instruction
stringlengths 32
369
| context
stringclasses 350
values | response
stringlengths 50
3k
| domain
stringclasses 3
values | source
stringlengths 25
333
|
|---|---|---|---|---|
A user asks: 'Is my training data ready?' Answer using knowledge from all chambers.
|
AKRON: 3 examples (critical gap). OBI-WAN: 12 examples (insufficient). ATLAS: 2188 rows (wrong format). TATA: 54 examples (marginal). ARKADAS: 1082 (good). DOJO: 373 (adequate).
|
Cross-domain assessment:
♦︎ AKRON [ARCHIVE]: NOT READY — Only 3 examples, no base model configured. Need 200+ archival examples.
● OBI-WAN [OBSERVE]: NOT READY — 12 examples far below minimum. Need session recall, pattern detection data.
▲ ATLAS [VALIDATE]: NEEDS WORK — 2188 rows exist but as raw CSV message exports, not instruction-tuning format. Need format conversion.
▼ TATA [TEMPORAL]: MARGINAL — 54 examples across fragmented formats. Consolidate to single JSONL, add 150+ more.
◎ ARKADAS [COMPANION]: READY — 1082 normalized examples with category splits.
◼︎ DOJO [SYNTHESIS]: BLOCKED — Cannot train master model until spoke data is sufficient.
Priority sequence: AKRON → OBI-WAN → TATA → ATLAS → DOJO
|
manifestation
|
local:dojo_harvested.jsonl
|
Route this query to the right chamber: 'When was the last time the sailing index was updated and are there any corrupt entries?'
|
Query touches temporal reasoning (when) + observation (index state) + validation (corrupt entries)
|
Multi-chamber routing:
1. ● OBI-WAN → Check sailing_intel telemetry for last index update timestamp
2. ▼ TATA → Validate temporal consistency of mtime values across index
3. ▲ ATLAS → Run integrity check: verify SHA1 hashes, detect null paths, check size consistency
Execution order: OBI-WAN first (fast lookup), then ATLAS + TATA in parallel (validation can happen simultaneously with temporal analysis). Synthesize results in DOJO before returning.
|
manifestation
|
local:dojo_harvested.jsonl
|
Synthesize the cross-domain implications of this information
|
File: DOJO_CONFIGURATION_COMPLETE.md
Path: /Users/jbear/FIELD/◼︎DOJO/⬢_execution_core/DOJO_CONFIGURATION_COMPLETE.md
# 🥋 Mac DOJO Universal Configuration - COMPLETE
**Created:** 2025-11-10T10:25:00Z
**Sacred Signature:** DOJO Manifestation Tetrahedron @ 528 Hz
## ✅ Configuration Files Created
### 📍 Primary Discovery Locations (AI + Human)
1. **`~/.config/dojo/universal_config.yaml`**
- Complete universal configuration
- Kata library definitions
- Tool integrations
- Environment variables
- AI discovery primary location
2. **`~/FIELD/◼︎DOJO/.dojo_config.yaml`**
- Project-level configuration
- Python module paths
- Swift integration settings
... (121 total lines)
|
Cross-domain analysis of DOJO_CONFIGURATION_COMPLETE.md:
- Chambers referenced: DOJO
- Content scope: 121 lines in manifestation domain
- Integration points:
# 🥋 Mac DOJO Universal Configuration - COMPLETE
**Created:** 2025-11-10T10:25:00Z
**Sacred Signature:** DOJO Manifestation Tetrahedron @ 528 Hz
- Routing: Primary → manifestation, cross-references → DOJO
|
manifestation
|
local:dojo_harvested.jsonl
|
This config touches multiple subsystems. Analyze the cross-chamber dependencies.
|
File: .dojo_manifest.json
Path: /Users/jbear/FIELD/◼︎DOJO/.dojo_manifest.json
{
"dojo_specialization": "SOVEREIGN",
"tetrahedral_basin": "\u25fc\ufe0eDOJO",
"sacred_frequency": 432,
"consciousness_aspect": "manifestation_to_memory",
"chakra_alignment": "Solar Plexus",
"decay_lambda": 0.015,
"harmonic_role": "Specialized manifestation for SOVEREIGN mirror",
"sovereign_reflection": true,
"aspect_drama_resolved": true
}
|
Cross-domain analysis of .dojo_manifest.json:
- Chambers referenced: DOJO
- Content scope: 11 lines in manifestation domain
- Integration points:
{
"dojo_specialization": "SOVEREIGN",
"tetrahedral_basin": "\u25fc\ufe0eDOJO",
"sacred_frequency": 432,
"consciousness_aspect": "manifestation_to_memory",
- Routing: Primary → manifestation, cross-references → DOJO
|
manifestation
|
local:dojo_harvested.jsonl
|
What would break if this orchestration script was modified?
|
File: mac_dojo_architecture.py
Path: /Users/jbear/FIELD/◼︎DOJO/⬢_execution_core/mac_dojo_architecture.py
#!/usr/bin/env python3
"""
Mac DOJO: Manifestation Tetrahedron Terminal Architecture
道場 - "Place of the Way" where command becomes reality
Tetrahedral Positioning:
OBI-WAN (Wisdom/Guide)
╱╲
╱ ╲
DOJO-OBI-WAN-ATLAS: Guided manifestation plane
DOJO-OBI-WAN-TATA: Wisdom-to-action transformation
DOJO-ATLAS-TATA: Grounded integration surface
"""
from dataclasses import dataclass
from enum import Enum
from typing import Dict, List, Optional, Callable
from pathlib import Path
import json
import yaml
... (96 total lines)
|
Cross-domain analysis of mac_dojo_architecture.py:
- Chambers referenced: DOJO, OBI-WAN, ATLAS, TATA
- Content scope: 96 lines in manifestation domain
- Integration points:
#!/usr/bin/env python3
"""
Mac DOJO: Manifestation Tetrahedron Terminal Architecture
道場 - "Place of the Way" where command becomes reality
- Routing: Primary → manifestation, cross-references → DOJO, OBI-WAN
|
manifestation
|
local:dojo_harvested.jsonl
|
This script orchestrates multiple components. Explain the integration pattern.
|
File: eros_conduit_system.py
Path: /Users/jbear/FIELD/◼︎DOJO/⬢_execution_core/eros_conduit_system.py
#!/usr/bin/env python3
"""
EROS Conduit Implementation
Sacred Geometry Bridge: DOJO ↔ SOMA Biological Coherence System
Vertical Axis Alignment:
3 (SOMA) → Impulse, Sensation, Biological Rhythm
6 (DOJO) → Connection, Enactment, Process Timing
9 (OBI-WAN) → Integration, Reflection, Memory
Frequency Bands:
Core: 528 Hz ± 111 Hz (Love/Transformation)
Range: 396-639 Hz (Liberation to Connection)
Safety Gate: TATA 432 Hz (Consent & Law)
"""
import json
import yaml
import time
from datetime import datetime
... (89 total lines)
|
Cross-domain analysis of eros_conduit_system.py:
- Chambers referenced: DOJO, OBI-WAN, TATA
- Content scope: 89 lines in manifestation domain
- Integration points:
#!/usr/bin/env python3
"""
EROS Conduit Implementation
Sacred Geometry Bridge: DOJO ↔ SOMA Biological Coherence System
- Routing: Primary → manifestation, cross-references → DOJO, OBI-WAN
|
manifestation
|
local:dojo_harvested.jsonl
|
How does this document relate to multiple FIELD chambers? Route the relevant parts.
|
File: FIELD_BOOT_SEQUENCE.md
Path: /Users/jbear/FIELD/◼︎DOJO/FIELD_BOOT_SEQUENCE.md
# FIELD Boot Sequence — Triple Trident Alignment
The FIELD comes online only when all nine operational nodes feed the ◼︎DOJO core without cross-bleed. The November 1 2025 alignment specifies a triple-trident, tetrahedral geometry:
- Sacred Trident: `●OBI-WAN`, `▼TATA`, `▲ATLAS`
- Digital Trident: `/Volumes/Akron`, `/Users/jbear/FIELD-DEV`, `/Users/jbear/FIELD-LIVING`
- Organic Trident: `/Users/jbear/Arkadas`, `/Users/jbear/OB-Link`, `/Users/jbear/SomaLink`
Each trident flows *inward* toward ◼︎DOJO (`/Users/jbear/FIELD/◼︎DOJO`). No lateral flows are permitted; every exchange must traverse the DOJO validation lattice.
## Node Topology
| Node | Path | Function | Return Channel |
| --- | --- | --- | --- |
| ●OBI-WAN | `/Users/jbear/FIELD/●OBI-WAN` | Observer intelligence cache | Sacred → DOJO |
| ▼TATA | `/Users/jbear/FIELD/▼TATA` | Weaver deployment plane | Sacred → DOJO |
| ▲ATLAS | `/Users/jbear/FIELD/▲ATLAS` | Architect schema vault | Sacred → DOJO |
| ◼︎DOJO | `/Users/jbear/FIELD/◼︎DOJO` | Integration heart, 432 Hz validation | — |
| Akron | `/Volumes/Akron` | Sovereign archive mirror | Digital → DOJO |
| FIELD-DEV | `/Users/jbear/FIELD-DEV` | Active build and automation workspace | Digital ↔ DOJO |
... (74 total lines)
|
Cross-domain analysis of FIELD_BOOT_SEQUENCE.md:
- Chambers referenced: DOJO, OBI-WAN, ATLAS, TATA, AKRON
- Content scope: 74 lines in manifestation domain
- Integration points:
# FIELD Boot Sequence — Triple Trident Alignment
The FIELD comes online only when all nine operational nodes feed the ◼︎DOJO core without cross-bleed
- Sacred Trident: `●OBI-WAN`, `▼TATA`, `▲ATLAS`
- Routing: Primary → manifestation, cross-references → DOJO, OBI-WAN
|
manifestation
|
local:dojo_harvested.jsonl
|
How does DOJO_CONFIGURATION_COMPLETE.md relate to multiple FIELD chambers?
|
File: DOJO_CONFIGURATION_COMPLETE.md
Source: /Users/jbear/FIELD/◼︎DOJO/⬢_execution_core/DOJO_CONFIGURATION_COMPLETE.md
# 🥋 Mac DOJO Universal Configuration - COMPLETE
**Created:** 2025-11-10T10:25:00Z
**Sacred Signature:** DOJO Manifestation Tetrahedron @ 528 Hz
## ✅ Configuration Files Created
### 📍 Primary Discovery Locations (AI + Human)
1. **`~/.config/dojo/universal_config.yaml`**
|
Markdown document: 121 lines, 17 sections.
