CinemaWalk, cc-handguard). Plus 43+ additional iOS apps elsewhere in the fleet.
Desktop: Echelon (Tauri/Rust).
HEF Evolutions: 2 experimental web apps (aesthetic-dna, failure-museum).
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Infrastructure That Actually Runs
| Service | Port | Deployment | Status |
|---|---|---|---|
| Graph Kernel | :8001 | LaunchAgent on cloud-vm | LIVE |
| RAG++ | :8000 | LaunchAgent on Mac1 | LIVE (was offline in March, recovered) |
| Orbit | cloud | Cloud Run | LIVE |
| cc-bridged | :9462/:9463 | Binary on Mac1 | LIVE |
| meshd | :9451 | LaunchAgent all machines | LIVE |
| NATS | :4222 | Mac1 | LIVE |
| OPA | :8181 | Mac1 | LIVE |
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The Gap Between Built and Production
### What "production" means here
Mohamed's mesh is not a SaaS startup. "Production" means: the service starts automatically (LaunchAgent/systemd), survives reboot, has health checks, logs to a known location, and other services depend on it without manual intervention.
### Actually production (4 projects)
1. cc-graph-kernel -- binary, LaunchAgent, health check, Supabase backend
2. cc-rag-plus-plus -- venv, LaunchAgent, health check, 332K rows
3. cc-bridged -- binary, 3 adapters, deployed
4. cc-event-bus -- works as internal pub/sub
### Could be production with 1-2 days work (6 projects)
1. cc-core / cc-core-rs -- stable but no service layer
2. cc-anticipation -- works but needs deployment wrapper
3. cc-inscription -- works, used in research
4. cc-relay -- works for Mocopi
5. cc-speak -- works for audio capture
6. cc-agent-daemon -- polls tasks, needs LaunchAgent
### Prototype / substantial but not deployable (12 projects)
cc-echelon, cc-dj, cc-cinematographer, cc-stream, cc-conductor, cc-orchestrator-agent, cc-gesture, cc-window-aligner, cc-sms-gateway, cc-ml, cc-kernel, cc-pulse-orchestrator
### Stubs / dead weight (4 projects)
cc-telegram-gateway, cc-claude-code-gateway, cc-motion-utils, cc-perception-mesh
### Experimental / may abandon (4 projects)
latent-browser, novel, aesthetic-dna, failure-museum
---
Build System -- Current State
There is no unified build system. The current state:
- Rust projects: Individual Cargo.toml files. No workspace Cargo.toml at root. Each project compiles independently. Some have release binaries, most have only debug builds or no builds at all.
- Python projects: Mix of pyproject.toml, requirements.txt, and setup.py (root level). No unified virtual environment. RAG++ has its own .venv.
- TypeScript projects: Individual package.json files. No monorepo tool (no turborepo, no nx, no pnpm workspace). Each has its own node_modules.
- Docker: docker-compose.yml exists but references an old inference service. Not used for current production services.
- CI/CD: 8 GitHub Actions workflows exist (ci.yml, rust-tests.yml, etc.) but their actual run state is unknown.
- Makefile: Exists but targets are for Episode 1 (the original motion capture project), not the full monorepo.
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Source Signals
1. INDEX.md (2025-02-02) -- comprehensive but stale. Missing 5+ projects that exist in directories.
2. STRUCTURE.md -- matches reality for top-level dirs.
3. CLAUDE.md (in Comp-Core) -- accurate for service ports and running state.
4. HEALTH-REPORT-20260301.md -- honest about RAG++ and GK being down. RAG++ has since recovered.
5. *CP- completion files -- 10 completed project plans. Evidence of real execution.
6. Agent memory -- comp-core-layers.md reference exists but file was missing from pulse-runner memory. Echelon canonical gap documented separately.
7. Filesystem scan** -- 73+ components verified. Release binaries confirmed for: graph-kernel, bridged, beyond, echelon (libmotion_bridge only).
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Key Tensions
1. Monorepo without monorepo tooling. 73 components, no workspace build, no dependency graph enforcement.
2. Three languages, zero unified CI. Rust/Python/TypeScript each have their own world. No single `make build-all` that works.
3. INDEX.md drift. The authoritative index hasn't been updated in 14 months. Reality has outgrown documentation.
4. Agent layer redundancy. cc-conductor, cc-orchestrator-agent, meshd, pane-orchestrator, and NATS all do overlapping work.
5. Audio-media ambition vs. reality. Echelon is 19 crates and 107K lines but temporal intelligence (the core differentiator) isn't built.
6. Production services run but aren't reproducible. Graph Kernel and RAG++ work, but deploying them on a new machine requires manual .env setup, manual binary compilation, and manual LaunchAgent installation.
Promotion Decision
Attach run IDs, datasets, metrics, and reproduction commands.
Source Anchor
evo-cube-output/comp-core-production-map/stage0-research.md
Detected Structure
Method · Evaluation · References · Code Anchors · Architecture · is Stage Research