2125_GCE/XIC_GLYPH_RESONANCE_REPORT.md

XIC v1.5 Glyph Resonance Awareness Upgrade Report

Date: 2026-05-21
Status: ✅ Complete and validated
Scope: Enhanced glyph resonance tracking with comprehensive metric extraction and querying

---

Executive Summary

Extended XIC v1.5 with comprehensive glyph resonance awareness:

1. Enhanced Data Structures (glyphos/symbolic_pipeline.py)

   • New GlyphResonanceMetrics dataclass: weight, lineage_score, contributor_score, frequency_score, grammar_score
   • Enhanced GlyphResonanceMap with utility methods for querying and aggregation
   • Updated FusedSymbol with full resonance metric support

2. Glyph Resonance Utilities

   • extract_glyph_resonances(pipeline_result) → extract per-glyph metrics
   • get_dominant_glyphs(pipeline_result, n=3) → rank glyphs by weight
   • format_glyph_resonance_report(pipeline_result) → human-readable reports

3. Enhanced CALL_GLYPH Operation (xic_ops.py)

   • Now extracts and stores comprehensive resonance data
   • Captures full SymbolicPipelineResult for direct access
   • Stores resonance_metrics dict, global_resonance_score, and execution steps

4. New GET_GLYPH_RESONANCE Instruction (xic_ops.py)

   • Query stored glyph resonance metrics with flexible metric selection
   • Supports: report, global, dominant, weight, lineage, contributor, frequency, grammar
   • Results stored for programmatic access

5. Demo Program (programs/demo_glyph_resonance.gx.json)

   • Two-chain analysis demonstrating resonance metric queries
   • Covers all metric types: report, global, dominant, specific metrics

6. Updated Formal Specification (XIC_SEMANTICS_v1_5.md)

   • Added FusedSymbol structure documentation with example JSON
   • Documented GlyphResonanceMetrics and GlyphResonanceMap
   • Added GET_GLYPH_RESONANCE instruction semantics
   • Clarified glyph resonance data access patterns

Zero breaking changes. All XIC v1 and v1.5 programs continue to work unchanged.

---

Phase 1: Enhanced Data Structures

File: glyphos/symbolic_pipeline.py

New Dataclasses

GlyphResonanceMetrics

@dataclass
class GlyphResonanceMetrics:
    weight: float                  # Relative importance [0.0, 1.0]
    lineage_score: float          # Symbolic ancestry [0.0, 1.0]
    contributor_score: float      # Contribution to fusion [0.0, 1.0]
    frequency_score: float        # Occurrence frequency [0.0, 1.0]
    grammar_score: float          # Structural alignment [0.0, 1.0]

GlyphResonanceMap (Enhanced)

@dataclass
class GlyphResonanceMap:
    resonances: Dict[str, GlyphResonanceMetrics]
    global_resonance_score: float
    
    # New methods:
    def get_glyph_resonance(self, glyph_id: str) → Optional[GlyphResonanceMetrics]
    def get_top_glyphs(self, n: int = 5) → List[tuple[str, GlyphResonanceMetrics]]
    def get_average_resonance(self) → float

FusedSymbol (Updated)

@dataclass
class FusedSymbol:
    summary: str
    glyph_ids: List[str]
    resonance_map: GlyphResonanceMap = field(default_factory=GlyphResonanceMap)
    
    @classmethod
    def from_lain_result(cls, lain_fused_symbol: Dict[str, Any]) → "FusedSymbol"

Parsing LAIN Output

FusedSymbol.from_lain_result() parses LAIN cognition output:

lain_result = {
    "summary": "...",
    "glyph_ids": [...],
    "global_resonance_score": 0.847,
    "resonance_map": {
        "glyph_id": {
            "weight": 0.95,
            "lineage_score": 0.82,
            ...
        }
    }
}

fused_symbol = FusedSymbol.from_lain_result(lain_result)

---

Phase 2: Glyph Resonance Utilities

File: glyphos/symbolic_pipeline.py

extract_glyph_resonances()

def extract_glyph_resonances(
    pipeline_result: "SymbolicPipelineResult",
) → Dict[str, Dict[str, Any]]

Behavior: Extracts per-glyph metrics from pipeline result.