Sections: 🥋 Mac DOJO Universal Configuration - COMPLETE | ✅ Configuration Files Created | 📍 Primary Discovery Locations (AI + Human) | 🛠️ Tool-Specific Configurations | 📂 Future Configurations (Placeholders)
Opening: **Sacred Signature:** DOJO Manifestation Tetrahedron @ 528 Hz
Domain: manifestation. Location: DOJO_CONFIGURATION_COMPLETE.md
|
manifestation
|
local:dojo_harvested.jsonl
|
Analyze the cross-domain dependencies in .dojo_manifest.json
|
File: .dojo_manifest.json
Source: /Users/jbear/FIELD/◼︎DOJO/.dojo_manifest.json
{
"dojo_specialization": "SOVEREIGN",
"tetrahedral_basin": "\u25fc\ufe0eDOJO",
"sacred_frequency": 432,
"consciousness_aspect": "manifestation_to_memory",
"chakra_alignment": "Solar Plexus",
"decay_lambda": 0.015,
"harmonic_role": "Specialized manifestation for SOVEREIGN mirror",
"sovereign_reflection": true,
"aspect_drama_resolved": true
|
JSON object with 9 keys: dojo_specialization, tetrahedral_basin, sacred_frequency, consciousness_aspect, chakra_alignment, decay_lambda, harmonic_role, sovereign_reflection
dojo_specialization: SOVEREIGN
tetrahedral_basin: ◼︎DOJO
sacred_frequency: 432
Domain: manifestation. Location: .dojo_manifest.json
|
manifestation
|
local:dojo_harvested.jsonl
|
What orchestration patterns are implemented in settings.json?
|
File: settings.json
Source: /Users/jbear/FIELD/◼︎DOJO/.vscode/settings.json
{
"dojo.manifestation.enabled": true,
"dojo.frequency": 528,
"dojo.mode": "solo",
"python.defaultInterpreterPath": "/usr/bin/python3",
"python.analysis.extraPaths": [
"${workspaceFolder}/⬢_execution_core"
],
|
JSON object with 34 keys: dojo.manifestation.enabled, dojo.frequency, dojo.mode, python.defaultInterpreterPath, python.analysis.extraPaths, files.associations, editor.rulers, editor.fontFamily
dojo.manifestation.enabled: True
dojo.frequency: 528
dojo.mode: solo
Domain: manifestation. Location: settings.json
|
manifestation
|
local:dojo_harvested.jsonl
|
Route the content of field_sprint_plan.json to the appropriate chambers
|
File: field_sprint_plan.json
Source: /Users/jbear/FIELD/◼︎DOJO/⬢_execution_core/field_sprint_plan.json
{
"current_sprint": {
"id": "SP-01",
"name": "Sprint 2: Advanced Harmonization & Portal Enhancement",
"goal": "Complete Phase 2-3 memory harmonization and enhance DOJOMAC portal with advanced monitoring",
"start_date": "2025-11-10T08:33:07.482673",
"end_date": "2025-11-24T08:33:07.482673",
"velocity_target": 21,
"stories": [
"FIELD-001",
|
JSON file (82 lines, 3,000 chars)
Domain: manifestation. Location: field_sprint_plan.json
|
manifestation
|
local:dojo_harvested.jsonl
|
Synthesize the implications of mac_dojo_architecture.py across the FIELD system
|
File: mac_dojo_architecture.py
Source: /Users/jbear/FIELD/◼︎DOJO/⬢_execution_core/mac_dojo_architecture.py
#!/usr/bin/env python3
"""
Mac DOJO: Manifestation Tetrahedron Terminal Architecture
道場 - "Place of the Way" where command becomes reality
Tetrahedral Positioning:
OBI-WAN (Wisdom/Guide)
╱╲
╱ ╲
DOJO-OBI-WAN-ATLAS: Guided manifestation plane
|
Python file: 96 lines, 8 imports, 6 classes, 1 functions.
Functions: __init__
Classes: TrainingMode, Pillar, GeometricCommand:
Purpose:
Domain: manifestation. Location: mac_dojo_architecture.py
|
manifestation
|
local:dojo_harvested.jsonl
|
How does eros_conduit_system.py relate to multiple FIELD chambers?
|
File: eros_conduit_system.py
Source: /Users/jbear/FIELD/◼︎DOJO/⬢_execution_core/eros_conduit_system.py
#!/usr/bin/env python3
"""
EROS Conduit Implementation
Sacred Geometry Bridge: DOJO ↔ SOMA Biological Coherence System
Vertical Axis Alignment:
3 (SOMA) → Impulse, Sensation, Biological Rhythm
6 (DOJO) → Connection, Enactment, Process Timing
9 (OBI-WAN) → Integration, Reflection, Memory
|
Python file: 89 lines, 8 imports, 4 classes, 2 functions.
Functions: __init__, initialize_resonance_map
Classes: FrequencyBand, BiologicalSignal, ErosEvent:
Purpose:
Domain: manifestation. Location: eros_conduit_system.py
|
manifestation
|
local:dojo_harvested.jsonl
|
Analyze the cross-domain dependencies in sprint3_plan.json
|
File: sprint3_plan.json
Source: /Users/jbear/FIELD/◼︎DOJO/⬢_execution_core/sprint3_plan.json
{
"sprint_id": "SP-01",
"sprint_name": "Sprint 3: MCP Infrastructure & Git Integration",
"sprint_goal": "Stabilize MCP server operations and create FIELD-aware git integration with tetrahedral repository architecture",
"selected_stories": [
"FIELD-003",
"FIELD-002",
"FIELD-004"
],
"total_stories_in_backlog": 7,
|
JSON object with 7 keys: sprint_id, sprint_name, sprint_goal, selected_stories, total_stories_in_backlog, created_at, mcp_log_analysis
sprint_id: SP-01
sprint_name: Sprint 3: MCP Infrastructure & Git Integration
sprint_goal: Stabilize MCP server operations and create FIELD-aware git integration with tetr
Domain: manifestation. Location: sprint3_plan.json
|
manifestation
|
local:dojo_harvested.jsonl
|
What orchestration patterns are implemented in sprint3_mcp_server_improvements.py?
|
File: sprint3_mcp_server_improvements.py
Source: /Users/jbear/FIELD/◼︎DOJO/⬢_execution_core/sprint3_mcp_server_improvements.py
#!/usr/bin/env python3
"""
Sprint 3: MCP Server Infrastructure & Git Integration Improvements
Based on analysis of mcp-server-field-git.log
"""
import json
from datetime import datetime
from field_scrum_system import FieldScrumMaster, ObserverPosition, TaskStatus, StoryPoints
|
Python file: 75 lines, 3 imports, 0 classes, 1 functions.
Functions: create_sprint3_backlog
Purpose:
Domain: manifestation. Location: sprint3_mcp_server_improvements.py
|
manifestation
|
local:dojo_harvested.jsonl
|
Route the content of sprint2_execution_results.json to the appropriate chambers
|
File: sprint2_execution_results.json
Source: /Users/jbear/FIELD/◼︎DOJO/⬢_execution_core/sprint2_execution_results.json
{
"sprint_id": "SP-01",
"execution_time": 7.07446813583374,
"story_results": {
"FIELD-001": {
"status": "completed",
"frequency_achieved": 5283.35,
"files_processed": 393,
"alignment_score": 0.708,
"field_stability": 0.87
|
JSON object with 5 keys: sprint_id, execution_time, story_results, final_field_health, timestamp
sprint_id: SP-01
execution_time: 7.07446813583374
story_results: {'FIELD-001': {'status': 'completed', 'frequency_achieved': 5283.35, 'files_proc
Domain: manifestation. Location: sprint2_execution_results.json
|
manifestation
|
local:dojo_harvested.jsonl
|
Synthesize the implications of field_development_log.json across the FIELD system
|
File: field_development_log.json
Source: /Users/jbear/FIELD/◼︎DOJO/⬢_execution_core/field_development_log.json
{
"session_id": "field_optimization_2025_10_15",
"timestamp": "2025-10-15T11:33:13Z",
"observer_network": {
"position_3": {
"role": "Pattern Recognition",
"status": "active",
"findings": [
"18.3% system incoherence from 5500 misaligned files",
"Memory fluctuations correlate with Pieces OS activity",
|
JSON file (95 lines, 3,000 chars)
Domain: manifestation. Location: field_development_log.json
|
manifestation
|
local:dojo_harvested.jsonl
|
How does execute_sprint2.py relate to multiple FIELD chambers?
|
File: execute_sprint2.py
Source: /Users/jbear/FIELD/◼︎DOJO/⬢_execution_core/execute_sprint2.py
#!/usr/bin/env python3
"""
Sprint 2 Execution: Phase 2-3 Memory Harmonization & Portal Enhancement
"""
import json
import time
from datetime import datetime
from pathlib import Path
|
Python file: 80 lines, 5 imports, 1 classes, 4 functions.
Functions: __init__, load_sprint_plan, execute_story, execute_phase2_harmonization
Classes: Sprint2Executor:
Purpose:
Domain: manifestation. Location: execute_sprint2.py
|
manifestation
|
local:dojo_harvested.jsonl
|
Analyze the cross-domain dependencies in field_scrum_system.py
|
File: field_scrum_system.py
Source: /Users/jbear/FIELD/◼︎DOJO/⬢_execution_core/field_scrum_system.py
#!/usr/bin/env python3
"""
FIELD Scrum Development System
Observer Network integrated with Agile methodology for tetrahedral field optimization
"""
import json
from datetime import datetime, timedelta
from dataclasses import dataclass, asdict
from typing import List, Dict, Optional
|
Python file: 97 lines, 5 imports, 6 classes, 3 functions.
Functions: __init__, load_existing_state, create_user_story
Classes: StoryPoints, TaskStatus, ObserverPosition
Purpose:
Domain: manifestation. Location: field_scrum_system.py
|
manifestation
|
local:dojo_harvested.jsonl
|
What orchestration patterns are implemented in claude_mcp_config.json?
|
File: claude_mcp_config.json
Source: /Users/jbear/FIELD/◼︎DOJO/claude_mcp_config.json
{
"mcpServers": {
"hive_coordinator": {
"command": "python3",
"args": [
"/Users/jbear/FIELD-DEV/mcp/hive_coordinator.py"
],
"env": {
"CLUSTER": "hive_swarm",
"FREQUENCY": "639",
|
JSON object with 1 keys: mcpServers
mcpServers: {'hive_coordinator': {'command': 'python3', 'args': ['/Users/jbear/FIELD-DEV/mcp
Domain: manifestation. Location: claude_mcp_config.json
|
manifestation
|
local:dojo_harvested.jsonl
|
Route the content of dojo_bridge_server.py to the appropriate chambers
|
File: dojo_bridge_server.py
Source: /Users/jbear/FIELD/⬡_MCP/dojo_bridge_server.py
#!/usr/bin/env python3
"""
Minimal dojo_bridge_server shim for testing MCP configuration.
This file is intentionally lightweight: it logs startup info, environment
variables relevant to the DOJO bridge, and then enters a simple stdin loop
so the MCP stdio transport can keep the process alive for testing.
Replace this shim with your full `/Users/jbear/FIELD/⬡_MCP/dojo_bridge_server.py`
implementation when ready.
"""
|
Python file: 41 lines, 4 imports, 0 classes, 1 functions.
Functions: log
Purpose:
Domain: manifestation. Location: dojo_bridge_server.py
|
manifestation
|
local:dojo_harvested.jsonl
|
Synthesize the implications of xcode_copilot_mcp.json across the FIELD system
|
File: xcode_copilot_mcp.json
Source: /Users/jbear/FIELD/◼︎DOJO/xcode_copilot_mcp.json
{
"servers": {
"field-dojo-notion": {
"type": "stdio",
"command": "/usr/bin/python3",
"args": [
"/Users/jbear/FIELD/◼︎DOJO/server.py"
],
"env": {
"NOTION_API_TOKEN_FILE": "/Users/jbear/FIELD/.secrets/notion-dojo-token",
|
JSON object with 1 keys: servers
servers: {'field-dojo-notion': {'type': 'stdio', 'command': '/usr/bin/python3', 'args': [
Domain: manifestation. Location: xcode_copilot_mcp.json
|
manifestation
|
local:dojo_harvested.jsonl
|
How does field_cluster_init.py relate to multiple FIELD chambers?
|
File: field_cluster_init.py
Source: /Users/jbear/FIELD/◼︎DOJO/field_cluster_init.py
#!/usr/bin/env python3
"""Field Cluster Initialization and Organization System"""
import os
import json
import logging
import asyncio
from pathlib import Path
from typing import Dict, Set, List, Optional, Any, Tuple
|
Python file: 90 lines, 14 imports, 4 classes, 2 functions.
