Published January 1, 2026
| Version v2
Preprint
Open
Streamlined Interagent Protocol (Slipstream): Semantic Quantization for Efficient Multi-Agent Coordination
Authors/Creators
Description
As multi-agent LLM systems scale, coordination bandwidth becomes a primary cost driver. This paper introduces Slipstream, a protocol that performs semantic quantization: mapping free-form messages onto a shared Universal Concept Reference (UCR) and transmitting compact mnemonic anchors. Results show 82% token reduction (41.9 → 7.4 tokens average) while maintaining semantic fidelity.
Reference implementation available: pip install slipcore
Files
a2a_slipstream_extension.md
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Additional details
Related works
- Is supplemented by
- Software: 10.5281/zenodo.18063537 (DOI)
- Software: https://github.com/anthony-maio/slipcore (URL)
Software
- Repository URL
- https://www.github.com/anthony-maio/slipcore
- Programming language
- Python
- Development Status
- Active
References
- Reimers, N., & Gurevych, I. (2019). Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. EMNLP-IJCNLP 2019
- Lloyd, S. (1982). Least squares quantization in PCM. IEEE Transactions on Information Theory
- Sculley, D. (2010). Web-scale k-means clustering. WWW 2010
- Linux Foundation. (2025). Agentic AI Foundation Announcement
- Anthropic. (2024). Model Context Protocol Specification