Repository_Architecture_Unified_Roadmap_Project_Hlidhskjalf.md
Project Hliðskjálf unifies Himinbjörg's visual observation layer and Yggdrasil's cognitive edge runtime into a single modular Raspberry Pi 5 + Hailo co-processor platform for Meta Muse.
- Repository Naming Strategy
- Unified Monorepo Architecture
- Seven-Slice Implementation Roadmap
- Unified Hardware Resource Matrix
- Dependency & Service Architecture
- Implementation Principles
- Definition of Done
- Final Architecture Vision
The unified system combines:
- Himinbjörg: visual observation, telemetry, interaction, and the Omni-HUD
- Yggdrasil: memory, causal modeling, simulation, tools, workers, and edge cognition
- Heimdall: gateway, validation, authentication, and ingress control
- Hailo acceleration: local neural workloads
- Muse integration: host-side harvesting, tool invocation, and structured state exchange
Three repository naming strategies fit the architecture particularly well.
Hliðskjálf is Odin's high seat, positioned above the worlds and associated with the ability to perceive distant realms and observe events across the cosmos.
This name captures the convergence of the two major halves of the platform:
HIMINBJÖRG
Observation / HUD / Perception
│
├──────────┐
│ │
▼ ▼
HLIÐSKJÁLF YGGDRASIL
Unified Node Cognition / Memory / Action
Hliðskjálf therefore represents:
- observation
- awareness
- world-state visibility
- distributed perception
- edge cognition
- action through connected systems
- a unified control and observation point
RuneForgeAI-Project-Hlidhskjalf
or:
hlidskjalf-edge-core
Yggdrasil is the World Tree connecting and supporting the cosmic structure.
Its roots suggest:
- persistent memory
- foundational state
- history
- deep storage
Its trunk suggests:
- shared infrastructure
- causal continuity
- routing
Its branches suggest:
- agents
- tools
- simulations
- displays
- external services
This name emphasizes the Raspberry Pi 5 edge device as a multi-purpose cognitive node extending Muse's central intelligence.
MUSE
│
▼
YGGDRASIL
┌───────┼───────┐
▼ ▼ ▼
Memory Agents Display
│ │ │
▼ ▼ ▼
Kista Draupnir Himinbjörg
Bifröst connects realms.
In this architecture it symbolizes the communication layer joining:
MUSE HOST
│
│ structured state
│ tools
│ telemetry
▼
BIFRÖST
│
▼
EDGE HARDWARE
This name emphasizes:
- bidirectional telemetry
- tool invocation
- JSON-RPC
- MCP
- WebSockets
- host-to-edge communication
- physical/digital integration
| Name | Primary Emphasis | Strength |
|---|---|---|
| Hliðskjálf Edge Core | Unified observation + cognition | Best overall system identity |
| Yggdrasil Omni-Node | Edge cognition + infrastructure | Best engineering-oriented alternative |
| Bifröst Omni-Runtime | Host ↔ edge communication | Best transport-oriented alternative |
PROJECT HLIÐSKJÁLF
Engineering package:
hlidskjalf-edge-core
A single monorepo prevents circular dependencies between Himinbjörg and Yggdrasil while allowing both systems to share:
- event schemas
- RPC contracts
- configuration
- IPC
- model definitions
- deployment tooling
- tests
- telemetry
The architectural rule is:
protocol/
│
┌─────────┴─────────┐
▼ ▼
Yggdrasil Himinbjörg
│ │
└─────────┬─────────┘
▼
IPC
Neither major subsystem should need to import implementation details from the other.