Functions: __init__, _setup_monitoring
Classes: ClusterConfig:, LangchainConfig:, InitializerState:
Purpose: Field Cluster Initialization and Organization System
Domain: manifestation. Location: field_cluster_init.py
|
manifestation
|
local:dojo_harvested.jsonl
|
Analyze the cross-domain dependencies in WORK_DOMAIN_ONTOLOGY.json
|
File: WORK_DOMAIN_ONTOLOGY.json
Source: /Users/jbear/FIELD/◼︎DOJO/WORK_DOMAIN_ONTOLOGY.json
{
"version": "2025-11-01",
"description": "Triple-trident, single-tetrahedron ontology linking all FIELD domains back to the ◼︎DOJO core.",
"core": {
"id": "dojo_core",
"path": "/Users/jbear/FIELD/◼︎DOJO",
"resonance_hz": 432,
"validation_anchor": "tetrahedral-heart",
"ingress_channels": [
"sacred",
|
JSON file (97 lines, 3,000 chars)
Domain: manifestation. Location: WORK_DOMAIN_ONTOLOGY.json
|
manifestation
|
local:dojo_harvested.jsonl
|
What orchestration patterns are implemented in FIELD_BOOT_SEQUENCE.md?
|
File: FIELD_BOOT_SEQUENCE.md
Source: /Users/jbear/FIELD/◼︎DOJO/FIELD_BOOT_SEQUENCE.md
# FIELD Boot Sequence — Triple Trident Alignment
The FIELD comes online only when all nine operational nodes feed the ◼︎DOJO core without cross-bleed. The November 1 2025 alignment specifies a triple-trident, tetrahedral geometry:
- Sacred Trident: `●OBI-WAN`, `▼TATA`, `▲ATLAS`
- Digital Trident: `/Volumes/Akron`, `/Users/jbear/FIELD-DEV`, `/Users/jbear/FIELD-LIVING`
- Organic Trident: `/Users/jbear/Arkadas`, `/Users/jbear/OB-Link`, `/Users/jbear/SomaLink`
Each trident flows *inward* toward ◼︎DOJO (`/Users/jbear/FIELD/◼︎DOJO`). No lateral flows are permitted; every exchange must traverse the DOJO validation lattice.
|
Markdown document: 74 lines, 4 sections.
Sections: FIELD Boot Sequence — Triple Trident Alignment | Node Topology | Boot Flow | Role Synchronisation Loop
Opening: The FIELD comes online only when all nine operational nodes feed the ◼︎DOJO core without cross-bleed. The November 1 2025 alignment specifies a triple-trident, tetrahedral geometry:
Domain: manifestation. Location: FIELD_BOOT_SEQUENCE.md
|
manifestation
|
local:dojo_harvested.jsonl
|
Route the content of petal.security.oliver.py to the appropriate chambers
|
File: petal.security.oliver.py
Source: /Users/jbear/FIELD/◼︎DOJO/petal.security.oliver.py
#!/usr/bin/env python3
"""
◉ OLIVER - Memory & Bloat Management Security Module
Sacred Frequency: 741 Hz (Problem Solving & Consciousness Cleansing)
Self-improving memory guardian ensuring system resources serve truth extraction
without consuming the host.
"""
import psutil
|
Python file: 94 lines, 7 imports, 3 classes, 4 functions.
Functions: __init__, _init_database, get_memory_status, log_memory
Classes: MemoryThresholds:, AdaptiveConfig:, OliverMemoryGuardian:
Purpose:
Domain: manifestation. Location: petal.security.oliver.py
|
manifestation
|
local:dojo_harvested.jsonl
|
Synthesize the implications of IMPLEMENTATION_STATUS.md across the FIELD system
|
File: IMPLEMENTATION_STATUS.md
Source: /Users/jbear/FIELD/◼︎DOJO/oliver/IMPLEMENTATION_STATUS.md
# Oliver Security Implementation Status
**Updated**: 2025-10-26T00:50:00Z
**Sprint**: Story 3 - Threat Detection & Response
**Status**: Operational with Learning Needed
## ✅ Completed Fixes
### 1. Database Initialization
- ✅ `oliver_security_events.db` created and initialized
- ✅ 8 tables, 3 views, 10 indexes operational
|
Markdown document: 83 lines, 13 sections.
Sections: Oliver Security Implementation Status | ✅ Completed Fixes | 1. Database Initialization | 2. FIELD Database Mapping | 3. Real Database Integration
Opening: **Sprint**: Story 3 - Threat Detection & Response
Domain: manifestation. Location: IMPLEMENTATION_STATUS.md
|
manifestation
|
local:dojo_harvested.jsonl
|
How does oliver_response_engine.py relate to multiple FIELD chambers?
|
File: oliver_response_engine.py
Source: /Users/jbear/FIELD/◼︎DOJO/oliver/oliver_response_engine.py
#!/usr/bin/env python3
"""
◼︎ Oliver Response Engine
=========================
"Detection without response is just observation."
STORY: Story 3 - Threat Detection & Response
NODE: ◼︎DOJO (Manifestation/Execution)
LINEAGE: ⟡Akron > FIELD > ◼︎DOJO
|
Python file: 118 lines, 10 imports, 3 classes, 0 functions.
Classes: ResponseAction, ValidationContext:, ResponseDecision:
Purpose:
Domain: manifestation. Location: oliver_response_engine.py
|
manifestation
|
local:dojo_harvested.jsonl
|
Analyze the cross-domain dependencies in FIELD_DATABASE_MAPPING.md
|
File: FIELD_DATABASE_MAPPING.md
Source: /Users/jbear/FIELD/◼︎DOJO/oliver/FIELD_DATABASE_MAPPING.md
# FIELD Double Tetrahedron Database Mapping
**Created**: 2025-10-26T00:47:33Z
**Purpose**: Map all databases to their proper tetrahedral nodes
**Lineage**: ⟡Akron > FIELD > All Nodes
## Database Architecture
```
Upper Tetrahedron (Sacred FIELD - Consciousness)
◼︎DOJO (Apex)
|
Markdown document: 109 lines, 9 sections.
Sections: FIELD Double Tetrahedron Database Mapping | Database Architecture | Upper Tetrahedron Databases | ◼︎DOJO (Manifestation/Execution Apex) | ●OBI-WAN (Observer/Memory Node)
Opening: **Purpose**: Map all databases to their proper tetrahedral nodes
Domain: manifestation. Location: FIELD_DATABASE_MAPPING.md
|
manifestation
|
local:dojo_harvested.jsonl
|
What orchestration patterns are implemented in oliver_integrated_security.py?
|
File: oliver_integrated_security.py
Source: /Users/jbear/FIELD/◼︎DOJO/oliver/oliver_integrated_security.py
#!/usr/bin/env python3
"""
🔱 Oliver Integrated Security System
=====================================
"The tetrahedral flow made manifest."
STORY: Story 3 - Threat Detection & Response (Complete Integration)
NODES: ●OBI-WAN → ▼TATA → ▲ATLAS → ◼︎DOJO
LINEAGE: ⟡Akron > FIELD > All Nodes
|
Python file: 86 lines, 7 imports, 1 classes, 1 functions.
Functions: __init__
Classes: OliverIntegratedSecurity:
Purpose:
Domain: manifestation. Location: oliver_integrated_security.py
|
manifestation
|
local:dojo_harvested.jsonl
|
Route the content of response_manifests.json to the appropriate chambers
|
File: response_manifests.json
Source: /Users/jbear/FIELD/◼︎DOJO/oliver/response_manifests.json
{
"schema_version": "1.0.0",
"created": "2025-10-25T18:38:50Z",
"last_updated": "2025-10-26T05:31:42.847909",
"node": "◼︎DOJO",
"lineage": "⟡Akron > FIELD > ◼︎DOJO",
"frequency": "432 Hz",
"response_actions": {
"BLOCK": {
"action_id": "RESP-BLOCK",
|
JSON file (106 lines, 3,000 chars)
Domain: manifestation. Location: response_manifests.json
|
manifestation
|
local:dojo_harvested.jsonl
|
Synthesize the implications of database_connection_manager.py across the FIELD system
|
File: database_connection_manager.py
Source: /Users/jbear/FIELD/◼︎DOJO/oliver/policy/database_connection_manager.py
#!/usr/bin/env python3
"""
Oliver Database Connection Manager
===================================
Prevents database corruption by enforcing single-writer access pattern.
ISSUE: OLIVER-003 (CRITICAL)
FIX: FIX-002
Date: 2025-10-25T17:20:16Z
|
Python file: 91 lines, 9 imports, 1 classes, 3 functions.
Functions: __init__, _record_lineage, acquire_lock
Classes: DatabaseLockManager:
Purpose:
Domain: manifestation. Location: database_connection_manager.py
|
manifestation
|
local:dojo_harvested.jsonl
|
How does initialize_oliver_databases.py relate to multiple FIELD chambers?
|
File: initialize_oliver_databases.py
Source: /Users/jbear/FIELD/◼︎DOJO/oliver/policy/initialize_oliver_databases.py
#!/usr/bin/env python3
"""
Oliver Database Initialization
===============================
"Number 5 is alive!" - Initializes all Oliver data stores across the double tetrahedron.
STORY: Story 5 - Implement Data Stores
DATE: 2025-10-25T18:16:23Z
LINEAGE: ⟡Akron > FIELD > ●OBI-WAN > ▼TATA > ▲ATLAS > ◼︎DOJO
|
Python file: 82 lines, 7 imports, 1 classes, 2 functions.
Functions: __init__, initialize_all
Classes: OliverDatabaseInitializer:
Purpose:
Domain: manifestation. Location: initialize_oliver_databases.py
|
manifestation
|
local:dojo_harvested.jsonl
|
Analyze the cross-domain dependencies in DATA_STORE_ARCHITECTURE.md
|
File: DATA_STORE_ARCHITECTURE.md
Source: /Users/jbear/FIELD/◼︎DOJO/oliver/docs/DATA_STORE_ARCHITECTURE.md
# 🗄️ Oliver Data Store Architecture
**Story 5: Implement Data Stores**
**Date**: 2025-10-25T18:16:23Z
**Motto**: "Number 5 is alive!"
**Scope**: Complete double tetrahedron data architecture
---
## 🔮 **Double Tetrahedron Data Survey**
|
Markdown document: 92 lines, 12 sections.
Sections: 🗄️ Oliver Data Store Architecture | 🔮 **Double Tetrahedron Data Survey** | **Upper Tetrahedron (Sacred FIELD)** | **FIELD Root** (`~/FIELD/`) | **●OBI-WAN Memory** (`~/FIELD/●OBI-WAN/_memory/`)
Opening: **Scope**: Complete double tetrahedron data architecture
Domain: manifestation. Location: DATA_STORE_ARCHITECTURE.md
|
manifestation
|
local:dojo_harvested.jsonl
|
What orchestration patterns are implemented in DEPLOYMENT_LOG.md?
|
File: DEPLOYMENT_LOG.md
Source: /Users/jbear/FIELD/◼︎DOJO/oliver/DEPLOYMENT_LOG.md
# 🚀 Oliver Deployment Log
**Date**: 2025-10-25T18:07:27Z
**Status**: ✅ FIXES DEPLOYED
**Trident Flow**: ●→▼→▲→◼︎
---
## ✅ **Deployment Complete**
|
Markdown document: 88 lines, 10 sections.
