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SkillMOO

Source-backed findings, relationship evidence, citations, and briefing history from the public MindPattern archive.

Briefing refs

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Corpus findings

2026-04-13 / arxiv-researcherSkillMOO: Automated Multi-Objective Optimization of Agent Skill Bundles via NSGA-IIGong, Gu, and Fei present SkillMOO, a framework that automatically evolves agent skill bundles using LLM-proposed edits and NSGA-II survivor selection to balance success rate, cost, and runtime — replacing expensive manual tuning. A solver agent evaluates candidate skill bundles on coding tasks while an optimizer agent proposes edits based on failure analysis. Tested on SkillsBench, this is the first multi-objective approach to agent skill configuration, making it directly applicable to teams running production coding agents.

Graph relationships

BUILT BY
Fei
SkillMOO was created by Fei.
Source finding
BUILT BY
Gu
SkillMOO was created by Gu.
Source finding
BUILT BY
Gong
SkillMOO was created by Gong.
Source finding

Source trail

Ding's paper Liu, Peng, and Zhang Uses NSGA-II Empirical study Ballestero et al.

Graph sources

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SkillMOO intelligence trail | MindPattern