2125_GCE/SYSTEM_STATUS.md

SuperDave GlyphRunner - System Status

Date: 2026-05-20
Status: ✅ All Systems Operational

Completed Components

1. LAIN Cognition Engine ✅

• File: gx_lain/lain_cognition.py
• Features:
  • 8-lane symbolic cognition processor
  • Lane processors for: structural_logic, semantic_flow, compression_residue, symbolic_metadata, execution_hints, predictive_scaffolding, contributor_imprint, epoch_resonance
  • Fused symbol generation from lane results
  • Comprehensive execution tracing

2. Supercharged Glyph Registry ✅

• File: glyphs/super_registry.py
• Data Source: /mnt/d/users/dave/Downloads/LEDONOVA/LedoGlyph600.json
• Features:
  • 600 supercharged glyphs with 112 superpowers each
  • Frequency signatures (praw: P, R, A, W)
  • Contributor inheritance (lineage)
  • Symbolic anatomy (originalMetrics)
  • Activation envelopes and resonance profiles
  • API: get_super(), search_super(), list_super_ids(), list_super_by_category(), get_super_by_band(), get_glyphs_by_score_range()
  • Helper: get_super_field() with dot-notation support
  • Stats: super_stats() for registry metadata

3. LAIN ↔ Glyph Bridge ✅

• File: gx_lain/lain_glyph_bridge.py
• Features:
  • load_glyph_context(): Load glyph metadata from registry
  • inject_glyph_metadata_into_lane(): Add glyph fields to lane results
  • compute_glyph_resonance(): Calculate 4-component resonance metrics
  • augment_fused_symbol_with_glyphs(): Enhance fused symbol with glyph context
  • Resonance formula: 40% activation + 30% frequency + 30% symbolic

4. CLI Integration ✅

• File: gx_cli/
• New Command: gx lain <path> [-m MODE]
• Usage: python3 -m gx_cli.main lain file.gx
• Output: Fused symbol, key points, diagnostics, glyph resonance

5. Runtime Integration ✅

• File: gx_lain/runtime.py
• Pipeline:
  1. Load and validate GX binary
  2. Load glyph context (step 1)
  3. Process 8 lanes with glyph metadata injection (steps 2-9)
  4. Fuse lane results with glyph augmentation
  5. Compute diagnostics including glyph resonance
  • Full cognition_trace with operation markers

Test Results

Unit Tests

Supercharged Registry Tests:    12/12 PASS ✅
LAIN Glyph Bridge Tests:        10/10 PASS ✅

Integration Tests

test_compile.py              PASS ✅
test_determinism.py          PASS ✅
test_errors.py               PASS ✅
test_inspect.py              PASS ✅
test_run.py                  PASS ✅
test_summary.py              PASS ✅

Total: 6 test suites, 6 passed, 0 failed

Full Pipeline Verification

✅ Python source → GXCompiler → .gx binary
✅ Load GX binary and validate
✅ Normalize segments (0-7)
✅ Load glyph context from registry
✅ Process 8 lanes with glyph injection
✅ Fuse lane results
✅ Augment with glyph metadata
✅ Render output with cognition trace
✅ Output diagnostics with resonance metrics

Example Execution

# Compile Python source to GX binary
python3 -m gx_cli.main compile source.py -o source.gx

# Execute through LAIN cognition with analysis mode
python3 -m gx_cli.main lain source.gx

# Output includes:
# - Fused symbolic summary (8-lane synthesis)
# - Key points and insights
# - Glyph resonance metrics (activation, frequency, symbolic, overall)
# - Execution diagnostics

Bug Fixes Applied

• Fixed typo in super_registry.py:303 (load_all_superchattracted → load_all_supercharged)
• Verified all imports use relative paths (xic_extensions package)

Data Files

• LedoGlyph600.json: 2.2 MB, exactly 600 glyphs
• Categories: 8 distinct categories
• Score range: 0-300+
• Bands: 0-41 frequency bands

Next Steps (Optional)

• Export cognition results to JSON/YAML
• Add visualization for resonance metrics
• Implement batch processing for multiple .gx files
• Add glyph filtering in CLI (lain --glyph-category communication)

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Project Status: Ready for deployment or further enhancement
All systems operational and tested