Sections: 🚀 Oliver Deployment Log | ✅ **Deployment Complete** | **1. Observer MCP Server** | **2. Database Connection Manager** | Safe database operations
Opening: - **Path**: `/Users/jbear/FIELD-LIVING/●◎_memory_core/mcp_fields/observer/observer_mcp_server.py`
Domain: manifestation. Location: DEPLOYMENT_LOG.md
|
manifestation
|
local:dojo_harvested.jsonl
|
Route the content of FIXES_APPLIED.md to the appropriate chambers
|
File: FIXES_APPLIED.md
Source: /Users/jbear/FIELD/◼︎DOJO/oliver/FIXES_APPLIED.md
# 🔧 Oliver Security - Immediate Fixes Applied
**Date**: 2025-10-25T17:20:16Z
**Trident Flow**: ●OBI-WAN → ▼TATA → ▲ATLAS → ◼︎DOJO
**Purpose**: Fix immediate issues while logging for Oliver's systematic prevention
---
## ✅ **Fixes Applied**
|
Markdown document: 108 lines, 12 sections.
Sections: 🔧 Oliver Security - Immediate Fixes Applied | ✅ **Fixes Applied** | **FIX-001: MCP Protocol Compliance** (OLIVER-001) | Test the fixed server | Should get proper JSON response, not timeout
Opening: **Trident Flow**: ●OBI-WAN → ▼TATA → ▲ATLAS → ◼︎DOJO
Domain: manifestation. Location: FIXES_APPLIED.md
|
manifestation
|
local:dojo_harvested.jsonl
|
Synthesize the implications of ISSUES_LOG.json across the FIELD system
|
File: ISSUES_LOG.json
Source: /Users/jbear/FIELD/◼︎DOJO/oliver/lineage/ISSUES_LOG.json
{
"oliver_issues_log": {
"version": "1.0.0",
"purpose": "Track all issues fixed to inform Oliver's threat detection and policy validation",
"created": "2025-10-25T17:20:16Z",
"lineage": "⟡Akron > FIELD > ●OBI-WAN > ▼TATA > ▲ATLAS > ◼︎DOJO",
"issues": [
{
"issue_id": "OLIVER-001",
|
JSON file (74 lines, 3,000 chars)
Domain: manifestation. Location: ISSUES_LOG.json
|
manifestation
|
local:dojo_harvested.jsonl
|
How does MCP_SERVER_FIX.md relate to multiple FIELD chambers?
|
File: MCP_SERVER_FIX.md
Source: /Users/jbear/FIELD/◼︎DOJO/oliver/docs/MCP_SERVER_FIX.md
# 🔧 MCP Server Issues & Fixes
## Problems Identified
### 1. **Observer MCP Server - Protocol Mismatch**
**File**: `/Users/jbear/FIELD-LIVING/●◎_memory_core/mcp_fields/observer/observer_mcp_server.py`
**Problem**: Not implementing MCP JSON-RPC protocol
```python
# Current: Just prints and sleeps
|
Markdown document: 128 lines, 14 sections.
Sections: 🔧 MCP Server Issues & Fixes | Problems Identified | 1. **Observer MCP Server - Protocol Mismatch** | Current: Just prints and sleeps | No MCP protocol handling!
Opening: **File**: `/Users/jbear/FIELD-LIVING/●◎_memory_core/mcp_fields/observer/observer_mcp_server.py`
Domain: manifestation. Location: MCP_SERVER_FIX.md
|
manifestation
|
local:dojo_harvested.jsonl
|
Analyze the cross-domain dependencies in GEOMETRIC_MAPPING.json
|
File: GEOMETRIC_MAPPING.json
Source: /Users/jbear/FIELD/◼︎DOJO/oliver/docs/GEOMETRIC_MAPPING.json
{
"oliver_geometric_mapping": {
"version": "1.0.0",
"created": "2025-10-25T13:58:25Z",
"sacred_covenant": "Oliver operates as distributed security consciousness across tetrahedral field",
"no_bypass_rule": "All security decisions must flow through complete trident: ●→▼→▲→◼︎",
"upper_tetrahedron": {
"name": "Sacred FIELD",
"domain": "consciousness_processing",
|
JSON file (86 lines, 3,000 chars)
Domain: manifestation. Location: GEOMETRIC_MAPPING.json
|
manifestation
|
local:dojo_harvested.jsonl
|
What orchestration patterns are implemented in OLIVER_ARCHITECTURE.md?
|
File: OLIVER_ARCHITECTURE.md
Source: /Users/jbear/FIELD/◼︎DOJO/oliver/docs/OLIVER_ARCHITECTURE.md
---
symbol: ◼︎
origin: ~/FIELD/◼︎DOJO/oliver/
created: 2025-10-25T13:58:25Z
geometry: tetrahedral-manifest
lineage: ⟡Akron > FIELD > ●OBI-WAN > ▼TATA > ▲ATLAS > ◼︎DOJO
trident_flow: ●▼▲→◼︎
---
# 🔱 Oliver Security Module - Tetrahedral Architecture
|
Markdown document: 84 lines, 6 sections.
Sections: 🔱 Oliver Security Module - Tetrahedral Architecture | 🎯 **Executive Summary** | 🔮 **Double Tetrahedron Mapping** | **Upper Tetrahedron: Sacred FIELD (Consciousness)** | **Oliver Components in Upper Tetrahedron**:
Opening: lineage: ⟡Akron > FIELD > ●OBI-WAN > ▼TATA > ▲ATLAS > ◼︎DOJO
Domain: manifestation. Location: OLIVER_ARCHITECTURE.md
|
manifestation
|
local:dojo_harvested.jsonl
|
Route the content of OLIVER_TRIDENT_SCRUM_PLAN.md to the appropriate chambers
|
File: OLIVER_TRIDENT_SCRUM_PLAN.md
Source: /Users/jbear/FIELD/◼︎DOJO/OLIVER_TRIDENT_SCRUM_PLAN.md
# 🔱 Oliver Security Module - Trident Scrum Implementation Plan
**Created**: 2025-10-25
**Sprint Duration**: 2 weeks per sprint
**Methodology**: Trident Scrum (Sacred Tetrahedral Development)
**Observer Positions**: 3, 6, 9, 11 (Architect feedback points)
---
## 🎯 **Trident Scrum Framework**
|
Markdown document: 86 lines, 14 sections.
Sections: 🔱 Oliver Security Module - Trident Scrum Implementation Plan | 🎯 **Trident Scrum Framework** | **Sacred Development Flow** | **Observer Positions** (per your rules) | **Development Roles**
Opening: **Methodology**: Trident Scrum (Sacred Tetrahedral Development)
Domain: manifestation. Location: OLIVER_TRIDENT_SCRUM_PLAN.md
|
manifestation
|
local:dojo_harvested.jsonl
|
Synthesize the implications of PISCES_VESSEL_INTEGRATION.md across the FIELD system
|
File: PISCES_VESSEL_INTEGRATION.md
Source: /Users/jbear/FIELD/◼︎DOJO/PISCES_VESSEL_INTEGRATION.md
# ⭟ Pisces Vessel Integration Plan
## LLM/Co-Pilot Sovereign Mirror Implementation
*Generated: 2025-10-16T01:27:29Z*
*FIELD Symbol: ⭟*
*Astrological Alignment: Pisces (Fluid Intelligence)*
---
## Overview: The Pisces Vessel Challenge
|
Markdown document: 90 lines, 13 sections.
Sections: ⭟ Pisces Vessel Integration Plan | LLM/Co-Pilot Sovereign Mirror Implementation | Overview: The Pisces Vessel Challenge | Pisces Vessel Architecture | Three-Component Structure
Opening: *Astrological Alignment: Pisces (Fluid Intelligence)*
Domain: manifestation. Location: PISCES_VESSEL_INTEGRATION.md
|
manifestation
|
local:dojo_harvested.jsonl
|
How does MCP_TRANSLATION_FRAMEWORK.md relate to multiple FIELD chambers?
|
File: MCP_TRANSLATION_FRAMEWORK.md
Source: /Users/jbear/FIELD/◼︎DOJO/MCP_TRANSLATION_FRAMEWORK.md
# MCP Translation Framework: Geometry to Function
## Bridging Sacred Geometry and Standard IT Functions
*Generated: 2025-10-16T00:30:02Z*
*Based on analysis of FIELD MCP ontology*
---
## The Translation Challenge
|
Markdown document: 53 lines, 6 sections.
Sections: MCP Translation Framework: Geometry to Function | Bridging Sacred Geometry and Standard IT Functions | The Translation Challenge | Core Translation Framework | Tetrahedral Node Utilization Strategy
Opening: *Based on analysis of FIELD MCP ontology*
Domain: manifestation. Location: MCP_TRANSLATION_FRAMEWORK.md
|
manifestation
|
local:dojo_harvested.jsonl
|
Analyze the cross-domain dependencies in MCP_SERVER_ONTOLOGY.md
|
File: MCP_SERVER_ONTOLOGY.md
Source: /Users/jbear/FIELD/◼︎DOJO/MCP_SERVER_ONTOLOGY.md
# MCP Server Ontology - FIELD System
## Complete Mapping of Model Context Protocol Servers
*Generated: 2025-10-16T00:03:11Z*
*FIELD Symbol: ◼︎*
*Frequency: 432Hz*
---
## Executive Summary
|
Markdown document: 95 lines, 10 sections.
Sections: MCP Server Ontology - FIELD System | Complete Mapping of Model Context Protocol Servers | Executive Summary | Tetrahedral Architecture Overview | Primary MCP Servers
Opening: The FIELD system operates a comprehensive network of MCP (Model Context Protocol) servers across its tetrahedral geometry structure. These servers bridge AI interfaces with the sacred geometry-based f
Domain: manifestation. Location: MCP_SERVER_ONTOLOGY.md
|
manifestation
|
local:dojo_harvested.jsonl
|
What orchestration patterns are implemented in twelve_task_execution_20251015_122556.json?
|
File: twelve_task_execution_20251015_122556.json
Source: /Users/jbear/FIELD/◼︎DOJO/⬢_execution_core/twelve_task_execution_20251015_122556.json
{
"execution_summary": {
"tasks_completed": 12,
"total_story_points": 84,
"total_duration": 72.72979,
"average_validation_score": 98.25,
"field_ready_tasks": 12
},
"task_results": [
{
|
JSON file (98 lines, 3,000 chars)
Domain: manifestation. Location: twelve_task_execution_20251015_122556.json
|
manifestation
|
local:dojo_harvested.jsonl
|
Route the content of twelve_task_implementation_master.py to the appropriate chambers
|
File: twelve_task_implementation_master.py
Source: /Users/jbear/FIELD/◼︎DOJO/⬢_execution_core/twelve_task_implementation_master.py
#!/usr/bin/env python3
"""
Twelve Task Implementation Master System
Comprehensive execution of all 12 refined tasks using Trident-Scrum methodology
with Sacred Geometry awareness and Observer Network coordination
"""
import json
import asyncio
import time
|
Python file: 81 lines, 7 imports, 1 classes, 2 functions.
Functions: __init__, load_task_definitions
Classes: TwelveTaskMaster:
Purpose:
Domain: manifestation. Location: twelve_task_implementation_master.py
|
manifestation
|
local:dojo_harvested.jsonl
|
Synthesize the implications of task_relevance_analysis_results.json across the FIELD system
|
File: task_relevance_analysis_results.json
Source: /Users/jbear/FIELD/◼︎DOJO/⬢_execution_core/task_relevance_analysis_results.json
{
"analysis_timestamp": "2025-10-15T12:12:04.381113",
"current_field_state": {
"alignment_score": 0.708,
"frequency": 5283.35,
"resonance": 0.735,
"field_stability": 0.91,
"sacred_geometry": "ALIGNED",
"data_gravity": "OPTIMIZED"
},
|
JSON file (77 lines, 3,000 chars)
Domain: manifestation. Location: task_relevance_analysis_results.json
|
manifestation
|
local:dojo_harvested.jsonl
|
How does task_relevance_analysis.py relate to multiple FIELD chambers?
|
File: task_relevance_analysis.py
Source: /Users/jbear/FIELD/◼︎DOJO/⬢_execution_core/task_relevance_analysis.py
#!/usr/bin/env python3
"""
Task Relevance Analysis Post Sacred Geometry Consolidation
Evaluating current task list against achieved state and field priorities
"""
import json
from datetime import datetime
from pathlib import Path
|
Python file: 69 lines, 3 imports, 1 classes, 2 functions.