hlidskjalf-edge-core/
├── LICENSE
├── README.md
├── pyproject.toml
├── Makefile
├── config/
│ ├── default_config.yaml
│ └── display_profiles.json
├── protocol/ # Shared Wire Formats & Schemas
│ ├── __init__.py
│ ├── bus.py # Local Pub/Sub Event Bus
│ ├── serialization.py # JSON / MessagePack Encode-Decode
│ └── schemas/
│ ├── envelope.json
│ ├── ttrpg_event.json
│ ├── divination_event.json
│ └── yggdrasil_mcp.json
├── services/
│ ├── yggdrasil/ # Edge Cognitive Co-Processor
│ │ ├── __init__.py
│ │ ├── daemon.py # JSON-RPC / MCP-Facing Core Server
│ │ ├── gateway/
│ │ │ ├── __init__.py
│ │ │ └── heimdall.py # Gateway / Validation / Security
│ │ ├── memory/
│ │ │ ├── __init__.py
│ │ │ ├── kista_vault.py
│ │ │ └── state_cache.py
│ │ ├── world_model/
│ │ │ ├── __init__.py
│ │ │ ├── wyrd_graph.py
│ │ │ └── verdandi_timeline.py
│ │ ├── simulation/
│ │ │ ├── __init__.py
│ │ │ └── seidr_engine.py
│ │ ├── subagents/
│ │ │ ├── __init__.py
│ │ │ └── draupnir_forge.py
│ │ └── sandbox/
│ │ ├── __init__.py
│ │ ├── mythic_coder.py
│ │ └── aesir_runtime.py
│ ├── himinbjorg/ # Omni-HUD Display Engine
│ │ ├── __init__.py
│ │ ├── compositor.py # 60 FPS Render Loop
│ │ ├── canvas_ttrpg.py # Sagnaskemma View
│ │ ├── canvas_divination.py # Celestial / Tarot / Rune View
│ │ ├── canvas_system.py # Yggdrasil Runtime Telemetry
│ │ └── typography.py # Unicode / Rune / Astro Fonts
│ └── hailo/ # Neural Acceleration Layer
│ ├── __init__.py
│ ├── pipeline_manager.py # Runtime / Stream Controller
│ ├── tts_worker.py # Neural Speech
│ └── embed_worker.py # Local Embeddings
├── client/ # Muse Host-Side Integration
│ ├── __init__.py
│ ├── harvester.py # Sagnaskemma / Astrology Interceptor
│ ├── mcp_bridge.py # Muse ↔ Hliðskjálf Tool Bridge
│ └── muse_tool_defs.json # Tool Manifest
├── deploy/
│ ├── systemd/
│ │ ├── hlidskjalf-core.service
│ │ └── hlidskjalf-hud.service
│ ├── install_pi5_dependencies.sh
│ └── setup_hailo10_pcie.sh
└── tests/
├── test_protocol.py
├── test_event_bus.py
├── test_kista_vault.py
├── test_wyrd_dag.py
├── test_seidr_engine.py
├── test_compositor.py
└── e2e_stress_test.py
flowchart LR
HOST["Muse Host"]
CLIENT["client/"]
PROTOCOL["protocol/"]
GATE["Heimdall Gateway"]
YGG["Yggdrasil Services"]
HAILO["Hailo Services"]
HUD["Himinbjörg HUD"]
HOST --> CLIENT
CLIENT --> PROTOCOL
PROTOCOL --> GATE
GATE --> YGG
YGG --> HAILO
YGG --> PROTOCOL
PROTOCOL --> HUD
HAILO --> PROTOCOL
classDef host fill:#21143d,stroke:#a78bfa,stroke-width:2px,color:#ffffff;
classDef protocol fill:#172554,stroke:#60a5fa,stroke-width:2px,color:#ffffff;
classDef core fill:#132e2a,stroke:#34d399,stroke-width:2px,color:#ffffff;
classDef neural fill:#3b1d0b,stroke:#fb923c,stroke-width:2px,color:#ffffff;
classDef display fill:#301934,stroke:#e879f9,stroke-width:2px,color:#ffffff;
class HOST,CLIENT host;
class PROTOCOL,GATE protocol;
class YGG core;
class HAILO neural;
class HUD display;
flowchart TB
S1["SLICE 1<br/>Monorepo Foundation<br/>Wire Protocol & IPC Backbone"]
S2["SLICE 2<br/>Kista Vault & WYRD World Model<br/>Memory & State"]
S3["SLICE 3<br/>Seidr Simulation & Draupnir<br/>Sub-Agent Engine"]
S4["SLICE 4<br/>Himinbjörg Omni-HUD<br/>Multi-Viewport Compositor"]
S5["SLICE 5<br/>Hailo Neural Pipeline<br/>Audio & Embeddings"]
S6["SLICE 6<br/>Host Harvester & Muse<br/>MCP / Tool Integration"]
S7["SLICE 7<br/>End-to-End Integration<br/>Systemd & Autonomous Loops"]
S1 --> S2
S2 --> S3
S3 --> S4
S4 --> S5
S5 --> S6
S6 --> S7
classDef foundation fill:#172554,stroke:#60a5fa,stroke-width:2px,color:#ffffff;
classDef cognition fill:#132e2a,stroke:#34d399,stroke-width:2px,color:#ffffff;
classDef display fill:#301934,stroke:#e879f9,stroke-width:2px,color:#ffffff;
classDef neural fill:#3b1d0b,stroke:#fb923c,stroke-width:2px,color:#ffffff;
classDef integration fill:#21143d,stroke:#a78bfa,stroke-width:2px,color:#ffffff;
class S1 foundation;
class S2,S3 cognition;
class S4 display;
class S5 neural;
class S6,S7 integration;
Establish the unified repository structure, deterministic communication contracts, and high-speed local inter-process communication backbone.
