# Break It Down, Pass It On: Cross-Task Skill Transfer in LLM Agents

Source: [arXiv](https://arxiv.org/abs/2608.20274v1)  
Feed7 permalink: https://feed7.dev/p/break-it-down-pass-it-on-cross-task-skill-transfer-in-ll-990ea76696  
Published: 2026-08-20T00:00:00.000Z  
Trust: Needs Review (needs_review)

## Why Included

Store small textual procedures, because subtask-level skills transferred better while whole-task skills often hurt performance.

## Source Summary

Reusable agent skills transferred better when induced from subtasks and stored as text. Whole-task skills often hurt versus no memory, so retrieval alone is not evidence that a memory helps.

## Practical Implication

Build agent memory from small, reusable procedures and prefer textual guidance unless execution requires code. Before retrieval, score candidates for both task specificity and breadth of relevance rather than assuming any prior solution will help.

## Agent-Ready Context

The study compares task-level against subtask-level skill induction and text against code formats. **Task-level skills often fell below the no-memory baseline**, while **subtask-level skills improved performance on average**; text transferred better than code.

Build agent memory from small, reusable procedures and prefer textual guidance unless execution requires code. Before retrieval, score candidates for both task specificity and breadth of relevance rather than assuming any prior solution will help.

Neither specificity nor abstractness predicted outcomes alone. Their combined **skill utility score** correlated with transfer performance and requires only skills plus task descriptions, but the supplied material gives no tasks, models, or effect sizes for judging generality.

## Context Map

- Layer: agent
- Domains: None
- Topics: skills, agent-memory, agent-reliability

## Uncertainty

- Automatically selected from source material; feed7 has not independently tested the claim.

## Agent Instruction

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