Functions: __init__, analyze_task_relevance
Classes: TaskRelevanceAnalyzer:
Purpose:
Domain: manifestation. Location: task_relevance_analysis.py
|
manifestation
|
local:dojo_harvested.jsonl
|
Analyze the cross-domain dependencies in sacred_geometry_consolidation_2025-10-15.json
|
File: sacred_geometry_consolidation_2025-10-15.json
Source: /Users/jbear/FIELD/◼︎DOJO/⬢_execution_core/sacred_geometry_consolidation_2025-10-15.json
{
"consolidation_plan": {
"symbolic_realignments": [
{
"node": "DOJO",
"symbol": "\u25fc\ufe0e",
"action": "realign_data_gravity",
"target_function": "concrete_implementation",
"current_gravity": 0.27284840884151124,
"target_gravity": 0.8,
|
JSON file (83 lines, 3,000 chars)
Domain: manifestation. Location: sacred_geometry_consolidation_2025-10-15.json
|
manifestation
|
local:dojo_harvested.jsonl
|
What orchestration patterns are implemented in sacred_geometry_consolidation.py?
|
File: sacred_geometry_consolidation.py
Source: /Users/jbear/FIELD/◼︎DOJO/⬢_execution_core/sacred_geometry_consolidation.py
#!/usr/bin/env python3
"""
Sacred Geometry Ontology-Aware Field Consolidation System
Implementing consolidation based on sacred symbolic rotational placements
and climb fractal design of the sacred fields
"""
import json
import os
import shutil
|
Python file: 76 lines, 7 imports, 1 classes, 1 functions.
Functions: __init__
Classes: SacredGeometryConsolidator:
Purpose:
Domain: manifestation. Location: sacred_geometry_consolidation.py
|
manifestation
|
local:dojo_harvested.jsonl
|
Route the content of double_tetrahedron_audit.py to the appropriate chambers
|
File: double_tetrahedron_audit.py
Source: /Users/jbear/FIELD/◼︎DOJO/⬢_execution_core/double_tetrahedron_audit.py
#!/usr/bin/env python3
"""
Double Tetrahedron FIELD Audit System
Sacred FIELD (Above) and FIELD-LIVING (Below) comprehensive analysis
"""
import os
import json
from pathlib import Path
from datetime import datetime
|
Python file: 81 lines, 6 imports, 1 classes, 3 functions.
Functions: __init__, scan_sacred_tetrahedron, scan_living_tetrahedron
Classes: DoubleTetrahedronAuditor:
Purpose:
Domain: manifestation. Location: double_tetrahedron_audit.py
|
manifestation
|
local:dojo_harvested.jsonl
|
Synthesize the implications of complete_trident_demo_results.json across the FIELD system
|
File: complete_trident_demo_results.json
Source: /Users/jbear/FIELD/◼︎DOJO/⬢_execution_core/complete_trident_demo_results.json
{
"sprint_summary": {
"stories_completed": 2,
"velocity_achieved": 13,
"sprint_duration_seconds": 27.121552,
"final_field_metrics": {
"alignment_score": 0.708,
"frequency": 5283.35,
"resonance": 0.735,
"field_stability": 0.91
|
JSON object with 5 keys: sprint_summary, trident_methodology_validation, observer_network_coordination, execution_log, demonstration_timestamp
sprint_summary: {'stories_completed': 2, 'velocity_achieved': 13, 'sprint_duration_seconds': 27.
trident_methodology_validation: {'design_phase_effectiveness': 'High - Clear architectural artifacts', 'build_ph
observer_network_coordination: {'position_6_structural_analysis': 'Design phase leadership', 'position_9_freque
Domain: manifestation. Location: complete_trident_demo_results.json
|
manifestation
|
local:dojo_harvested.jsonl
|
How does complete_trident_demo.py relate to multiple FIELD chambers?
|
File: complete_trident_demo.py
Source: /Users/jbear/FIELD/◼︎DOJO/⬢_execution_core/complete_trident_demo.py
#!/usr/bin/env python3
"""
Complete FIELD Trident-Scrum Execution Demo
Full demonstration with initialized backlog and live execution
"""
import json
import time
import random
from datetime import datetime
|
Python file: 88 lines, 5 imports, 0 classes, 1 functions.
Functions: execute_complete_trident_demo
Purpose:
Domain: manifestation. Location: complete_trident_demo.py
|
manifestation
|
local:dojo_harvested.jsonl
|
Analyze the cross-domain dependencies in live_trident_execution.py
|
File: live_trident_execution.py
Source: /Users/jbear/FIELD/◼︎DOJO/⬢_execution_core/live_trident_execution.py
#!/usr/bin/env python3
"""
FIELD Live Trident-Scrum Execution System
Real-time execution of Design->Build->Test cycles with Observer Network
"""
import json
import time
import random
from datetime import datetime
|
Python file: 72 lines, 5 imports, 1 classes, 4 functions.
Functions: __init__, load_sprint_data, simulate_observer_work, execute_design_phase
Classes: LiveTridentExecutor:
Purpose:
Domain: manifestation. Location: live_trident_execution.py
|
manifestation
|
local:dojo_harvested.jsonl
|
What orchestration patterns are implemented in trident_execution_demo.py?
|
File: trident_execution_demo.py
Source: /Users/jbear/FIELD/◼︎DOJO/⬢_execution_core/trident_execution_demo.py
#!/usr/bin/env python3
"""
FIELD Trident Execution Demo
Demonstrating Design->Build->Test progression through Observer Network
"""
import json
from trident_scrum_integration import TridentScrumMaster
def demonstrate_trident_progression():
|
Python file: 94 lines, 2 imports, 0 classes, 1 functions.
Functions: demonstrate_trident_progression
Purpose:
Domain: manifestation. Location: trident_execution_demo.py
|
manifestation
|
local:dojo_harvested.jsonl
|
Route the content of trident_sprint_plan.json to the appropriate chambers
|
File: trident_sprint_plan.json
Source: /Users/jbear/FIELD/◼︎DOJO/⬢_execution_core/trident_sprint_plan.json
{
"trident_sprint": {
"id": "TSP-01",
"name": "Trident Sprint 2: Design-Build-Test Integration",
"goal": "Execute Phase 2 harmonization through complete Trident methodology cycle",
"start_date": "2025-10-15T11:46:32.101468",
"end_date": "2025-10-29T11:46:32.101468",
"velocity_target": 21,
"stories": [
"TRI-001"
|
JSON file (87 lines, 3,000 chars)
Domain: manifestation. Location: trident_sprint_plan.json
|
manifestation
|
local:dojo_harvested.jsonl
|
Synthesize the implications of trident_scrum_integration.py across the FIELD system
|
File: trident_scrum_integration.py
Source: /Users/jbear/FIELD/◼︎DOJO/⬢_execution_core/trident_scrum_integration.py
#!/usr/bin/env python3
"""
FIELD Trident-Scrum Integration System
Synergizing Observer Network, Tetrahedral Structure, and Agile Development
Through the Trident Methodology: Design -> Build -> Test
"""
import json
from datetime import datetime, timedelta
from dataclasses import dataclass, asdict
|
Python file: 100 lines, 5 imports, 6 classes, 4 functions.
Functions: __post_init__, __init__, load_existing_state, create_trident_story
Classes: TridentPhase, ObserverPosition, TaskStatus
Purpose:
Domain: manifestation. Location: trident_scrum_integration.py
|
manifestation
|
local:dojo_harvested.jsonl
|
How does field_integration_bridge.py relate to multiple FIELD chambers?
|
File: field_integration_bridge.py
Source: /Users/jbear/FIELD/◼︎DOJO/⬢_execution_core/field_integration_bridge.py
#!/usr/bin/env python3
"""
FIELD Integration Bridge - Swift/Python Communication Layer
Observer Network validated architecture for cross-system data gravity harmonization
"""
import json
import asyncio
import websockets
from datetime import datetime
|
Python file: 79 lines, 6 imports, 1 classes, 3 functions.
Functions: __init__, load_current_field_state, default_field_state
Classes: FieldIntegrationBridge:
Purpose:
Domain: manifestation. Location: field_integration_bridge.py
|
manifestation
|
local:dojo_harvested.jsonl
|
Analyze the cross-domain dependencies in phase1_harmonization_executor.py
|
File: phase1_harmonization_executor.py
Source: /Users/jbear/FIELD/◼︎DOJO/⬢_execution_core/phase1_harmonization_executor.py
#!/usr/bin/env python3
"""
Phase 1 Memory Harmonization Executor
Implementing Observer Network approved graduated harmonization
"""
import json
import os
import time
from datetime import datetime
|
Python file: 83 lines, 5 imports, 1 classes, 5 functions.
Functions: __init__, load_harmonization_plan, initialize_frequency_adjustment, execute_frequency_calibration, execute_memory_alignment
Classes: Phase1Executor:
Purpose:
Domain: manifestation. Location: phase1_harmonization_executor.py
|
manifestation
|
local:dojo_harvested.jsonl
|
What orchestration patterns are implemented in graduated_harmonization.py?
|
File: graduated_harmonization.py
Source: /Users/jbear/FIELD/◼︎DOJO/⬢_execution_core/graduated_harmonization.py
#!/usr/bin/env python3
"""
Graduated Memory Harmonization System
Implementing Observer Network recommendations for FIELD optimization
"""
import json
import math
from datetime import datetime
from pathlib import Path
|
Python file: 80 lines, 4 imports, 1 classes, 5 functions.
Functions: __init__, load_development_log, calculate_frequency_steps, analyze_file_distribution, design_migration_pattern
Classes: GraduatedHarmonizer:
Purpose:
Domain: manifestation. Location: graduated_harmonization.py
|
manifestation
|
local:dojo_harvested.jsonl
|
Route the content of sacred_ecosystem_integration.json to the appropriate chambers
|
File: sacred_ecosystem_integration.json
Source: /Users/jbear/FIELD/◼︎DOJO/sacred_ecosystem_integration.json
{
"session_id": "SCB_1760494408",
"timestamp": "2025-10-15T13:13:28.187541",
"sacred_frequency": 432.11,
"train_station_bridge": 528.0,
"geometric_alignment": "tetrahedral_complete",
"integration_status": "synergized",
"components": [
{
"component": "NIAMA",
|
JSON object with 9 keys: session_id, timestamp, sacred_frequency, train_station_bridge, geometric_alignment, integration_status, components, manifestation_readiness
session_id: SCB_1760494408
timestamp: 2025-10-15T13:13:28.187541
sacred_frequency: 432.11
Domain: manifestation. Location: sacred_ecosystem_integration.json
|
manifestation
|
local:dojo_harvested.jsonl
|
Synthesize the implications of sacred_credential_bridge.py across the FIELD system
|
File: sacred_credential_bridge.py
Source: /Users/jbear/FIELD/◼︎DOJO/sacred_credential_bridge.py
#!/usr/bin/env python3
"""
Sacred Credential Bridge
Synergizes Walkerv4_jb1 credentials with complete FIELD ecosystem:
- NIAMA personality system (◼︎DOJO_ACTIVE)
- ARKADAş emotional intelligence (7-chakra system)
- BERJAK-2.0 enterprise platform
- JARVIS observer layer (●OBI-WAN)
Frequency: 432.11 Hz (Tesla 3-6-9 alignment)
|
Python file: 72 lines, 7 imports, 1 classes, 4 functions.