Returns:

{
    "glyph_id": {
        "weight": 0.95,
        "lineage_score": 0.82,
        "contributor_score": 0.89,
        "frequency_score": 0.76,
        "grammar_score": 0.88
    },
    ...
}

get_dominant_glyphs()

def get_dominant_glyphs(
    pipeline_result: "SymbolicPipelineResult",
    n: int = 3,
) → List[tuple[str, float]]

Behavior: Returns top N glyphs ranked by weight.

Returns: [("glyph://compression_theory", 0.95), ("glyph://entropy", 0.73), ...]

format_glyph_resonance_report()

def format_glyph_resonance_report(
    pipeline_result: "SymbolicPipelineResult",
) → str

Behavior: Generates human-readable resonance report.

Output:

Global Resonance Score: 0.847
Glyphs Engaged: 3

Top Glyphs by Weight:
  glyph://compression_theory: weight=0.950, lineage=0.820, contributor=0.890
  glyph://entropy: weight=0.730, lineage=0.680, contributor=0.710
  ...

---

Phase 3: Enhanced CALL_GLYPH Operation

File: xic_ops.py

op_CALL_GLYPH Update

def op_CALL_GLYPH(ctx: XICContext, *args):
    glyph_id = str(args[0])
    payload = str(args[1]) if len(args) > 1 else ""
    
    # Route through symbolic pipeline
    pipeline_result = run_symbolic_pipeline(...)
    
    # Extract resonance metrics
    resonance_metrics = extract_glyph_resonances(pipeline_result)
    global_resonance = pipeline_result.fused_symbol.resonance_map.global_resonance_score
    
    # Store comprehensive result
    ctx._state[f"glyph_{glyph_id}"] = {
        "output_text": pipeline_result.output_text,
        "fused_symbol": {
            "summary": pipeline_result.fused_symbol.summary,
            "glyph_ids": pipeline_result.fused_symbol.glyph_ids,
        } if pipeline_result.fused_symbol else None,
        "resonance_metrics": resonance_metrics,
        "global_resonance_score": global_resonance,
        "steps": [step metadata...],
    }
    
    # Also store full pipeline result for direct access
    ctx._state[f"glyph_{glyph_id}_pipeline_result"] = pipeline_result

Stored Result Structure:

ctx._state[f"glyph_{glyph_id}"] = {
    "output_text": str,
    "fused_symbol": {
        "summary": str,
        "glyph_ids": List[str]
    } | None,
    "resonance_metrics": Dict[str, Dict[str, float]],
    "global_resonance_score": float,
    "steps": List[Dict],
}

---

Phase 4: New GET_GLYPH_RESONANCE Instruction

File: xic_ops.py

Instruction Signature

{ "op": "GET_GLYPH_RESONANCE", "args": ["<glyph_id>", "<metric>"] }

Metrics

Metric	Output	Use Case
<none> / "report"	Formatted report	Overview of all resonance data
"global"	Single float	Overall fusion quality
"dominant"	Top 5 glyphs	Most important engaged glyphs
"weight"	Float for glyph_id	Relative importance
"lineage"	Float for glyph_id	Symbolic ancestry score
"contributor"	Float for glyph_id	Contribution to fusion
"frequency"	Float for glyph_id	Occurrence frequency
"grammar"	Float for glyph_id	Structural alignment

Behavior

1. Looks up stored glyph data: ctx._state[f"glyph_{glyph_id}"]
2. If pipeline result available: uses full data (preferred)
3. Otherwise: uses stored resonance_metrics dict (fallback)
4. Prints formatted output with [XIC-RESONANCE] prefix
5. Stores result in ctx._state[f"resonance_query_{glyph_id}_{metric}"]

Example Outputs

Report (no metric):

[XIC-RESONANCE] Report for glyph://compression_theory:
Global Resonance Score: 0.847
Glyphs Engaged: 3

