Long Live the Librarian! A Persistent Search Sub-Agent for Energy-Efficient Multi-Agent Software Engineering Systems

Fuente: arXiv
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Main Authors: Cho, Seunghyuk, Choi, Sunghyun, Heo, Jaeseung, Choi, Youngbin, Moon, Saemi, Park, MoonJeong, Kim, Dongwoo
Format: Preprint
Published: 2026
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_version_ 1866913166218231808
author Cho, Seunghyuk
Choi, Sunghyun
Heo, Jaeseung
Choi, Youngbin
Moon, Saemi
Park, MoonJeong
Kim, Dongwoo
author_facet Cho, Seunghyuk
Choi, Sunghyun
Heo, Jaeseung
Choi, Youngbin
Moon, Saemi
Park, MoonJeong
Kim, Dongwoo
contents Multi-agent systems (MAS) have substantially advanced autonomous software engineering (SWE), but their growing inference energy demands raise sustainability concerns. In this paper, we demonstrate that this cost is concentrated in an overlooked source: redundant output tokens generated across agents. Two empirical findings ground this claim. First, our per-token energy attribution for MAS reveals a sharp asymmetry: an output token consumes 30 to 1,000 times more energy than an input or cached token. Second, MAS inflate per-episode output because agents repeatedly re-explore overlapping repository regions. To address this inefficiency, we propose Librarian, a persistent search sub-agent that tracks repository-search history and suppresses redundant exploration actions across agents. By returning short references to file regions instead of full file excerpts, Librarian further reduces output-token volume. On SWE-Bench Verified, Librarian reduces per-episode GPU energy consumption of existing multi-agent SWE systems by up to 25% while preserving task performance.
format Preprint
id arxiv_https___arxiv_org_abs_2605_27787
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Long Live the Librarian! A Persistent Search Sub-Agent for Energy-Efficient Multi-Agent Software Engineering Systems
Cho, Seunghyuk
Choi, Sunghyun
Heo, Jaeseung
Choi, Youngbin
Moon, Saemi
Park, MoonJeong
Kim, Dongwoo
Multiagent Systems
Computation and Language
Multi-agent systems (MAS) have substantially advanced autonomous software engineering (SWE), but their growing inference energy demands raise sustainability concerns. In this paper, we demonstrate that this cost is concentrated in an overlooked source: redundant output tokens generated across agents. Two empirical findings ground this claim. First, our per-token energy attribution for MAS reveals a sharp asymmetry: an output token consumes 30 to 1,000 times more energy than an input or cached token. Second, MAS inflate per-episode output because agents repeatedly re-explore overlapping repository regions. To address this inefficiency, we propose Librarian, a persistent search sub-agent that tracks repository-search history and suppresses redundant exploration actions across agents. By returning short references to file regions instead of full file excerpts, Librarian further reduces output-token volume. On SWE-Bench Verified, Librarian reduces per-episode GPU energy consumption of existing multi-agent SWE systems by up to 25% while preserving task performance.
title Long Live the Librarian! A Persistent Search Sub-Agent for Energy-Efficient Multi-Agent Software Engineering Systems
topic Multiagent Systems
Computation and Language
url https://arxiv.org/abs/2605.27787