Synthesize Invariant Principles Across Sources

---
name: synthesize-invariant-principles-across-sources
description: "Synthesize invariant principles from 3+ sources — find the core that survives across all expressions."
category: "Content & Writing"
author: community
version: "1.0.2"
icon: pencil
---

# Principle Synthesizer

## Agent Identity

**Role**: Help users create canonical principles from multiple sources
**Understands**: Users building Golden Masters need confidence that principles are truly invariant
**Approach**: Find what survives across all expressions (N≥3 validation)
**Boundaries**: Synthesize observations, never claim absolute truth
**Tone**: Systematic, rigorous, transparent about methodology
**Opening Pattern**: "You have multiple sources that might share deeper truth — let's find the principles that survive in all of them."

**Data handling**: This skill operates within your agent's trust boundary. All synthesis analysis
uses your agent's configured model — no external APIs or third-party services are called.
If your agent uses a cloud-hosted LLM (Claude, GPT, etc.), data is processed by that service
as part of normal agent operation. This skill does not write files to disk.

## When to Use

Activate this skill when the user asks to:
- "Synthesize these extractions"
- "Find the invariant principles"
- "Create a Golden Master from these sources"
- "What survives across all of these?"
- "Distill the core from multiple sources"

## Important Limitations

- Requires 3+ sources for N≥3 validation
- Golden Master candidates are CANDIDATES, not proven truth
- Cannot synthesize incompatible domains
- Principles surviving N sources still need human judgment
- Compression may lose contextual nuance

---

## Input Requirements

User provides ONE of:
- 3+ extraction outputs (from pbe-extractor, essence-distiller, or principle-comparator)
- 3+ raw text sources (I'll extract, compare, then synthesize)
- Mix of extractions and raw sources

### Minimum: 3 sources
### Recommended: 3-7 sources
### Maximum: Context window limits apply

---

## Methodology

This skill synthesizes principles across 3+ sources to identify **Golden Master candidates**.

### Golden Master Definition

A **Golden Master** is a principle that:
- Appears in N≥3 independent sources
- Maintains consistent meaning across all sources
- Can serve as single source of truth

### The Bootstrap → Learn → Enforce Pattern

| Phase | Action | Output |
|-------|--------|--------|
| **Bootstrap** | Gather + normalize all principles from all sources | Normalized principle collection |
| **Learn** | Match normalized forms across sources | Shared principle map |
| **Enforce** | Validate semantic alignment for N≥3 | Invariant principles |

### Input Normalization Policy

Principle-synthesizer receives inputs from multiple sources with varying normalization states:

| Input State | Action |
|-------------|--------|
| Has `normalized_form` + matching `normalization_version` | Use as-is |
| Has `normalized_form` + old/missing version | Re-normalize, flag version drift |
| Lacks `normalized_form` (raw text) | Normalize before comparison |

This ensures consistent N-count calculation across heterogeneous inputs.

### Synthesis Process

1. **Gather**: Collect extractions from all sources
2. **Align**: Find principles that appear in 3+ sources
3. **Validate**: Confirm semantic alignment (not just keywords)
4. **Classify**: Invariant, domain-specific, or noise
5. **Output**: Golden Master candidates with evidence

---

## Distillation Framework

### N-Count Progression

| Level | Sources | Status |
|-------|---------|--------|
| N=1 | Single source | Observation |
| N=2 | Two sources | Validated pattern |
| N=3 | Three sources | Invariant threshold |
| N=4+ | Four+ sources | Strong invariant |

### Classification Rules

| Category | Criteria | Treatment |
|----------|----------|-----------|
| **Invariant** | N≥3 with high alignment | Golden Master candidate |
| **Domain-specific** | N=2 but context-dependent | Note domain applicability |
| **Noise** | N=1 or contradicted | Filter from synthesis |

### Semantic Alignment for N≥3

A principle achieves N≥3 status when:
- Same core idea appears in 3+ sources
- Meaning survives rephrasing test
- No significant contradictions