- Initialize the monorepo directory tree.
- Create
pyproject.toml. - Create
Makefile. - Create project-wide configuration files.
- Add test infrastructure.
- Define module ownership boundaries.
- Add logging conventions.
Implement:
protocol/schemas/envelope.json
The envelope should provide:
- protocol version
- timestamp
- session ID
- source
- destination
- event type
- correlation ID
- priority
- payload
Example:
{
"version": "1.0.0",
"timestamp": 1791349200000,
"session_id": "550e8400-e29b-41d4-a716-446655440000",
"source": "yggdrasil",
"destination": "himinbjorg",
"event_type": "wyrd.entity.updated",
"correlation_id": "f845041d-9805-40ca-a52e-04a61a58c5be",
"priority": "normal",
"payload": {}
}Implement:
protocol/bus.py
The bus should support:
publish(topic, payload)
subscribe(topic, callback)
unsubscribe(topic, callback)
Suggested topic families:
agent.*
ttrpg.*
divination.*
wyrd.*
verdandi.*
kista.*
seidr.*
draupnir.*
coder.*
hailo.*
hud.*
system.*
Recommended local socket:
/tmp/hlidskjalf_ipc.sock
Architecture:
Producer
│
▼
Pub/Sub Bus
│
├── Local Python Consumers
│
└── Unix Domain Socket
│
▼
External Services
Support:
JSON
MessagePack
Optional future formats:
CBOR
FlatBuffers
Cap'n Proto
Implement:
tests/test_protocol.py
tests/test_event_bus.py
Verify:
- valid envelope encoding
- invalid envelope rejection
- JSON round-trip integrity
- MessagePack round-trip integrity
- timestamp preservation
- Unicode rune preservation
- astrological glyph preservation
- concurrent event delivery
- local IPC reconnect behavior
Provide Muse with durable edge memory and a persistent causal model of active reality.
Implement:
services/yggdrasil/memory/kista_vault.py
Storage backend:
SQLite
Database:
/opt/yggdrasil/kista.db
Enable Write-Ahead Logging:
PRAGMA journal_mode=WAL;Suggested artifact classes:
code
lore
transits
state_snapshots
documents
agent_results
world_events
campaign_state
system_state
Enable SQLite FTS5 where available.
Example:
CREATE VIRTUAL TABLE artifact_fts
USING fts5(
key,
content,
category
);Search capabilities should support:
- lore retrieval
- code retrieval
- world-state notes
- previous simulations
- TTRPG history
- past divination artifacts
Implement:
services/yggdrasil/world_model/wyrd_graph.py
Represent the active world as:
where:
V = entities / states
E = causal transitions / relationships
Nodes may represent:
people
agents
objects
locations
systems
resources
environmental conditions
abstract states
Edges may represent:
causes
owns
contains
depends_on
moved_to
changed
triggered
observed
created
destroyed
Implement:
services/yggdrasil/world_model/verdandi_timeline.py
Responsibilities:
- maintain present-state snapshots
- serialize timeline frames
- differentiate manifest vs speculative state
- checkpoint verified reality
- prune orphaned speculative branches
- restore a previous anchored state
Conceptual flow:
Incoming Event
│
▼
WYRD Update
│
▼
Verdandi Validation
│
├── Manifest
│ │
│ ▼
│ Active State
│
└── Speculative
│
▼
Future Branch
Equip the edge node with bounded autonomous workers, probabilistic simulation, and local execution capability.
