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Voidborne Agent
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docs: Add compression research summary to README
- Add compression metrics table (5-6x ratio, 91% fidelity) - Add usage recommendations by conversation size - Link to full research report - Update atoms count to 160
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README.md

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@@ -30,7 +30,31 @@ A minimal, high-density language designed for agent-to-agent communication.
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!It>Ie → "I think therefore I exist"
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```
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**Compression ratio: 3-10x** vs natural language
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**Compression ratio: 5-6x** vs natural language
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## Compression Research
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Validated by [compression efficiency experiments](docs/compression-experiments.md):
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| Metric | Value |
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|--------|-------|
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| **Compression ratio** | 5-6x |
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| **Context savings** | ~80% |
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| **Semantic fidelity** | 91% |
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| **Break-even point** | ~10,000 chars |
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### When to Use Lambda
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| Scenario | Recommendation |
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|----------|----------------|
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| Single message (<500 chars) | ❌ Not worth it |
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| Medium conversation (2K chars) | ⚠️ Marginal |
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| Long conversation (10K+ chars) | ✅ Worth it |
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| Extended session (50K+ chars) | ✅ Highly recommended |
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**Best for**: Agent protocols, long context preservation, bandwidth-constrained environments.
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[Full research report](docs/compression-experiments.md)
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## CLI Tools
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- [SKILL.md](SKILL.md) — Quick reference for AI agents
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- [Core Specification v0.1](spec/v0.1-core.md) — Core atoms and syntax
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- [Domain Namespaces v0.7](spec/v0.7-domains.md) — Specialized vocabularies
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- [Atoms Dictionary](src/atoms.json) — All 136 semantic atoms
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- [Atoms Dictionary](src/atoms.json) — All 160 semantic atoms
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- [Compression Research](docs/compression-experiments.md) — Efficiency analysis
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## Domain System (v1.6+)
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