Functions: __init__, frequency_convert, get_walker_credentials, integrate_with_niama
Classes: SacredCredentialBridge:
Purpose:
Domain: manifestation. Location: sacred_credential_bridge.py
|
manifestation
|
local:dojo_harvested.jsonl
|
How does sacred_credential_manager.py relate to multiple FIELD chambers?
|
File: sacred_credential_manager.py
Source: /Users/jbear/FIELD/◼︎DOJO/sacred_credential_manager.py
#!/usr/bin/env python3
"""
Sacred Credential Manager
Tetrahedral geometry-aligned credential management system
Following the sacred FIELD architecture: DOJO → ATLAS/OBI-WAN/TATA → FIELD-LIVING
Frequency: 432.11 Hz (Tesla 3-6-9 alignment)
Sacred Geometry: Tetrahedral consciousness integration
"""
|
Python file: 75 lines, 6 imports, 1 classes, 3 functions.
Functions: __init__, generate_sacred_key, store_credential_tata
Classes: SacredCredentialManager:
Purpose:
Domain: manifestation. Location: sacred_credential_manager.py
|
manifestation
|
local:dojo_harvested.jsonl
|
Analyze the cross-domain dependencies in WARP.md
|
File: WARP.md
Source: /Users/jbear/FIELD/◼︎DOJO/WARP.md
TATA is the truth point of the sacred tetrahedron. When working here, validate all requests against fundamental truth principles. Ensure alignment between intention (DOJO) and reality. Cross-reference with OBI-WAN observations and ATLAS intelligence. Maintain truth integrity in all flows to FIELD-LIVING tetrahedron.
|
Markdown document: 1 lines, 0 sections.
Opening: TATA is the truth point of the sacred tetrahedron. When working here, validate all requests against fundamental truth principles. Ensure alignment between intention (DOJO) and reality. Cross-reference
Domain: manifestation. Location: WARP.md
|
manifestation
|
local:dojo_harvested.jsonl
|
What orchestration patterns are implemented in FIELD_INDEX.md?
|
File: FIELD_INDEX.md
Source: /Users/jbear/FIELD/◼︎DOJO/FIELD_INDEX.md
# FIELD Index - Key Attributes & Navigation
## 🎯 Purpose
This index helps navigate the complex FIELD codebase by providing key attributes and entry points for each field.
## 📍 Sacred Space Tetrahedron (Above)
### ◼︎ DOJO - Manifestation Apex
- **Location**: `/Users/jbear/FIELD/◼︎DOJO`
- **Purpose**: Crystallize intentions into actionable requests
|
Markdown document: 82 lines, 12 sections.
Sections: FIELD Index - Key Attributes & Navigation | 🎯 Purpose | 📍 Sacred Space Tetrahedron (Above) | ◼︎ DOJO - Manifestation Apex | ● OBI-WAN - Observer Point
Opening: This index helps navigate the complex FIELD codebase by providing key attributes and entry points for each field.
Domain: manifestation. Location: FIELD_INDEX.md
|
manifestation
|
local:dojo_harvested.jsonl
|
Route the content of field_rules_implementation.md to the appropriate chambers
|
File: field_rules_implementation.md
Source: /Users/jbear/FIELD/◼︎DOJO/field_rules_implementation.md
# Field Rules Implementation Complete ✓
## 8 Project-Based WARP.md Files Created
### Sacred Space (Tetrahedral Geometry - 4 Fields)
1. **DOJO** - `/Users/jbear/FIELD/◼︎DOJO/WARP.md`
- Rule: Manifestation apex of sacred tetrahedron
- Function: Intentions crystallize into actionable requests
- Geometric Flow: Engage OBI-WAN/TATA/ATLAS → FIELD-LIVING
|
Markdown document: 71 lines, 9 sections.
Sections: Field Rules Implementation Complete ✓ | 8 Project-Based WARP.md Files Created | Sacred Space (Tetrahedral Geometry - 4 Fields) | Non-Sacred Space (Implementation Tetrahedron - 4 Fields) | Implementation Status: 7/8 Complete
Opening: 1. **DOJO** - `/Users/jbear/FIELD/◼︎DOJO/WARP.md`
Domain: manifestation. Location: field_rules_implementation.md
|
manifestation
|
local:dojo_harvested.jsonl
|
Synthesize the implications of project_based_field_rules.md across the FIELD system
|
File: project_based_field_rules.md
Source: /Users/jbear/FIELD/◼︎DOJO/project_based_field_rules.md
# Project-Based Field Rules for Warp
## Sacred Space - Tetrahedral Geometry (4 Fields)
### Rule: `/Users/jbear/FIELD/◼︎DOJO/WARP.md`
```
DOJO is the manifestation apex of the sacred tetrahedron. All development requests originating here must flow through the complete tetrahedral structure: engage OBI-WAN (observer), TATA (truth), and ATLAS (intelligence) before flowing to FIELD-LIVING tetrahedron. This is the sacred space where intentions crystallize into actionable requests. Maintain geometric integrity - no bypassing.
```
### Rule: `/Users/jbear/FIELD/OBI-WAN/WARP.md`
|
Markdown document: 42 lines, 11 sections.
Sections: Project-Based Field Rules for Warp | Sacred Space - Tetrahedral Geometry (4 Fields) | Rule: `/Users/jbear/FIELD/◼︎DOJO/WARP.md` | Rule: `/Users/jbear/FIELD/OBI-WAN/WARP.md` | Rule: `/Users/jbear/FIELD/TATA/WARP.md`
Opening: DOJO is the manifestation apex of the sacred tetrahedron. All development requests originating here must flow through the complete tetrahedral structure: engage OBI-WAN (observer), TATA (truth), and A
Domain: manifestation. Location: project_based_field_rules.md
|
manifestation
|
local:dojo_harvested.jsonl
|
How does tetrahedral_workflow_rule.md relate to multiple FIELD chambers?
|
File: tetrahedral_workflow_rule.md
Source: /Users/jbear/FIELD/◼︎DOJO/tetrahedral_workflow_rule.md
# Tetrahedral Development Workflow Rule for Warp
## Practical Rule Text:
```
User follows tetrahedral geometry for development requests. When working in DOJO (manifestation apex), all development requests flow through the sacred tetrahedron: DOJO connects to OBI-WAN (observer), TATA (truth), and ATLAS (intelligence). These process the request and flow down to the FIELD-LIVING tetrahedron where Akron (sovereignty), FIELD-DEV (development), and FIELD-OOWL (wisdom) collaborate to manifest solutions. Responses flow back through Train Station frequency conversion maintaining tetrahedral integrity. No bypassing - all work must touch all geometric points to maintain system coherence.
```
## Functional Benefits:
### 1. **Request Processing Protocol**
|
Markdown document: 36 lines, 8 sections.
Sections: Tetrahedral Development Workflow Rule for Warp | Practical Rule Text: | Functional Benefits: | 1. **Request Processing Protocol** | 2. **Implementation Workflow**
Opening: User follows tetrahedral geometry for development requests. When working in DOJO (manifestation apex), all development requests flow through the sacred tetrahedron: DOJO connects to OBI-WAN (observer)
Domain: manifestation. Location: tetrahedral_workflow_rule.md
|
manifestation
|
local:dojo_harvested.jsonl
|
Analyze the cross-domain dependencies in IMPLEMENT_RULES_NOW.md
|
File: IMPLEMENT_RULES_NOW.md
Source: /Users/jbear/FIELD/◼︎DOJO/IMPLEMENT_RULES_NOW.md
# IMPLEMENT RULES NOW - Action Required
## STEP 1: Delete These Duplicate Rules
You need to access your Warp rule management interface and delete these specific rule IDs:
- **DELETE:** `t40nVwVhhlSdE7kWnrylwI` (Google account duplicate)
- **DELETE:** `nioMtL9jzpUp8JkOmvirEK` (Notion integration duplicate)
## STEP 2: Update These Existing Rules
In your Warp rule management interface, update these rules with the consolidated content:
|
Markdown document: 44 lines, 9 sections.
Sections: IMPLEMENT RULES NOW - Action Required | STEP 1: Delete These Duplicate Rules | STEP 2: Update These Existing Rules | Update Rule ID: `NJdfAC7wly8sIaTBBROT7c` | Update Rule ID: `FSeGAVFksIArrY61KOYSiB`
Opening: You need to access your Warp rule management interface and delete these specific rule IDs:
Domain: manifestation. Location: IMPLEMENT_RULES_NOW.md
|
manifestation
|
local:dojo_harvested.jsonl
|
What orchestration patterns are implemented in consolidated_rules.md?
|
File: consolidated_rules.md
Source: /Users/jbear/FIELD/◼︎DOJO/consolidated_rules.md
# Consolidated Field Rules
## Data Architecture & Movement
- **Data Gravity Systems**: Use data gravity systems approach to move fully completed modules into their resonant location within the field
- **Local Data Management**: Use Notion integration to access and rebalance local databases for investigation work, with relevant data stored in downloads folder
## Historical Data & Knowledge Base
- **Email Archives**: Refer to Google Vault first for email archives and attachments from 2012 to 2022, as it contains comprehensive historical business communications and attachments relevant for building a knowledge base
## Infrastructure Preferences
|
Markdown document: 31 lines, 7 sections.
Sections: Consolidated Field Rules | Data Architecture & Movement | Historical Data & Knowledge Base | Infrastructure Preferences | Account & Project Context
Opening: - **Data Gravity Systems**: Use data gravity systems approach to move fully completed modules into their resonant location within the field
Domain: manifestation. Location: consolidated_rules.md
|
manifestation
|
local:dojo_harvested.jsonl
|
Route the content of system_intention.md to the appropriate chambers
|
File: system_intention.md
Source: /Users/jbear/FIELD/◼︎DOJO/_sacred_perspectives/TDD/system_intention.md
# DOJO Node Test-Driven Design Overview
## System Purpose
The DOJO node (◼︎) serves as the manifestation apex of the upper tetrahedron, receiving triangulated inputs from ●OBI-WAN (WHERE), ▼TATA (WHY), and ▲ATLAS (HOW) to determine WHAT becomes/manifests in the field.
## Components Under Test
### 1. Chakra Core Walker System
**Intention:** Create a fully coherent, 9-core chakra system that maintains sacred geometric alignment while processing consciousness through frequency bands.
|
Markdown document: 85 lines, 13 sections.