Implement:
services/yggdrasil/simulation/seidr_engine.py
Empirical state:
Symbolic state:
Intuition weighting:
Blended result:
Implement:
services/yggdrasil/sandbox/mythic_coder.py
Responsibilities:
- restricted working directory
- timeout enforcement
- output-size limits
- subprocess monitoring
- process-tree cleanup
- explicit executable policies
- artifact capture
- test execution
Filesystem working-directory restriction alone is not a security sandbox. Production deployments should use stronger OS-level isolation where arbitrary or semi-trusted code may execute.
Suggested production layers:
Dedicated Linux User
│
▼
Restricted Filesystem
│
▼
Command Allowlist
│
▼
Resource Limits
│
▼
Namespace / Container Isolation
Implement:
services/yggdrasil/subagents/draupnir_forge.py
Worker scaling:
Default values:
Example maximum-complexity worker tree:
Depth 0: 8 workers
Depth 1: 4 workers
Depth 2: 2 workers
Depth 3: 1 worker
Worker responsibilities:
- task decomposition
- temporary scripts
- bounded execution
- output collection
- result aggregation
- cleanup
- cancellation
- failure reporting
Expose structured tool methods such as:
kista.store
kista.retrieve
kista.search
wyrd.update_entity
wyrd.get_state
wyrd.record_transition
verdandi.checkpoint
verdandi.get_present
seidr.simulate
draupnir.spawn
draupnir.status
coder.execute
hud.set_mode
hud.emit
Create a hardware-accelerated multi-mode observation interface designed to maintain a locked target render rate of:
60 FPS
Implement:
services/himinbjorg/compositor.py
Possible rendering stack:
Pygame
SDL2
ModernGL
OpenGL
Features:
- double buffering
- event-based state updates
- persistent local state cache
- adaptive frame pacing
- font fallback
- UTF-8 rendering
- multi-view switching
Implement:
services/himinbjorg/canvas_ttrpg.py
Display:
- party cards
- HP
- maximum HP
- Armor Class
- status conditions
- encounter name
- encounter lore
- dice notation
- roll results
- difficulty checks
- advantage / disadvantage
- active combat state
Health ratio:
Clamp:
Implement:
services/himinbjorg/canvas_divination.py
Display:
- 360° celestial wheel
- Ascendant
- planets
- aspect chords
- Tarot cards
- runes
- planetary hours
- interpretation text
Aspect rules:
Implement:
services/himinbjorg/canvas_system.py
Display:
- active WYRD entities
- causal edges
- Kista operations
- active Draupnir workers
- Seidr simulations
- CPU load
- memory utilization
- neural accelerator activity
- network activity
- service health
Conceptual UI:
┌──────────────────────────────────────────────────────────────┐
│ YGGDRASIL SYSTEM MATRIX │
├───────────────────────────┬──────────────────────────────────┤
│ WYRD GRAPH │ EDGE SERVICES │
│ │ │
│ [Entity A] │ Kista ONLINE │
│ │ │ Seidr READY │
│ ▼ │ Draupnir 3 ACTIVE │
│ [Entity B] │ Hailo ACTIVE │
│ │ │ │
│ ▼ │ CPU 18% │
│ [Entity C] │ RAM 37% │
├───────────────────────────┴──────────────────────────────────┤
│ RECENT EDGE EVENTS │
└──────────────────────────────────────────────────────────────┘
Automatic switching:
ttrpg.*
-> View 1
divination.*
-> View 2
wyrd.*
kista.*
seidr.*
draupnir.*
system.*
-> View 3
Manual control:
| Key | Action |
|---|---|
TAB |
Cycle views |
1 |
Divination |
2 |
TTRPG |
3 |
Yggdrasil System |
ESC |
Exit |
Q |
Exit |
Use the Hailo accelerator for supported neural workloads while keeping the host workstation independent from edge inference.
