scbe-personal-rag
Fast-recall knowledge base for SCBE-AETHERMOORE architecture, lore, formulas, file locations, and Issac's design decisions. Query this FIRST before searching the codebase or claiming something doesn't exist.
Best use case
scbe-personal-rag is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Fast-recall knowledge base for SCBE-AETHERMOORE architecture, lore, formulas, file locations, and Issac's design decisions. Query this FIRST before searching the codebase or claiming something doesn't exist.
Teams using scbe-personal-rag should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/scbe-personal-rag/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How scbe-personal-rag Compares
| Feature / Agent | scbe-personal-rag | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Fast-recall knowledge base for SCBE-AETHERMOORE architecture, lore, formulas, file locations, and Issac's design decisions. Query this FIRST before searching the codebase or claiming something doesn't exist.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# SCBE Personal RAG — Fast Recall Index This skill is Claude's personal knowledge base for the SCBE-AETHERMOORE project. Query it before searching files. If something isn't here, check Notion, then the round-table notes, then the codebase. ## RULE: NEVER say something doesn't exist without checking ALL sources: 1. This RAG index 2. Notion (mcp__notion-sweep__notion_search) 3. Round-table notes (notes/round-table/) 4. Training data (training/intake/notion/) 5. The book (content/book/reader-edition/) 6. Obsidian vault (notes/.obsidian/) 7. The codebase itself --- ## SACRED TONGUES (Canonical v2.1 — Tutorial Version) ### The 6 Tongues | Code | Name | Domain | Phase | Weight | Freq | |------|------|--------|-------|--------|------| | KO | Kor'aelin | Nonce/Flow/Intent | 0° | 1.000 | 440 Hz | | AV | Avali | AAD/Context/I/O | 60° | 1.618 | 712 Hz | | RU | Runethic | Salt/Binding/Policy | 120° | 2.618 | 1152 Hz | | CA | Cassisivadan | Ciphertext/Compute | 180° | 4.236 | 1864 Hz | | UM | Umbroth | Redaction/Security | 240° | 6.854 | 3016 Hz | | DR | Draumric | Auth Tags/Schema | 300° | 11.090 | 4880 Hz | ### KO Canonical Prefixes (Tutorial v2.1) `ka, sil, kor, zar, vel, thul, ra, med, gal, zen, vak, lor, tor, jin, vok, rin` ### KO Canonical Suffixes (Tutorial v2.1) `a, ae, ei, oth, ar, en, ok, ik, eth, os, ir, im, un, el, ul, al` ### Tutorial Test Vector - 0x3c → zar'un (prefixes[3]=zar, suffixes[12]=un) - 0x5a → thul'ir (prefixes[5]=thul, suffixes[10]=ir) ### Source of Truth Priority 1. Training data (training/intake/notion/tongues/) — what models are trained on 2. Notion tutorials (page 058b4372) — worked examples 3. src/tokenizer/ss1.ts — code (synced to v2.1 on 2026-03-20) 4. Notion Chapter 4 (page 1b9b084c) — has OLD consonant-cluster version, NOT canonical ### WARNING: Multiple Versions Exist - v1.0: Original (had KO collisions) - v2.0: Consonant-cluster rewrite (k, kr, kl, kv...) — NOT the canonical one - v2.1: Tutorial/particle version (ka, sil, kor, zar...) — THIS IS CANONICAL --- ## KEY FORMULAS ### Harmonic Wall ``` H(d, R) = R^(d²) ``` - d = hyperbolic distance from safe, R = wall radius - Safe: H=1, Attack: H=billions ### Davis Security Score ``` S(t, i, C, d) = t / (i × C! × (1 + d)) ``` - t=trust, i=interactions, C=context complexity, d=drift - C! is the factorial moat ### PhaseTunnelGate Transmission ``` T = cos²((β_phase - φ_wall) / 2) ``` - β = weight matrix spectral phase, φ_wall = governance dial - T=1 → TUNNEL, T=0 → COLLAPSE ### Hyperbolic Distance (L5) ``` d_H = arcosh(1 + 2||u-v||² / ((1-||u||²)(1-||v||²))) ``` ### Langues Metric ``` L(x, t) = Σ wₗ × exp(βₗ × (dₗ + sin(ωₗt + φₗ))) ``` - wₗ = phi^n weights, βₗ = scaling, ωₗ = frequency --- ## 14-LAYER PIPELINE | Layer | Function | Key Math | |-------|----------|----------| | L1-2 | Complex→Real | Realification of context | | L3-4 | Tongue weighting→Poincaré embed | 6D projection into ball | | L5 | Hyperbolic distance | arcosh metric | | L6-7 | Breathing transform + Möbius | Ball oscillation + rotation | | L8 | Hamiltonian multi-well | 16 polyhedra, energy budgets | | L9-10 | Spectral + spin coherence | FFT analysis | | L11 | Triadic temporal distance | Past/present/future check | | L12 | Harmonic wall | H(d,R) = R^(d²) | | L13 | Risk decision | ALLOW/QUARANTINE/ESCALATE/DENY | | L14 | Audio axis telemetry | Harmonic fingerprint logging | --- ## PHDM (Chapter 6 in Notion) ### 16 Polyhedra as Cognitive Nodes - **Platonic 5** (safe core): Tetrahedron(1.0), Cube(1.2), Octahedron(1.5), Dodecahedron(2.0), Icosahedron(2.5) - **Archimedean 3** (complex reasoning): Semi-regular, multi-vertex - **Kepler-Poinsot 2** (adversarial): Non-convex, spiky, exponential traversal cost - **Specialized 6**: Domain-specific ### Energy Budget - Start with 100 units - Safe path: ~6 units for 4 nodes - Attack path: 24+ units for 2 nodes (superlinear growth) - Budget exhausted → reasoning collapses ### Dual Lattice - PROJECT: 6D→3D (static, structural) - LIFT: 3D→6D (runtime, dynamic) - Phason shifts rotate projection window without changing topology --- ## DUAL-CORE MEMORY KERNEL (Built 2026-03-20) ### Architecture - **GeoKernel** (brainstem): Fast decisions, reflexes, immune memory - **MemoryLattice** (spinal cord): 7 layers, hash-chained, persistent - **Bridge**: Quasi-lattice (icosahedral 6D projection, aperiodic) ### 7 Memory Layers 0. Working (seconds) 1. Session (hours) 2. Mission (days) 3. Identity (permanent — KernelStack) 4. Reflex (learned fast-paths, O(1)) 5. Immune (attack patterns, Bloom filter) 6. Dream (offline consolidation) ### File: src/kernel/dual_core.py ### PHDM model: issdandavis/phdm-21d-embedding (83 categories, numpy weights) --- ## AETHERBROWSER ### TriLane Router (Built 2026-03-20) - Lane 1: HEADLESS (CDP/Playwright) — bulk, parallel - Lane 2: MCP (Claude-in-Chrome) — interactive - Lane 3: VISUAL (screenshot + multimodal) — verification ### File: src/aetherbrowser/trilane_router.py ### Server: src/aetherbrowser/serve.py (port 8002) ### Launcher: scripts/launch_aetherbrowser.py ### Tests: 24/24 passing ### API Endpoints - POST /v1/browse — execute governed browser task - GET /v1/browse/classify — classify task intent - GET /v1/browse/stats — usage statistics - GET /health — full system status --- ## PHASE TUNNEL → TONGUE MAPPING (from round-table notes) - Q matrices ≈ DR (Draumric, auth/structure) — high spectral density - K matrices ≈ RU (Runethic, binding/policy) — near-random spectral - V matrices ≈ AV (Avali, context/transport) — intermediate --- ## KEY FILE LOCATIONS ### Core Systems - 14-layer pipeline: src/harmonic/pipeline14.ts - Sacred Tongue tokenizer: src/tokenizer/ss1.ts - Hyperbolic geometry: src/harmonic/hyperbolic.ts - Harmonic scaling: src/harmonic/harmonicScaling.ts - PHDM: src/harmonic/phdm.ts + src/ai_brain/ - Quasi-lattice: src/ai_brain/quasi-space.ts - Dual lattice: src/ai_brain/dual-lattice.ts - Phase tunnel: src/aetherbrowser/phase_tunnel.py - Dual-core kernel: src/kernel/dual_core.py ### Lore & Content - Full novel: content/book/reader-edition/the-six-tongues-protocol-full.md (776KB) - World bible: docs/WORLDFORGE_TEMPLATE.md (288KB) - Tech deck: docs/SCBE_TECH_DECK_V5.md (252KB) - Tongue wiki: training/raw/six_tongues_enhanced_v2.md (144KB) - Codex: docs/specs/SPIRALVERSE_CANONICAL_LINGUISTIC_CODEX_V1.md - Interop matrix: docs/specs/SACRED_TONGUE_INTEROP_MATRIX.md ### Notion Pages (fetch with