It's more-so recursive decomposition rather than clustering failures or stream summarizing. You can look at this repo if you want to learn more about how RLM's work: https://github.com/alexzhang13/rlm
Yeah, fair question. For a small number of traces just dumping them into Claude Code can work well.
However, once you're at production scale the problem changes. You can't always fit 10,000+ traces in Claude Code and still have it be effective especially when the relevant pattern of agent failures may only become apparent when you pass that many in. That's where the RLM based methodology helps. HALO recursively decomposes the trace data into smaller investigations, analyzes those sub-pieces, and then synthesizes those up to determine the recurring harness-level failure modes better than Claude Code or Codex ever could at a large scale.