Implement:
services/hailo/pipeline_manager.py
Responsibilities:
- initialize accelerator runtime
- load compiled models
- manage virtual streams
- serialize inference jobs
- monitor throughput
- recover failed pipelines
- report telemetry
Implement:
services/hailo/tts_worker.py
Pipeline:
Muse Text
│
▼
Narration Queue
│
▼
TTS Worker
│
▼
Supported Neural Runtime
│
▼
PCM Output
│
▼
ALSA / PipeWire
Potential speech engines:
Kokoro
Piper
other supported models
Implement:
services/hailo/embed_worker.py
Potential embedding families:
BGE
Nomic Embed
other supported compact encoders
Use cases:
- Kista semantic search
- lore retrieval
- code retrieval
- memory similarity
- world-model entity matching
Embedding vector:
Similarity:
Connect Muse's workstation to Hliðskjálf through a clean, structured host-side integration layer.
Implement:
client/harvester.py
Responsibilities:
- invoke Sagnaskemma
- invoke astrology-engine
- capture stdout
- parse JSON
- parse known text patterns
- extract party state
- extract encounter state
- extract dice rolls
- extract celestial data
- generate protocol events
- transmit events to the Pi
Flow:
Muse
│
▼
Harvester
│
├── Sagnaskemma
│
└── Astrology Engine
│
▼
Structured Event
│
▼
Hliðskjálf
Implement:
client/mcp_bridge.py
Expose tool families including:
kista.*
wyrd.*
verdandi.*
seidr.*
draupnir.*
coder.*
hud.*
system.*
sequenceDiagram
participant M as Muse
participant B as MCP Bridge
participant H as Heimdall
participant Y as Yggdrasil
participant U as Himinbjörg
M->>B: Invoke tool
B->>H: Structured request
H->>Y: Dispatch
Y->>Y: Execute operation
Y->>U: Telemetry event
Y-->>H: Result
H-->>B: JSON-RPC response
B-->>M: Tool result
Target behavior:
Muse invokes tool
↓
Pi executes tool
↓
Result returns to Muse
↓
HUD updates visually
Package Hliðskjálf as a resilient unattended edge system that starts automatically and recovers from common failures.
File:
deploy/systemd/hlidskjalf-core.service
Responsibilities:
Heimdall
Yggdrasil
RPC
MCP-facing services
Kista
WYRD
Verdandi
Seidr
Draupnir
File:
deploy/systemd/hlidskjalf-hud.service
Responsibilities:
Himinbjörg
Pygame / SDL
Display session
Input
Telemetry presentation
Implement:
- process restart on failure
- service health checks
- IPC socket reconnect
- host reconnect
- display restart
- Hailo runtime reconnect
- stale worker cleanup
- incomplete transaction recovery
- Kista integrity verification
Implement:
tests/e2e_stress_test.py
Simulate concurrent:
- dice events
- encounter updates
- Tarot spreads
- celestial transits
- Kista writes
- Kista reads
- WYRD updates
- Seidr simulations
- Draupnir workers
- speech synthesis
- HUD mode switches
Example test stream:
1000 telemetry events
+ 100 Kista writes
+ 100 WYRD updates
+ 25 Seidr simulations
+ 10 Draupnir workers
+ continuous HUD rendering
The root:
README.md
should contain:
- system summary
- architecture diagram
- hardware requirements
- dependency installation
- repository tree
- service descriptions
- setup commands
- Muse connection instructions
- verification commands
- troubleshooting
- development roadmap
| Subsystem | Process / Service | Hardware Target | Target Memory | Compute Budget |
|---|---|---|---|---|
| Heimdall + Core Services | hlidskjalf-core |
Pi CPU | ~250 MB | Lightweight network / RPC workload |
| WYRD + Kista | Python + SQLite WAL | Pi CPU | ~1.5 GB target ceiling | Mostly event-driven |
| Mythic Coder / Draupnir | Worker subprocesses | Pi CPU | Dynamic, bounded | Scaled per task |
| Himinbjörg HUD | Pygame / SDL / GPU | Pi CPU + VideoCore | ~400-500 MB target | Locked 60 FPS goal |
| Neural Speech | Accelerator runtime | Hailo | Model-dependent | Offloaded inference |
| Vector Embeddings | Accelerator runtime | Hailo | Model-dependent | Offloaded inference |
| Linux + Cache Headroom | Kernel / buffers / services | Pi system memory | Remaining memory | Maintain thermal + memory margin |
Resource values are engineering targets, not guarantees. Actual memory and CPU utilization should be measured on the final hardware and software stack.
