Google WikiSkill: Persistent Wiki Improves Skill-Evolving Agents

rohanpaul_ai · x · 2026-08-29

Google presents WikiSkill, an architecture that improves skill-evolving agents by maintaining a persistent wiki memory.

The Problem: Skill-evolving agents rewrite skill files every round, scattering the reasoning behind edits and losing rejected proposals.

The Solution: WikiSkill splits the agent workspace into three layers:

The wiki records failure patterns and the outcome (accept/reject) of every past proposal. If a skill edit is rejected, it disappears from the active file but remains in the wiki.

Results: On Gemini-3.5-Flash, WikiSkill averaged 68.1% across 5 benchmarks, beating the strongest competing method (56.1%) and the no-skill baseline (49.5%).

Caveat: Skills are handed to the agent rather than retrieved, so skill selection is not part of the evaluation.

Related event: Google's WikiSkill: Small Models Beat Larger Ones via Persistent Knowledge Wikis(9 posts)→

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