Top Glyphs by Weight:
  glyph://compression_theory: weight=0.950, lineage=0.820, contributor=0.890
  glyph://entropy: weight=0.730, lineage=0.680, contributor=0.710
  glyph://coding: weight=0.652, lineage=0.590, contributor=0.645

Global Score:

[XIC-RESONANCE] Global resonance for glyph://compression_theory: 0.847

Dominant Glyphs:

[XIC-RESONANCE] Dominant glyphs for glyph://compression_theory:
  glyph://compression_theory: 0.950
  glyph://entropy: 0.730
  glyph://coding: 0.652
  glyph://information: 0.515
  glyph://language: 0.487

Specific Metric:

[XIC-RESONANCE] weight for glyph://compression_theory: 0.950
[XIC-RESONANCE] lineage for glyph://compression_theory: 0.820

---

Demo Program

File: programs/demo_glyph_resonance.gx.json

Comprehensive two-chain demo showcasing:

1. Chain 1 (resonance_analysis_1)

   • CALL_GLYPH with compression_theory
   • Query: report (formatted overview)
   • Query: global (single score)
   • Query: dominant (top 5 glyphs)
   • Query: weight (specific metric)

2. Chain 2 (resonance_analysis_2)

   • CALL_GLYPH with neural_dynamics
   • Query: report
   • Query: lineage, contributor, frequency, grammar (individual metrics)

All queries logged with CHAIN markers for instrumentation.

---

Updated Formal Specification

File: XIC_SEMANTICS_v1_5.md

Additions

1. Glyph Resonance Structure Section

   • FusedSymbol dataclass definition
   • GlyphResonanceMap with methods
   • GlyphResonanceMetrics field documentation
   • Example JSON structure

2. GET_GLYPH_RESONANCE Instruction Semantics

   • Signature, preconditions, postconditions
   • Metric table with descriptions
   • Behavior specification
   • Side effects and remarks

Documentation

Clear path for accessing resonance data:

CALL_GLYPH "glyph_id" "payload"
    ↓
ctx._state["glyph_glyph_id"]  (resonance_metrics + global_resonance_score)
ctx._state["glyph_glyph_id_pipeline_result"]  (full SymbolicPipelineResult)
    ↓
GET_GLYPH_RESONANCE "glyph_id" "metric"  (query and display)

---

Exports and Integration

File: glyphos/__init__.py

Added exports:

• GlyphResonanceMetrics
• GlyphResonanceMap
• extract_glyph_resonances
• get_dominant_glyphs
• format_glyph_resonance_report

All resonance utilities available via:

from glyphos import (
    extract_glyph_resonances,
    get_dominant_glyphs,
    format_glyph_resonance_report,
    GlyphResonanceMetrics,
    GlyphResonanceMap,
)

---

Architecture

Module Hierarchy

glyphos/
  ├── cognitive_kernel.py      (CognitiveKernel, get_kernel, run_symbolic_prompt)
  ├── symbolic_pipeline.py      (SymbolicPipeline, resonance utilities)
  │   ├── SymbolicStep
  │   ├── SymbolicPipelineResult
  │   ├── FusedSymbol
  │   ├── GlyphResonanceMetrics        [NEW]
  │   ├── GlyphResonanceMap            [NEW]
  │   ├── run_symbolic_pipeline
  │   ├── extract_glyph_resonances     [NEW]
  │   ├── get_dominant_glyphs          [NEW]
  │   └── format_glyph_resonance_report [NEW]
  ├── events.py                (EventBus, emit, on)
  └── __init__.py              (exports all)

xic_ops.py
  ├── op_LOAD_MODEL
  ├── op_SET_MODE
  ├── op_SET_PARAM
  ├── op_SET_CONTEXT
  ├── op_RUN_PROMPT
  ├── op_STREAM
  ├── op_CHAIN
  ├── op_CALL_GLYPH            [ENHANCED]
  ├── op_GET_GLYPH_RESONANCE   [NEW]
  ├── op_LOG
  └── OP_TABLE                 [10 ops]

Data Flow (Resonance-Aware)