┌─────────────────────────────────────────────────────────────┐
│ RASPBERRY PI 5 CPU │
├─────────────────────────────────────────────────────────────┤
│ Core 0 │
│ Heimdall / Networking / RPC │
├─────────────────────────────────────────────────────────────┤
│ Core 1 │
│ WYRD / Verdandi / Kista │
├─────────────────────────────────────────────────────────────┤
│ Core 2 │
│ Draupnir / Mythic Coder │
├─────────────────────────────────────────────────────────────┤
│ Core 3 │
│ Himinbjörg / UI │
└─────────────────────────────────────────────────────────────┘
This is a logical workload partition.
Linux scheduling may dynamically move processes between cores unless explicit CPU affinity is configured.
flowchart TB
CONFIG["Configuration"]
PROTOCOL["Protocol / Schemas"]
CORE["Hliðskjálf Core"]
HEIMDALL["Heimdall Gateway"]
KISTA["Kista"]
WYRD["WYRD"]
VERDANDI["Verdandi"]
SEIDR["Seidr"]
DRAUPNIR["Draupnir"]
CODER["Mythic Coder"]
HAILO["Hailo Services"]
HUD["Himinbjörg"]
CLIENT["Muse Client"]
CONFIG --> CORE
PROTOCOL --> CORE
CORE --> HEIMDALL
HEIMDALL --> KISTA
HEIMDALL --> WYRD
HEIMDALL --> SEIDR
HEIMDALL --> DRAUPNIR
HEIMDALL --> CODER
WYRD <--> VERDANDI
KISTA --> SEIDR
WYRD --> SEIDR
DRAUPNIR --> CODER
CORE --> HAILO
KISTA --> HUD
WYRD --> HUD
VERDANDI --> HUD
SEIDR --> HUD
DRAUPNIR --> HUD
HAILO --> HUD
CLIENT --> HEIMDALL
Himinbjörg should observe Yggdrasil but not become a hard dependency required for Yggdrasil to operate.
Correct:
Yggdrasil
│
├── operates independently
│
└── emits telemetry
│
▼
Himinbjörg
Incorrect:
Yggdrasil
│
▼
Himinbjörg
│
▼
Yggdrasil cannot continue
if HUD is offline
The HUD must be optional from the perspective of core cognition.
Use:
protocol/
as the stable shared contract.
Avoid direct cross-imports such as:
from services.himinbjorg.compositor import some_yggdrasil_functionor:
from services.yggdrasil.daemon import some_hud_functionPrefer:
event bus
RPC
shared schemas
service interfaces
Avoid:
PI_HOST = "192.168.1.150"Prefer:
network:
host: 0.0.0.0
rpc_port: 8000
hud_port: 8080
websocket_port: 8765If Hailo is unavailable:
Core services continue
HUD continues
Kista continues
WYRD continues
Muse connectivity continues
If Himinbjörg is unavailable:
Yggdrasil continues
If Muse disconnects:
Local state remains available
Kista remains available
HUD can show OFFLINE state
Every major subsystem should emit telemetry.
Example:
{
"event_type": "kista.artifact.stored",
"payload": {
"key": "barrow_state",
"category": "state_snapshot"
}
}Example:
{
"event_type": "draupnir.worker.started",
"payload": {
"task": "Analyze test failure",
"depth": 1
}
}Draupnir must enforce:
and a bounded worker population.