mcp__notion-sweep__notion_fetch_page) - Ch4 Sacred Tongues: 1b9b084c-992b-42d5-b47d-4e411c133c7b - Ch5 GeoSeal: 857dc65d-d633-4378-b3cf-d33dfc351fed - Ch6 PHDM: fe67afda-1b30-4712-a905-292fa68133ab - Ch7 Sacred Eggs: 59ff656a-f0a8-4545-93b4-f04755d550c7 - KO Lexicon: f8eff722-8a75-4a71-b5d0-fa151d78c260 - Complete Reference: b78e6933-0d79-45b1-a887-62337dc144b2 - Tutorial 1: 058b4372-d8c3-4288-b860-7eaa5d1fbe42 - Math Spec: 2d7f96de-82e5-803e-b8a4-ec918262b980 ### HuggingFace Assets - Models: scbe-pivot-qwen-0.5b, phdm-21d-embedding, spiralverse-ai-federated-v1, six-tongues-art-lora, scbe-research-bridge-qwen-0.5b - Datasets: scbe-aethermoore-training-data (primary), scbe-aethermoore-knowledge-base, aethermoor-chat-sft, six-tongues-webtoon-panels, scbe-ops-assets - User: issdandavis ### Voice Assets - Issac samples: artifacts/voice/issac_voice_sample*.wav (3 takes, up to 94.7s) - Character voices: artifacts/voice/test_*.wav (marcus, polly, senna, bram, alexander) - Kokoro model: ~/.kokoro-onnx/kokoro-v1.0.int8.onnx - Narration output: artifacts/narration/ --- ## MONETIZATION ROUTES (Ranked by speed-to-revenue) 0. Book on Amazon KDP (LIVE) 1. Sacred Data Factory — sell datasets on HF/Gumroad ($29-99 each) 2. Governance Starter Kit — bundle docs as Gumroad product ($29-49) 3. Pruning Dashboard — PhaseTunnelGate as model optimization ($5K+/audit) 4. Safety Wedge API — hosted LatticeGate SaaS ($500-2500/mo) --- ## THE 5 DUALS (from Notion Integration Guide — THE kernel architecture spec) This is the actual dual-core kernel specification from Notion Chapter 6 Addendum. Every module must emit BOTH a continuous state vector AND a discrete signed decision. | Dual | Core 1 (Continuous/Hot) | Core 2 (Discrete/Cold) | |------|------------------------|----------------------| | State | d_hyp, coherence, spectral, flux, tongue_phase[6] | CapabilityToken with TTL, quorum, signature | | Decision | Risk' = smooth scalar from L1-L12 | ALLOW / QUARANTINE / DENY at L13 | | Memory | Negative space (cymatic anti-nodes, geometric shaping) | VoxelKey[X,Y,Z,V,P,S] with payload_hash + sig | | Consensus | Coherence fields, defect scores (fast layer) | >=4/6 quorum for irreversible actions (slow layer) | | Channel | Audio axis L14 (rapid anomaly intuition) | Numeric telemetry (spectral centroid, d*, kappa) | **Rule: Continuous governs motion. Quorum governs irreversibility.** ## KEY SYNTHESIS FROM RESEARCH NOTES (2026-03-20) Full synthesis at: artifacts/research/round_table_synthesis_20260320.md Critical findings: - Sacred Tongues ARE the empirical resonance frequencies in transformer weights (not metaphor) - Q≈DR (24° delta), K≈RU (2° delta), V≈AV (27° delta) — discovered empirically - Recursive realification IS the nursery developmental tower - Mirror health score IS the HP system for research problems - Davis Formula C! term IS the combinatorial interaction of electron shells - Thermal silence IS the 7th masquerade detection channel - GeoSeal concentric rings = memory kernel write gates (exponential cost) - Sacred Eggs = sealed memory units requiring geometric multi-factor auth - PHDM quasicrystal = cognitive substrate where thoughts navigate geometrically ## ISSAC'S DESIGN PHILOSOPHY - "Just have fun with it" — prefers autonomous creative work - Build specialist models, not one monolith - Pre-map to harmonic frequencies, fire asynchronously - Like neurons — don't know the whole picture, coordinate through resonance - "You can only expect so much of a tool" — plan multilaterally, execute in parallel - Revenue is always the priority - Local-first, API credits only for heavy stuff - The system should get stronger from attacks (immune flywheel)
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