Grounded Checklist Partial Credit for Agent Skill Trajectories
Source
Suliu Qin, Lu Yin, Xilu Wang
Author
Suliu Qin, Lu Yin, Xilu Wang
Date
Terms in this piece · Glossary
AI agent — An AI system that doesn't just answer once but works toward a goal in a loop — taking actions, reading the results, and deciding what to do next.
LLM — A large language model — the neural network behind tools like Claude and ChatGPT, trained on huge amounts of text to predict what comes next.
grounding — Tying a model's answers to checkable sources — retrieved documents, live data, tool results — instead of letting it answer from memory alone.
agent skill — A reusable instruction file that teaches an agent how to do one job well — the procedure, the tools, and what counts as done.
Why it matters
Binary task success hides partial progress and cannot show whether a agent skillA reusable instruction file that teaches an agent how to do one job well — the procedure, the tools, and what counts as done.Full definition → changed how an AI agentAn AI system that doesn't just answer once but works toward a goal in a loop — taking actions, reading the results, and deciding what to do next.Full definition → executed. This gives an evidence-groundingTying a model's answers to checkable sources — retrieved documents, live data, tool results — instead of letting it answer from memory alone.Full definition → partial-credit scheme where humans still author the rubric rules.
articleInducing Reward-Free Judging Rubrics that Reduce Over-Crediting in Agent EvaluationDarragh Quinn, David Dylan, Roisin Healy, Fionn Carroll, Maeve Donnelly, Cormac Sheehan
articleSkillEffect: Checked Lowering for Memory-Bounded Agent ToolsYinuo Wang, Yiyu Shi
articleWhen May an Agent Stop? Evidence-Carrying Termination for Tool-Using LLMsJason Liu