ruc-datalab

EvoOntology — Data skill for Claude Code

Data community

EvoOntology: A Self-Evolving Ontology Layer for Data Agents ⚙️ EvoOntology插件为Claude Code/Codex 建立&进化本体层.

How to install EvoOntology

This entry records only its repository, not the path inside it, so there is no exact command to give. Open ruc-datalab/EvoOntology and copy the folder into ~/.claude/skills/, or the file into ~/.claude/agents/.

What EvoOntology does

EvoOntology: A Self-Evolving Ontology Layer for Data Agents ⚙️ EvoOntology插件为Claude Code/Codex 建立&进化本体层.

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README

EvoOntology: A Self-Evolving Ontology Layer for Data Agents

English | 简体中文

**Authors:** [Meiduo Chong](https://github.com/MeiduoChong), [Shaolei Zhang](https://zhangshaolei1998.github.io/)*, [Ju Fan](https://iir.ruc.edu.cn/~fanj/), [Xiaoyong Du](https://info.ruc.edu.cn/jsky/szdw/ajxjgcx/jsjkxyjsx1/js2/7374b0a3f58045fc9543703ccea2eb9c.htm)
Renmin University of China

EvoOntology bridges the **agent-data gap** over heterogeneous tables, files, and databases. It exposes a versioned **Ontology Layer** through MCP tools, grounds that layer in real workload evidence, and continuously adapts it from execution trajectories.

🧭 Why EvoOntology

Raw data leaves semantics implicit. Table names, columns, file paths, and isolated observations rarely explain metric definitions, entity relationships, or business constraints. Agents must infer them repeatedly and are prone to semantic errors.
Static semantic layers do not scale with use. Hand-authored layers require sustained expert maintenance, become stale as data and workloads change, and consume increasing contex