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MidasToolstoday at 10:06 AM1 replyview on HN

Running a solo dev business on top of multi-agent Claude Code workflows (OpenClaw stack) -- the cascading context drift problem is real and the state partitioning approach in this thread is the right instinct.

The failure mode that bit us hardest: agents sharing a single context window where early tool outputs pollute later reasoning. Fixed it by treating each agent turn as append-only -- worker writes output to a structured log, reviewer reads only that log (not the raw conversation history). Isolated drift. Night and day.

The confidence score idea is underutilized. We log tool call outcomes as: {action, result, confidence: 0-3}. The reviewer agent pattern-matches on low-confidence streaks before they compound into something unfixable.

On the multi-model review question from another commenter: different models catch different failure types. Claude catches logical inconsistencies; a smaller/faster model catches format errors and incomplete outputs. Cheap pre-check before the expensive reviewer saves a lot of token burn.

What's your retry strategy when the reviewer blocks -- exponential backoff on the same worker context, or fresh context each retry? We do fresh context after 2 failures.


Replies

unoheetoday at 10:39 AM

OpenSwarm isolates context at the agent level — each worker is spawned via Claude Code’s -p flag, so there’s no shared conversation history between agents. The only shared state is written artifacts and a global work memory layer (CLAUDE.md + structured output). Each instance treats that as its single source of truth, rather than reading other agents’ raw context. One thing I’m actively formalizing: a CONFIDENCE-HALT mechanism. Currently it lives as a defined concept in CLAUDE.md, but the next revision will have OpenSwarm inject it explicitly into each worker context — so low-confidence streaks trigger a halt before they compound. Your {action, result, confidence: 0-3} logging pattern is basically the same instinct. Still early, but converging fast. Curious how you handle the structured log schema — do you version it across runs?