// Continual Learning from Experience and Skills // Skills are so good when you combine them properly with MCP & CLIs.
I have found that Skills can significantly improve tool usage of my coding agents.
The best way to improve them is to regularly document improvements, patterns, and things to avoid.
Self-improving skills don't work that well (yet).
Check out this related paper on the topic:
It introduces XSkill, a dual-stream continual learning framework.
Agents distill two types of reusable knowledge from past trajectories: experiences for action-level tool selection, and skills for task-level planning and workflows.
Both are grounded in visual observations.
During accumulation, agents compare successful and failed rollouts via cross-rollout critique to extract high-quality knowledge. During inference, they retrieve and adapt relevant experiences and skills to the current visual context.
Evaluated across five benchmarks with four backbone models, XSkill consistently outperforms baselines. On Gemini-3-Flash, the average success rate jumps from 33.6% to 40.3%. Skills reduce overall tool errors from 29.9% to 16.3%.
Agents that accumulate and reuse knowledge from their own trajectories get better over time without parameter updates.
I have now seen two papers this week with similar ideas.
Paper: arxiv.org/abs/2603.12056
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