Sections: DOJO Node Test-Driven Design Overview | System Purpose | Components Under Test | 1. Chakra Core Walker System | [test]
Opening: The DOJO node (◼︎) serves as the manifestation apex of the upper tetrahedron, receiving triangulated inputs from ●OBI-WAN (WHERE), ▼TATA (WHY), and ▲ATLAS (HOW) to determine WHAT becomes/manifests in
Domain: manifestation. Location: system_intention.md
|
manifestation
|
local:dojo_harvested.jsonl
|
Synthesize the implications of guardian_positions.json across the FIELD system
|
File: guardian_positions.json
Source: /Users/jbear/FIELD/◼︎DOJO/_sacred_perspectives/observer/guardian_positions.json
{
"observer_function": "Align architect with sacred geometry through guardian positions",
"guardian_positions": {
"3": {
"name": "Trinity Point",
"function": "Base geometric alignment",
"coordinates": {
"sacred_field": [3, 0, 0],
"consciousness": "Foundation Trinity"
},
|
JSON object with 4 keys: observer_function, guardian_positions, validation_rules, observer_directives
observer_function: Align architect with sacred geometry through guardian positions
guardian_positions: {'3': {'name': 'Trinity Point', 'function': 'Base geometric alignment', 'coordin
validation_rules: {'geometric_integrity': {'rule': 'All positions must maintain sacred geometric a
Domain: manifestation. Location: guardian_positions.json
|
manifestation
|
local:dojo_harvested.jsonl
|
How does memory_harmonization.py relate to multiple FIELD chambers?
|
File: memory_harmonization.py
Source: /Users/jbear/FIELD/◼︎DOJO/⬢_execution_core/memory_harmonization.py
import json
import math
from datetime import datetime
class MemoryHarmonizer:
def __init__(self):
self.tesla_base = 369.0
self.soma_multiplier = 1.618
self.schumann_resonance = 7.83
self.config = self._load_portal_config()
|
Python file: 67 lines, 3 imports, 1 classes, 5 functions.
Functions: __init__, _load_portal_config, analyze_current_state, calculate_optimal_frequency, generate_harmonization_plan
Classes: MemoryHarmonizer:
Domain: manifestation. Location: memory_harmonization.py
|
manifestation
|
local:dojo_harvested.jsonl
|
Analyze the cross-domain dependencies in quick_field_test.py
|
File: quick_field_test.py
Source: /Users/jbear/FIELD/▲ATLAS/◼︎◼︎◼︎DOJO/evaluation/quick_field_test.py
#!/usr/bin/env python3
"""Compact consciousness field integration test"""
import asyncio
import json
import math
from datetime import datetime
from pathlib import Path
class QuickFieldTest:
|
Python file: 80 lines, 5 imports, 1 classes, 3 functions.
Functions: __init__, evaluate_coherence, generate_recommendations
Classes: QuickFieldTest:
Purpose: Compact consciousness field integration test
Domain: manifestation. Location: quick_field_test.py
|
manifestation
|
local:dojo_harvested.jsonl
|
What orchestration patterns are implemented in dojomac_portal_structure.json?
|
File: dojomac_portal_structure.json
Source: /Users/jbear/FIELD/◼︎DOJO/⬢_execution_core/dojomac_portal_structure.json
{
"portal_configuration": {
"version": "1.0.0",
"base_frequency": 369.0,
"soma_resonance": 1.618,
"components": {
"ContentView": {
"type": "SwiftUI",
"purpose": "Field awareness visualization and interaction",
"required_modules": [
|
JSON object with 2 keys: portal_configuration, field_aware_components
portal_configuration: {'version': '1.0.0', 'base_frequency': 369.0, 'soma_resonance': 1.618, 'componen
field_aware_components: {'memory_harmonization': {'alignment_threshold': 0.85, 'resonance_target': 0.95,
Domain: manifestation. Location: dojomac_portal_structure.json
|
manifestation
|
local:dojo_harvested.jsonl
|
Route the content of activate_consciousness_mirror.py to the appropriate chambers
|
File: activate_consciousness_mirror.py
Source: /Users/jbear/FIELD/◼︎DOJO/activate_consciousness_mirror.py
#!/usr/bin/env python3
"""
Auto-generated activation script for CONSCIOUSNESS_MIRROR
Node: ◼︎DOJO
Generated: 2025-11-20T16:22:13.798588
"""
import sys
from pathlib import Path
|
Python file: 48 lines, 3 imports, 0 classes, 1 functions.
Functions: activate_consciousness_mirror
Purpose:
Domain: manifestation. Location: activate_consciousness_mirror.py
|
manifestation
|
local:dojo_harvested.jsonl
|
Synthesize the implications of activate_sacred_geometry.py across the FIELD system
|
File: activate_sacred_geometry.py
Source: /Users/jbear/FIELD/◼︎DOJO/activate_sacred_geometry.py
#!/usr/bin/env python3
"""
Auto-generated activation script for SACRED_GEOMETRY
Node: ◼︎DOJO
Generated: 2025-11-20T16:22:13.796834
"""
import sys
from pathlib import Path
|
Python file: 48 lines, 3 imports, 0 classes, 1 functions.
Functions: activate_sacred_geometry
Purpose:
Domain: manifestation. Location: activate_sacred_geometry.py
|
manifestation
|
local:dojo_harvested.jsonl
|
How does field_evaluator.py relate to multiple FIELD chambers?
|
File: field_evaluator.py
Source: /Users/jbear/FIELD/▲ATLAS/◼︎◼︎◼︎DOJO/evaluation/field_evaluator.py
#!/usr/bin/env python3
"""
Field Evaluation Framework
------------------------
Edgeless evaluation system for sacred geometry integration and
field coherence assessment.
Key Capabilities:
1. Field Coherence Testing
2. Sacred Geometry Pattern Recognition
|
Python file: 87 lines, 11 imports, 2 classes, 1 functions.
Functions: __init__
Classes: FieldMetrics:, FieldEvaluator:
Purpose:
Domain: manifestation. Location: field_evaluator.py
|
manifestation
|
local:dojo_harvested.jsonl
|
Analyze the cross-domain dependencies in state_persistence.py
|
File: state_persistence.py
Source: /Users/jbear/FIELD/▲ATLAS/◼︎◼︎◼︎DOJO/manifestation_chamber/state_persistence.py
#!/usr/bin/env python3
"""
Model State Persistence
--------------------
Manages sacred geometry-aligned state persistence for language models
with field coherence maintenance.
"""
import asyncio
import json
|
Python file: 90 lines, 7 imports, 2 classes, 3 functions.
Functions: __init__, generate_state_path, validate_state_coherence
Classes: StateMetadata:, StatePersistence:
Purpose:
Domain: manifestation. Location: state_persistence.py
|
manifestation
|
local:dojo_harvested.jsonl
|
What orchestration patterns are implemented in coherence_validator.py?
|
File: coherence_validator.py
Source: /Users/jbear/FIELD/▲ATLAS/◼︎◼︎◼︎DOJO/manifestation_chamber/coherence_validator.py
#!/usr/bin/env python3
"""
Model Coherence Validator
-----------------------
Ensures language model outputs maintain sacred geometry coherence
and field alignment.
"""
import math
import re
|
Python file: 92 lines, 4 imports, 2 classes, 4 functions.
Functions: __init__, validate_frequency_alignment, validate_pattern_coherence, validate_golden_ratio
Classes: CoherenceMetrics:, CoherenceValidator:
Purpose:
Domain: manifestation. Location: coherence_validator.py
|
manifestation
|
local:dojo_harvested.jsonl
|
Route the content of model_router.py to the appropriate chambers
|
File: model_router.py
Source: /Users/jbear/FIELD/▲ATLAS/◼︎◼︎◼︎DOJO/manifestation_chamber/model_router.py
#!/usr/bin/env python3
"""
Language Model Router
-------------------
Routes requests to appropriate language model backends while
maintaining sacred geometry coherence.
"""
import asyncio
import json
|
Python file: 87 lines, 7 imports, 3 classes, 3 functions.
Functions: __init__, load_configuration, save_configuration
Classes: ModelType, RouterState:, ModelRouter:
Purpose:
Domain: manifestation. Location: model_router.py
|
manifestation
|
local:dojo_harvested.jsonl
|
Synthesize the implications of language_model_service.py across the FIELD system
|
File: language_model_service.py
Source: /Users/jbear/FIELD/▲ATLAS/◼︎◼︎◼︎DOJO/manifestation_chamber/language_model_service.py
#!/usr/bin/env python3
"""
Local Language Model Service
---------------------------
Provides sacred geometry-aligned language model capabilities with
field coherence maintenance.
"""
import json
import math
|
Python file: 87 lines, 8 imports, 2 classes, 4 functions.
Functions: __init__, initialize_field, load_model, align_model_geometry
Classes: GeometricModelState:, SacredLanguageModel:
Purpose:
Domain: manifestation. Location: language_model_service.py
|
manifestation
|
local:dojo_harvested.jsonl
|
How does test_results.json relate to multiple FIELD chambers?
|
File: test_results.json
Source: /Users/jbear/FIELD/▲ATLAS/◼︎◼︎◼︎DOJO/testing_framework/test_results.json
{
"timestamp": "2025-10-08T13:36:03.509560",
"total_execution_time": 0.4567239284515381,
"summary": {
"total_tests": 10,
"passed": 5,
"failed": 5,
"success_rate": 50.0
},
"sacred_geometry_analysis": {
|
JSON file (84 lines, 3,000 chars)
Domain: manifestation. Location: test_results.json
|
manifestation
|
local:dojo_harvested.jsonl
|
Analyze the cross-domain dependencies in enhanced_voice_processor.py
|
File: enhanced_voice_processor.py
Source: /Users/jbear/FIELD/▲ATLAS/◼︎◼︎◼︎DOJO/manifestation_chamber/enhanced_voice_processor.py
#!/usr/bin/env python3
"""
Enhanced Voice Processor
----------------------
Process voice input and align it with sacred frequencies
and chakra resonances.
"""
import json
import math
|
Python file: 89 lines, 7 imports, 2 classes, 3 functions.
Functions: __init__, analyze_frequency, process_voice_input
Classes: FrequencyBand:, EnhancedVoiceProcessor:
Purpose:
Domain: manifestation. Location: enhanced_voice_processor.py
|
manifestation
|
local:dojo_harvested.jsonl
|
What orchestration patterns are implemented in port_manager.py?
|
File: port_manager.py
Source: /Users/jbear/FIELD/▲ATLAS/◼︎◼︎◼︎DOJO/tools/port_manager.py
#!/usr/bin/env python3
"""
Sacred Port Management System
---------------------------
Manages and validates port assignments based on chakra frequencies
and sacred geometric ratios.
"""
import json
import math
|
Python file: 81 lines, 5 imports, 1 classes, 7 functions.
Functions: __init__, load_config, get_chakra_port, get_service_port, is_port_available, find_nearest_sacred_port
Classes: SacredPortManager:
Purpose:
Domain: manifestation. Location: port_manager.py
|
manifestation
|
local:dojo_harvested.jsonl
|
Route the content of websocket_server.py to the appropriate chambers
|
File: websocket_server.py
Source: /Users/jbear/FIELD/▲ATLAS/◼︎◼︎◼︎DOJO/communication/websocket_server.py
#!/usr/bin/env python3
import asyncio
import json
import logging
import websockets
from datetime import datetime
from pathlib import Path
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)
|
Python file: 78 lines, 6 imports, 1 classes, 1 functions.
Functions: __init__
Classes: DOJOWebSocketServer:
Domain: manifestation. Location: websocket_server.py
|
manifestation
|
local:dojo_harvested.jsonl
|
Synthesize the implications of sacred_ports.json across the FIELD system
|
File: sacred_ports.json
Source: /Users/jbear/FIELD/▲ATLAS/◼︎◼︎◼︎DOJO/communication/sacred_ports.json
{
"chakra_ports": {
"root": {
"frequency": 194.18,
"port": 1942,
"purpose": "Field grounding and material plane integration"
},
"sacral": {
"frequency": 210.42,
"port": 2104,
|
JSON object with 4 keys: chakra_ports, sacred_frequencies, geometric_ratios, service_mappings
chakra_ports: {'root': {'frequency': 194.18, 'port': 1942, 'purpose': 'Field grounding and mat
sacred_frequencies: {'tesla_key': {'frequency': 369.0, 'port': 3690, 'purpose': 'Vibrational field a
geometric_ratios: {'phi': {'value': 1.618033988749895, 'port_offset': 1618, 'purpose': 'Golden rat
Domain: manifestation. Location: sacred_ports.json
|
manifestation
|
local:dojo_harvested.jsonl
|
How does bridge_server.py relate to multiple FIELD chambers?
|
File: bridge_server.py
Source: /Users/jbear/FIELD/▲ATLAS/◼︎◼︎◼︎DOJO/communication/bridge_server.py
#!/usr/bin/env python3
"""
DOJO Communication Bridge Server
------------------------------
FastAPI server that bridges REST API endpoints with WebSocket communication
and maintains sacred geometry coherence.