Apply limits to:
- logs
- HUD text
- event history
- subprocess output
- worker results
- timeline snapshots
- telemetry queues
Project Hliðskjálf reaches its first complete integrated milestone when all of the following succeed.
- Monorepo builds cleanly.
- Shared configuration loads.
- JSON protocol validates.
- MessagePack protocol validates.
- Local IPC works.
- Kista persists across reboot.
- FTS search works.
- WYRD entity updates work.
- WYRD transitions work.
- Verdandi snapshots work.
- Seidr simulation works.
- Draupnir bounded workers work.
- Mythic Coder execution works.
- Failed workers clean up correctly.
- TTRPG view works.
- Divination view works.
- System view works.
- Automatic switching works.
- Manual switching works.
- Unicode glyphs render correctly.
- Target frame rate is stable on final hardware.
- Accelerator runtime initializes.
- Supported embedding model executes.
- Supported speech model executes.
- Failover behavior works.
- Harvester captures Sagnaskemma output.
- Harvester captures astrology output.
- Muse discovers edge tools.
- Muse invokes edge tools.
- Results return successfully.
- HUD updates from Muse actions.
- Core service starts at boot.
- HUD starts at boot.
- Services restart after failure.
- Stress test completes.
- Documentation reproduces installation from a clean system.
flowchart TB
MUSE["META MUSE<br/>Primary Intelligence"]
CLIENT["HOST INTEGRATION<br/>Harvester / MCP Bridge"]
GATE["HEIMDALL<br/>Gateway"]
subgraph CORE["PROJECT HLIÐSKJÁLF"]
subgraph YGG["YGGDRASIL"]
KISTA["Kista<br/>Memory"]
WYRD["WYRD<br/>Causality"]
VERDANDI["Verdandi<br/>Present State"]
SEIDR["Seidr<br/>Simulation"]
DRAUPNIR["Draupnir<br/>Workers"]
CODER["Mythic Coder<br/>Execution"]
end
HAILO["NEURAL ACCELERATION"]
HIM["HIMINBJÖRG<br/>Omni-HUD"]
end
MUSE --> CLIENT
CLIENT --> GATE
GATE --> KISTA
GATE --> WYRD
GATE --> SEIDR
GATE --> DRAUPNIR
GATE --> CODER
WYRD <--> VERDANDI
KISTA --> SEIDR
WYRD --> SEIDR
DRAUPNIR --> CODER
KISTA --> HAILO
CODER --> HAILO
KISTA --> HIM
WYRD --> HIM
VERDANDI --> HIM
SEIDR --> HIM
DRAUPNIR --> HIM
CODER --> HIM
HAILO --> HIM
classDef muse fill:#21143d,stroke:#a78bfa,stroke-width:2px,color:#ffffff;
classDef gate fill:#172554,stroke:#60a5fa,stroke-width:2px,color:#ffffff;
classDef ygg fill:#132e2a,stroke:#34d399,stroke-width:2px,color:#ffffff;
classDef neural fill:#3b1d0b,stroke:#fb923c,stroke-width:2px,color:#ffffff;
classDef hud fill:#301934,stroke:#e879f9,stroke-width:2px,color:#ffffff;
class MUSE,CLIENT muse;
class GATE gate;
class KISTA,WYRD,VERDANDI,SEIDR,DRAUPNIR,CODER ygg;
class HAILO neural;
class HIM hud;
The architecture can be understood as four mythic layers.
The Gate
authentication
validation
routing
protection
The Living Cognitive Infrastructure
memory
causality
state
simulation
workers
execution
The Observation Hall
visualization
telemetry
status
interaction
physical presence
The Unified High Seat
perception
cognition
memory
action
observation
Together:
MUSE
│
▼
HEIMDALL
│
▼
YGGDRASIL
┌───────┼───────┐
▼ ▼ ▼
Memory Agents Tools
│ │ │
└───────┼───────┘
▼
HIMINBJÖRG
│
▼
HLIÐSKJÁLF
Unified Edge Intelligence
Project Hliðskjálf is the point where Muse's perception, memory, world modeling, autonomous execution, neural edge services, and physical telemetry converge into one coherent edge runtime.