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, 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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Are most agent errors caused by the agent's own logic?No. In Datadog's 2026 report, 5% of LLM call spans errored in February 2026, and 60% of those were exceeded rate limits, not the agent's reasoning.answer →Can content an agent retrieves override its own instructions?Yes. Text inside a webpage, document, or tool result an agent reads can contain instructions the model follows, a failure called indirect prompt injection.answer →How do multi-agent systems actually fail?Across three root causes: 41.77% specification issues, 36.94% inter-agent misalignment, and 21.30% task verification failures, per the MAST taxonomy's 1,600+ annotated traces.answer →Everything on failure modesThe definition, and every question answered under failure modes.concept →

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