# What is inter-agent misalignment?

Inter-agent misalignment is the failure category where agents miscommunicate, lose context during a handoff, or return results that contradict each other, as distinct from one agent simply getting its own task wrong. The [MAST taxonomy](https://arxiv.org/abs/2503.13657), built from more than 1,600 annotated traces across seven multi-agent frameworks, names it as one of three root-cause categories alongside specification issues and task verification, and it accounts for 36.94 percent of the failures MAST annotated.

The distinction matters operationally. When a downstream agent's score drops, the default move is to fix that agent, and that agent is usually fine. The cause sits at the seam: an earlier agent's prompt changed, or a tool it calls started returning different data, and the output it passed along still reads as valid to anything checking it in isolation. A per-agent grader has no visibility into the handoff itself, so it never sees the seam where the failure actually happened.

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Sources:
- MAST, "Why Do Multi-Agent LLM Systems Fail?" (arXiv:2503.13657): https://arxiv.org/abs/2503.13657 (fetched 2026-08-25)

Source: https://tessary.ai/answers/failure-modes/what-is-inter-agent-misalignment
More on Failure modes: https://tessary.ai/answers/failure-modes
From Tessary, agent reliability for AI agents in production: https://tessary.ai