S2F-agent: Skill-grounded agent for Sequence-to-Function computational genomics workflows

Sequence-to-Function (S2F) foundation models are revolutionizing genomic research, yet their fragmented ecosystem severely bottlenecks practical application by incompatible inputs, outputs, and runtime environments. General-purpose coding agents lack the strict domain constraints necessary to resolve these biological intricacies safely. Here, we present s2f-agent, a skill-grounded agent orchestration system that translates open-ended genomics queries into reproducible, executable analysis. By integrating canonical input keys, task-specific playbooks, and normalized contracts, s2f-agent unifies workflows across 11 state-of-the-art models, including AlphaGenome, Borzoi, and Evo 2. Validated through rigorous routing and groundedness evaluations, s2f-agent bridges the critical gap between complex model architectures and practical utility, effectively transforming an unwieldy ecosystem into an accessible operational layer for researchers.