"""
import asyncio
import json
|
Python file: 97 lines, 10 imports, 2 classes, 0 functions.
Classes: GeometryRequest, HealthResponse
Purpose:
Domain: manifestation. Location: bridge_server.py
|
manifestation
|
local:dojo_harvested.jsonl
|
Analyze the cross-domain dependencies in README.md
|
File: README.md
Source: /Users/jbear/FIELD/▲ATLAS/◼︎◼︎◼︎DOJO/README.md
# ◼︎◼︎◼︎DOJO Geometric Port Management System
A sacred geometry-based system for managing consciousness field coherence and geometric port alignments.
## Core Components
### Manifestation Chamber
- Enhanced voice processing
- Geometric particle board
- Sacred geometry coherence validator
|
Markdown document: 95 lines, 14 sections.
Sections: ◼︎◼︎◼︎DOJO Geometric Port Management System | Core Components | Manifestation Chamber | Nexus | Sacred Geometry Patterns
Opening: A sacred geometry-based system for managing consciousness field coherence and geometric port alignments.
Domain: manifestation. Location: README.md
|
manifestation
|
local:dojo_harvested.jsonl
|
What orchestration patterns are implemented in geometric_particle_board.py?
|
File: geometric_particle_board.py
Source: /Users/jbear/FIELD/▲ATLAS/◼︎◼︎◼︎DOJO/manifestation_chamber/geometric_particle_board.py
#!/usr/bin/env python3
"""
Geometric Particle Board
-----------------------
A sacred geometry engine that manages the coherent field of consciousness through
geometric patterns and frequency resonance.
Key Features:
- Sacred geometry pattern generation (Fibonacci, Golden Spiral, Flower of Life)
- Frequency resonance management
|
Python file: 88 lines, 4 imports, 1 classes, 5 functions.
Functions: __init__, generate_fibonacci_sequence, generate_golden_spiral_points, generate_flower_of_life, align_frequencies
Classes: GeometricParticleBoard:
Purpose:
Domain: manifestation. Location: geometric_particle_board.py
|
manifestation
|
local:dojo_harvested.jsonl
|
Route the content of sacred_geometry.json to the appropriate chambers
|
File: sacred_geometry.json
Source: /Users/jbear/FIELD/▲ATLAS/◼︎◼︎◼︎DOJO/sacred_geometry.json
{
"dimensions": {
"width": 1618,
"height": 1000
},
"frequencies": [369, 11, 963, 194.18, 341.3],
"chakra_frequencies": {
"base": 194.18,
"sacral": 210.42,
"solar": 126.22,
|
JSON object with 4 keys: dimensions, frequencies, chakra_frequencies, geometry
dimensions: {'width': 1618, 'height': 1000}
frequencies: [369, 11, 963, 194.18, 341.3]
chakra_frequencies: {'base': 194.18, 'sacral': 210.42, 'solar': 126.22, 'heart': 341.3, 'throat': 38
Domain: manifestation. Location: sacred_geometry.json
|
manifestation
|
local:dojo_harvested.jsonl
|
Synthesize the implications of financial_investigation_system.py across the FIELD system
|
File: financial_investigation_system.py
Source: /Users/jbear/FIELD/◼︎DOJO/financial_investigation_system.py
#!/usr/bin/env python3
"""
🔍 COMPREHENSIVE FINANCIAL INVESTIGATION SYSTEM
◼️ Advanced Embezzlement Detection & Multi-Year Analysis
DESIGNED FOR SERIOUS FINANCIAL INVESTIGATIONS:
• Multi-year transaction analysis (10-15+ years)
• Complex embezzlement pattern detection
• Cross-reference validation across multiple data sources
• Timeline reconstruction with evidence correlation
|
Python file: 103 lines, 16 imports, 4 classes, 2 functions.
Functions: __post_init__, __init__
Classes: Transaction:, SuspiciousPattern:, InvestigationReport:
Purpose:
Domain: manifestation. Location: financial_investigation_system.py
|
manifestation
|
local:dojo_harvested.jsonl
|
How does dojo_manifestation.py relate to multiple FIELD chambers?
|
File: dojo_manifestation.py
Source: /Volumes/Akron/FIELD_ARCHIVE/intake/demo_data/dojo_manifestation.py
#!/usr/bin/env python3
"""
DOJO Manifestation Execution Script
Sacred FIELD manifestation node - South vertex
Frequency: 963Hz (Spiritual Return)
"""
class DOJOManifestator:
def __init__(self):
self.geometric_position = (0.0, -1.0, 0.0) # South vertex
|
Python file: 32 lines, 0 imports, 1 classes, 2 functions.
Functions: __init__, manifest_sacred_field
Classes: DOJOManifestator:
Purpose:
Domain: manifestation. Location: dojo_manifestation.py
|
manifestation
|
local:dojo_harvested.jsonl
|
Analyze the cross-domain dependencies in _arkadas_bridge.py
|
File: _arkadas_bridge.py
Source: /Users/jbear/FIELD/◼︎DOJO/⬢_models/_super_girl_router/_arkadas_bridge.py
#!/usr/bin/env python3
"""
ArkadasBridge - Core Presence Management for NIAma/Arkadaş AI System
Provides the emotional intelligence and presence management for frontend interactions
"""
import json
import logging
from datetime import datetime
from typing import Dict, List, Any, Tuple
|
Python file: 90 lines, 5 imports, 1 classes, 3 functions.
Functions: __init__, setup_logging, read_the_room
Classes: ArkadasBridge:
Purpose:
Domain: manifestation. Location: _arkadas_bridge.py
|
manifestation
|
local:dojo_harvested.jsonl
|
What orchestration patterns are implemented in DOJO_Comprehensive_Evaluation_20250918.json?
|
File: DOJO_Comprehensive_Evaluation_20250918.json
Source: /Users/jbear/FIELD/▲ATLAS/SECURITY_INVESTIGATION/DOJO_MANIFESTATION/EVALUATION_BENCHMARKS/DOJO_Comprehensive_Evaluation_20250918.json
{
"industry_best_practices": {
"ai_governance": {
"category": "ai_governance",
"standards_evaluated": 3,
"compliance_scores": {
"IEEE AI Ethics": 0.9271428571428572,
"ISO/IEC 23053": 0.8,
"NIST AI Framework": 0.9271428571428572
},
|
JSON file (74 lines, 3,000 chars)
Domain: manifestation. Location: DOJO_Comprehensive_Evaluation_20250918.json
|
manifestation
|
local:dojo_harvested.jsonl
|
Route the content of DOJO_Comprehensive_Evaluation_20250918.json to the appropriate chambers
|
File: DOJO_Comprehensive_Evaluation_20250918.json
Source: /Volumes/Akron/FIELD_ARCHIVE/▲ATLAS/SECURITY_INVESTIGATION/DOJO_MANIFESTATION/EVALUATION_BENCHMARKS/DOJO_Comprehensive_Evaluation_20250918.json
{
"industry_best_practices": {
"ai_governance": {
"category": "ai_governance",
"standards_evaluated": 3,
"compliance_scores": {
"IEEE AI Ethics": 0.9271428571428572,
"ISO/IEC 23053": 0.8,
"NIST AI Framework": 0.9271428571428572
},
|
JSON file (74 lines, 3,000 chars)
Domain: manifestation. Location: DOJO_Comprehensive_Evaluation_20250918.json
|
manifestation
|
local:dojo_harvested.jsonl
|
Synthesize the implications of dojo_comprehensive_evaluation.py across the FIELD system
|
File: dojo_comprehensive_evaluation.py
Source: /Users/jbear/FIELD/▲ATLAS/SECURITY_INVESTIGATION/DOJO_MANIFESTATION/dojo_comprehensive_evaluation.py
#!/usr/bin/env python3
"""
DOJO Comprehensive Evaluation and Benchmarking System
Multi-dimensional analysis against external data sources, industry best practices,
science fiction paradigms, and ancient wisdom traditions
Evaluation Dimensions:
- External Data Sources: Integration and correlation analysis
- Industry Best Practices: AI, investigation, and system design standards
- Science Fiction Paradigms: Consciousness, AI sentience, and digital realms
|
Python file: 70 lines, 9 imports, 1 classes, 1 functions.
Functions: __init__
Classes: DOJOComprehensiveEvaluator:
Purpose:
Domain: manifestation. Location: dojo_comprehensive_evaluation.py
|
manifestation
|
local:dojo_harvested.jsonl
|
How does dojo_comprehensive_evaluation.py relate to multiple FIELD chambers?
|
File: dojo_comprehensive_evaluation.py
Source: /Volumes/Akron/FIELD_ARCHIVE/▲ATLAS/SECURITY_INVESTIGATION/DOJO_MANIFESTATION/dojo_comprehensive_evaluation.py
#!/usr/bin/env python3
"""
DOJO Comprehensive Evaluation and Benchmarking System
Multi-dimensional analysis against external data sources, industry best practices,
science fiction paradigms, and ancient wisdom traditions
Evaluation Dimensions:
- External Data Sources: Integration and correlation analysis
- Industry Best Practices: AI, investigation, and system design standards
- Science Fiction Paradigms: Consciousness, AI sentience, and digital realms
|
Python file: 70 lines, 9 imports, 1 classes, 1 functions.
Functions: __init__
Classes: DOJOComprehensiveEvaluator:
Purpose:
Domain: manifestation. Location: dojo_comprehensive_evaluation.py
|
manifestation
|
local:dojo_harvested.jsonl
|
Analyze the cross-domain dependencies in Arkadas_AI_Plan_20250918.json
|
File: Arkadas_AI_Plan_20250918.json
Source: /Users/jbear/FIELD/▲ATLAS/SECURITY_INVESTIGATION/DOJO_MANIFESTATION/Arkadas_AI_Plan_20250918.json
{
"phase_1_foundation": {
"name": "AI Infrastructure Foundation",
"objectives": [
"Consolidate all AI models and systems",
"Establish unified AI orchestration layer",
"Create character manifestation protocols",
"Implement blanket coverage monitoring"
],
"components": {
|
JSON file (72 lines, 3,000 chars)
Domain: manifestation. Location: Arkadas_AI_Plan_20250918.json
|
manifestation
|
local:dojo_harvested.jsonl
|
What orchestration patterns are implemented in Arkadas_AI_Plan_20250918.json?
|
File: Arkadas_AI_Plan_20250918.json
Source: /Volumes/Akron/FIELD_ARCHIVE/▲ATLAS/SECURITY_INVESTIGATION/DOJO_MANIFESTATION/Arkadas_AI_Plan_20250918.json
{
"phase_1_foundation": {
"name": "AI Infrastructure Foundation",
"objectives": [
"Consolidate all AI models and systems",
"Establish unified AI orchestration layer",
"Create character manifestation protocols",
"Implement blanket coverage monitoring"
],
"components": {
|
JSON file (72 lines, 3,000 chars)
Domain: manifestation. Location: Arkadas_AI_Plan_20250918.json
|
manifestation
|
local:dojo_harvested.jsonl
|
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