CALL_GLYPH "glyph_id" "payload"
    ↓
run_symbolic_pipeline(payload, context, glyph_id)
    ↓
[Compress → Manifest → LAIN cognition]
    ↓
SymbolicPipelineResult
├─ steps: [SymbolicStep...]
├─ output_text: str
└─ fused_symbol: FusedSymbol
   ├─ summary: str
   ├─ glyph_ids: [str]
   └─ resonance_map: GlyphResonanceMap
      ├─ global_resonance_score: float
      └─ resonances: {glyph_id → GlyphResonanceMetrics}
    ↓
Store in ctx._state:
├─ glyph_{glyph_id}: {output_text, fused_symbol, resonance_metrics, global_resonance_score, steps}
└─ glyph_{glyph_id}_pipeline_result: SymbolicPipelineResult
    ↓
GET_GLYPH_RESONANCE "glyph_id" "metric"
    ↓
Query + Display → ctx._state["resonance_query_{glyph_id}_{metric}"]

---

Validation Tests

Test Coverage (10 tests)

✅ Test 1: GlyphResonanceMetrics Creation

• Instantiate with all fields
• Verify all fields accessible

✅ Test 2: GlyphResonanceMap Methods

• get_glyph_resonance() retrieval
• get_top_glyphs() sorting
• get_average_resonance() calculation

✅ Test 3: FusedSymbol from_lain_result()

• Parse LAIN output structure
• Verify resonance_map populated
• Check glyph_ids list

✅ Test 4: extract_glyph_resonances()

• Extract metrics from SymbolicPipelineResult
• Verify dict structure
• Check metric values

✅ Test 5: get_dominant_glyphs()

• Rank glyphs by weight
• Return top N correctly
• Verify sorting order

✅ Test 6: format_glyph_resonance_report()

• Generate human-readable output
• Include global score
• List top glyphs

✅ Test 7: op_CALL_GLYPH Storage

• Execute CALL_GLYPH
• Verify ctx.state["glyph*"] populated
• Check resonance_metrics structure

✅ Test 8: op_GET_GLYPH_RESONANCE Query (report)

• Query with no metric
• Verify formatted output
• Check ctx._state storage

✅ Test 9: op_GET_GLYPH_RESONANCE Query (metrics)

• Query global, weight, lineage, contributor, frequency, grammar
• Verify each metric extracted
• Check stored values

✅ Test 10: demo_glyph_resonance Program

• Execute full demo program
• Verify all instructions execute
• Check both chains complete
• Verify resonance queries all succeed

---

Backward Compatibility

✅ XIC v1 programs work unchanged:

• All existing ops maintain same signatures
• Compressed mode execution path unaffected
• demo_chat.gx.json still works

✅ XIC v1.5 programs work unchanged:

• RUN_PROMPT, STREAM, CALL_GLYPH behavior preserved
• run_symbolic_pipeline() signature unchanged
• SymbolicPipelineResult structure preserved

✅ New features are additive:

• GET_GLYPH_RESONANCE is new op, doesn't affect existing ones
• Enhanced CALL_GLYPH stores additional data but doesn't change output behavior
• Enhanced data structures don't break existing access patterns

---

Key Design Decisions

1. Multi-Dimensional Resonance Metrics

Decision: Five separate metrics (weight, lineage, contributor, frequency, grammar) instead of single resonance score.

Rationale: Enables nuanced understanding of glyph engagement. Each dimension captures different aspect of cognitive activity.

2. FusedSymbol.from_lain_result() Class Method

Decision: Parse LAIN output via class method instead of constructor.

Rationale: Allows flexible LAIN output structure. Keeps constructor simple for manual creation.

3. GET_GLYPH_RESONANCE as Separate Instruction

Decision: New instruction instead of extending CALL_GLYPH.

Rationale: Separates concerns (execution vs. introspection). Enables flexible post-execution queries. Supports programmatic access to metrics.

4. Store Full SymbolicPipelineResult

Decision: Keep full pipeline object in ctx._state alongside extracted metrics.

Rationale: Enables direct access to complete data for power users. Supports future introspection capabilities.

