Google Proposes SKILL.state to Fix Long-Horizon Agent Context Poisoning
dair_ai · x · 2026-09-01
Google introduces SKILL.state to address efficiency and context poisoning issues in long-horizon agents.
Problem:
- Current agents maintain state by appending every observation, action, and reasoning trace to the conversation history.
- This causes slowdowns and continuous prompt growth, leading to context poisoning.
Solution SKILL.state:
- Replaces the growing history with an explicit mutable execution state.
- The model sees only the immutable skill specification, current structured state, and latest observation at each step.
- Intermediate reasoning is discarded once it produces a validated state update.
Results:
- Improved task accuracy across datasets and environments.
- Reduced cumulative token consumption.
- Architecture-agnostic design allows porting to existing skill runtimes.
Related event: Google's SKILL.state Slashes Agent Session Tokens by 94%(2 posts)→
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