cs.AIMar 18, 2026

Don't Vibe Code, Do Skele-Code: Interactive No-Code Notebooks for Subject Matter Experts to Build Lower-Cost Agentic Workflows

Authors: Sriram Gopalakrishnan

Organizations: JP Morgan Chase & Co. AI Research

Abstract

Skele-Code is a natural-language and graph-based interface for building workflows with AI agents, designed especially for less or non-technical users. It supports incremental, interactive notebook-style development, and each step is converted to code with a required set of functions and behavior to enable incremental building of workflows. Agents are invoked only for code generation and error recovery, not orchestration or task execution. This agent-supported, but code-first approach to workflows, along with the context-engineering used in Skele-Code, can help reduce token costs compared to the multi-agent system approach to executing workflows. Skele-Code produces modular, easily extensible, and shareable workflows. The generated workflows can also be used as skills by agents, or as steps in other workflows.

Figures & tables

Appendix figures & tables2 assets

Supplementary material from the paper’s appendix.

Appendix

Explore similar work

CardsList
  1. Skill-as-Pseudocode: Refactoring Skill Libraries to Pseudocode for LLM Agents

    May 27, 2026Xinze Li, Yuhang Zang, Yixin Cao +1Tool-Augmented Language Model AgentsLLM Agent Skill Retrieval