# 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**
```python
@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)
```python
@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)
```python
@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:

```python
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()

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

**Behavior**: Extracts per-glyph metrics from pipeline result.

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

#### get_dominant_glyphs()

```python
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()

```python
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

```python
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**:
```python
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

```json
{ "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:
```python
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

```bash
glyph --xic programs/demo_glyph_resonance.gx.json
```

Output includes formatted reports for multiple glyphs with all metrics.

### Example 2: Programmatic Access

```python
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

```python
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** ✅