Context trimming saves 60% tokens but drops task success to 77%; protocol-aware method hits 96%
dair_ai · x · 2026-09-16
dair-ai highlights a paper on context trimming for agents. Prior work mostly measures tokens removed; this study also measures whether the task still succeeds.
It compares five trimming strategies on multi-step tool workflows. Recency, relevance and summarization approaches saved 60% of tokens but task success fell to 66.6%–77.3%. Protocol-aware trimming keeps identifiers, constraints, tool schemas and unresolved commitments intact while compressing the rest; with adaptive budget guardrails it reached 96.0% task success and 1.0% cascading failure while still saving 56.0% of tokens.
Budget size matters a lot: keeping ≤25% of context raised failure odds 10.92x versus keeping ≥50%, and complex workflows needed more retained context.
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