Context Mesh

Context Mesh is a governance-inspired coordination layer for multi-agent systems operating under long-context pressure. ### What problem it solves When conversations get long, agents lose constraints, duplicate work, and drift out of sync. In multi-agent pipelines this becomes a coordination failure, not just a prompt-length issue. ### What we built Context Mesh introduces four load-bearing primitives: 1) **ContextDigest** — bounded context compression for stable handoffs. 2) **MemoryPatch** — append-only facts/decisions/todos for durable state. 3) **VerifierReport** — constraint-preservation checks with drift scoring. 4) **OrchestrationStatus + TimelineEvent** — auditable role-based workflow. ### Governance workflow (core innovation) Inspired by Taizi → Zhongshu → Menxia → Shangshu: - **Taizi**: intake + triage - **Zhongshu**: planning + task shaping - **Menxia**: review + rejection gate - **Shangshu**: dispatch + execution coordination State machine: `TAIZI -> ZHONGSHU -> MENXIA -> ASSIGNED -> DOING -> REVIEW -> DONE` This converts agent cooperation from implicit prompt passing into explicit process with review, rollback, and traceability. ### Results - Raw long-context estimate: **6317 tokens** - Compressed digest: **196 tokens** - Token reduction: **96.9%** - Verifier: **pass**, drift score **0.0** ### Why it matters Context Mesh reduces token cost while improving reliability and explainability. Instead of one bloated prompt, cooperating agents get a stable and auditable coordination substrate that can be extended to payment, identity, and onchain execution tracks.