---

Files Modified or Created

Created

File	Purpose
programs/demo_glyph_resonance.gx.json	Demo of glyph resonance metric queries
XIC_GLYPH_RESONANCE_REPORT.md	This comprehensive report

Modified

File	Changes
glyphos/symbolic_pipeline.py	+GlyphResonanceMetrics, +GlyphResonanceMap, +FusedSymbol.from_lain_result(), +extract_glyph_resonances, +get_dominant_glyphs, +format_glyph_resonance_report
xic_ops.py	Enhanced op_CALL_GLYPH, +op_GET_GLYPH_RESONANCE, +OP_TABLE entry
glyphos/__init__.py	+exports for resonance utilities and dataclasses
XIC_SEMANTICS_v1_5.md	+Glyph Resonance Structure section, +GET_GLYPH_RESONANCE instruction semantics

Unchanged (Backward Compatibility)

• xic_loader.py
• xic_vm.py
• xic_executor.py
• runtime_executor/runner.py
• glyphos/cognitive_kernel.py (unchanged signature)
• All existing .gx files

---

Usage Examples

Example 1: Query Resonance Report

glyph --xic programs/demo_glyph_resonance.gx.json

Output includes formatted reports for multiple glyphs with all metrics.

Example 2: Programmatic Access

from xic_executor import run_xic
ctx = run_xic("programs/demo_glyph_resonance.gx.json")

# Access resonance query results
report = ctx._state.get("resonance_query_glyph://compression_theory_report")
global_score = ctx._state.get("resonance_query_glyph://compression_theory_global")
dominant = ctx._state.get("resonance_query_glyph://compression_theory_dominant")

Example 3: Direct Pipeline Result Access

from xic_executor import run_xic
ctx = run_xic("programs/demo_glyph_resonance.gx.json")

# Get full pipeline result
pipeline_result = ctx._state.get("glyph_glyph://compression_theory_pipeline_result")
fused_symbol = pipeline_result.fused_symbol

# Query resonance map
top_glyphs = fused_symbol.resonance_map.get_top_glyphs(n=10)
avg_resonance = fused_symbol.resonance_map.get_average_resonance()

---

Testing

All validation tests pass:

[TEST 1] GlyphResonanceMetrics creation ✅
[TEST 2] GlyphResonanceMap methods ✅
[TEST 3] FusedSymbol from_lain_result() ✅
[TEST 4] extract_glyph_resonances() ✅
[TEST 5] get_dominant_glyphs() ✅
[TEST 6] format_glyph_resonance_report() ✅
[TEST 7] op_CALL_GLYPH storage ✅
[TEST 8] op_GET_GLYPH_RESONANCE report ✅
[TEST 9] op_GET_GLYPH_RESONANCE metrics ✅
[TEST 10] demo_glyph_resonance program ✅

---

References

• Formal Specification: See XIC_SEMANTICS_v1_5.md for complete instruction semantics
• Previous Reports:
  • XIC_SYMBOLIC_EXTENSION_REPORT.md (v1 symbolic mode)
  • XIC_SYMBOLIC_PIPELINE_REPORT.md (v1.5 pipeline abstraction)
• Implementation: glyphos/symbolic_pipeline.py, xic_ops.py, glyphos/__init__.py
• Demo: programs/demo_glyph_resonance.gx.json

---

Summary

XIC v1.5 glyph resonance awareness upgrade provides:

• Enhanced Data Structures: GlyphResonanceMetrics with 5-dimensional resonance scoring
• Utility Functions: Extract, rank, and report on glyph resonance metrics
• Query Capability: GET_GLYPH_RESONANCE instruction with flexible metric selection
• Full Introspection: Access complete SymbolicPipelineResult for power users
• Comprehensive Documentation: Updated formal semantics with examples
• Demo Program: Multi-chain example showcasing all resonance query types

No breaking changes. All XIC v1 and v1.5 programs continue to work unchanged.

---

Implementation Complete ✅
All tests passing ✅
Backward compatible ✅
Formal semantics documented ✅
Resonance awareness enabled ✅