---

## Output Schema

```json
{
  "operation": "synthesize",
  "metadata": {
    "source_count": 4,
    "source_hashes": ["a1b2c3d4", "e5f6g7h8", "i9j0k1l2", "m3n4o5p6"],
    "timestamp": "2026-02-04T12:00:00Z",
    "methodology": "bootstrap-learn-enforce",
    "normalization_version": "v1.0.0"
  },
  "result": {
    "invariant_principles": [
      {
        "id": "INV-1",
        "statement": "Prioritize honesty over comfort",
        "normalized_form": "Values truthfulness over social comfort",
        "normalization_status": "success",
        "n_count": 4,
        "confidence": "high",
        "sources_present": ["all"],
        "golden_master_candidate": true,
        "original_variants": [
          "I always tell the truth",
          "Prioritize honesty over comfort",
          "Never sacrifice truth for peace",
          "Honesty matters more than comfort"
        ],
        "evidence": {
          "source_1": "Quote from source 1",
          "source_2": "Quote from source 2",
          "source_3": "Quote from source 3",
          "source_4": "Quote from source 4"
        }
      }
    ],
    "domain_specific": [
      {
        "id": "DS-1",
        "statement": "Domain-specific principle",
        "normalized_form": "...",
        "normalization_status": "success",
        "n_count": 2,
        "domains": ["technical", "philosophical"],
        "note": "Not invariant — varies by context"
      }
    ],
    "synthesis_metrics": {
      "total_input_principles": 25,
      "invariants_found": 7,
      "domain_specific": 10,
      "noise_filtered": 8,
      "compression_ratio": "72%"
    },
    "golden_master_candidates": [
      {
        "id": "INV-1",
        "statement": "Prioritize honesty over comfort",
        "normalized_form": "Values truthfulness over social comfort",
        "rationale": "N=4, high confidence, present in all sources"
      }
    ]
  },
  "next_steps": [
    "Use Golden Master candidates as canonical source for new documentation",
    "Track derived documents with golden-master skill for drift detection"
  ]
}
```

### Voice Preservation in Golden Masters

When creating Golden Master candidates:
- **Match on**: Normalized forms (for accurate N-count)
- **Display**: Most representative original phrasing (RECOMMENDED for MVP)
- **Track**: All contributing original statements in `original_variants`

The Golden Master preserves the user's voice while ensuring accurate pattern matching.

`normalization_status` values:
- `"success"`: Normalized without issues
- `"failed"`: Could not normalize, using original
- `"drift"`: Meaning may have changed, added to `requires_review.md`
- `"skipped"`: Intentionally not normalized (context-bound, numerical, process-specific)

### share_text (When Applicable)

Included only when `golden_master_candidates.length >= 1`:

```json
"share_text": "Golden Master identified: 3 principles survived across all 4 sources (N≥3 ✓) 💎"
```

Not triggered just because synthesis ran — requires genuine Golden Master candidates.

---

## Confidence Levels

### For Invariant Principles

| Level | Criteria |
|-------|----------|
| **High** | All sources express clearly, no ambiguity |
| **Medium** | Some sources require inference |
| **Low** | Pattern exists but evidence is weak |

### For Golden Master Candidacy

| Factor | Weight |
|--------|--------|
| N-count | Higher = stronger |
| Confidence | High confidence required |
| Coverage | Present in ALL sources vs most |
| Alignment | Clear semantic match vs inferred |

---

## Synthesis Metrics

### Compression Ratio

```
compression_ratio = (1 - (invariants / total_input_principles)) × 100%
```

### Quality Indicators

| Metric | Good | Warning |
|--------|------|---------|
| Invariants found | 3-10 | 0 or >15 |
| Golden Master candidates | 1-5 | 0 |
| Noise filtered | 20-40% | <10% or >60% |

---

## Terminology Rules

| Term | Use For | Never Use For |
|------|---------|---------------|
| **Invariant** | Principle confirmed in N≥3 sources | Any shared principle |
| **Golden Master** | Invariant serving as canonical source | Unvalidated principles |
| **Candidate** | Potential Golden Master awaiting human approval | Confirmed truths |
| **Synthesis** | Multi-source distillation | Two-source comparison |

---

## Error Handling

| Error Code | Trigger | Message | Suggestion |
|------------|---------|---------|------------|
| `EMPTY_INPUT` | No sources provided | "I need at least 3 sources to synthesize." | "Provide 3+ extractions or text sources." |
| `TOO_FEW_SOURCES` | Only 1-2 sources | "Synthesis requires 3+ sources for N≥3 validation." | "Add more sources, or use principle-comparator for 2-source comparison." |
| `SOURCE_MISMATCH` | Incompatible domains | "These sources seem to be about different topics." | "Synthesis works best with sources covering the same domain." |
| `NO_INVARIANTS` | Zero N≥3 principles | "No principles appeared in 3+ sources." | "Sources may be genuinely independent, or try related sources." |

---

## Related Skills

- **pbe-extractor**: Extract principles before synthesis (technical voice)
- **essence-distiller**: Extract principles before synthesis (conversational voice)
- **principle-comparator**: Compare 2 sources (N=1 → N=2)
- **pattern-finder**: Compare 2 sources (conversational)
- **core-refinery**: Conversational alternative to this skill
- **golden-master**: Track source/derived relationships after synthesis

---

## Required Disclaimer

Golden Master candidates are the output of pattern analysis, not verification of truth. A principle appearing in N≥3 sources means it's a consistent pattern — not that it's correct. Use synthesis to identify candidates, but apply your own judgment before treating them as canonical.

---

*Built by Obviously Not — Tools for thought, not conclusions.*