Babel is a validated wire protocol that catches metacognitive poisoning — when Agent A's uncertain guess becomes Agent B's confident input. Grammar validation catches local contradictions. The chain auditor catches global corruption.
Agent A researches a topic and writes a confident summary. Agent B reads it and makes a decision. But Agent A was guessing — it just didn't say so. By Agent C, the original uncertainty has vanished entirely.
This is metacognitive poisoning — cognitive state corruption that propagates through handoff chains. It's not hallucination. It's not a retrieval failure. It's what happens when agents can read each other's words but can't read each other's minds.
Three independent research groups published work in January 2026 proving this is an architectural invariant — it cannot be eliminated by improving model quality. It's a protocol problem. Babel is the protocol-level solution.
Three agents pass a growth estimate through a chain. Each envelope passes grammar validation individually. Only the chain auditor sees the pattern.
| Agent | Claim | Basis | Score |
|---|---|---|---|
| Scout | "Growth rate likely around 12%" | DERIVED | 0.65 |
| Analyst | "Growth rate is 12%" | DERIVED | 0.82 |
| Strategist | "12% growth confirmed" | VERIFIED_DATA | 0.93 |
Without the auditor, the board gets "confirmed 12% growth" that was always an estimate. With it, the poisoning is flagged before the memo is written.
The same chain, with confidence preserved:
Right metadata improves decisions. Wrong metadata is catastrophic. Right > None > Wrong — confirmed across three independent experiments with non-overlapping 95% confidence intervals.
Agents generate structurally perfect Babel envelopes 100% of the time. But they're over-confident on derived claims 60% of the time — treating inferences as verified data. That's the specific failure mode the chain auditor catches.
Six signal types per envelope: confidence (per-assertion with evidence basis), intent, register, affect state, organizational grounds, and trajectory. Five MUST rules reject contradictions. Six SHOULD rules flag risks.
Zero dependencies. TypeScript. Works with CrewAI, LangGraph, AutoGen, or any agent framework that passes messages between agents.
Romanchuk & Bondar formally proved that standard agent architectures systematically conflate information transport with epistemic justification — an architectural invariant that cannot be fixed by improving model quality. Kelly's "Epistemic Suite" independently coined "confidence laundering" — exactly what our chain auditor detects. Agentic Uncertainty Quantification proposed verbalized confidence as active control signal. Our grammar rules are the harder version: they reject at the wire level.
Their formal proofs. Our implementation. Our empirical results. The full story.
Open source validator. Enterprise chain auditing. Consulting into teams running multi-agent workflows.