菜单
Review AI4S generated data for structure, scientific consistency, and hallucination risk.
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
Designs and builds ETL/ELT data pipelines. Takes data sources, destination, transformation requirements. Generates pipeline code (Python/SQL), scheduling config, error handling, monitoring setup, and data quality checks. Outputs data-pipeline-spec.md + implementation files.
Use MinerU to parse scientific PDFs into structured JSON for AI4S data generation.
Coordinate crawler, parser, synthesizer, and reviewer agents for AI4S data production.
Generate Sci-Evo style AI4S training data from structured paper content.
| name | data-quality-review |
| description | Review AI4S generated data for structure, scientific consistency, and hallucination risk. |
Use this skill when reviewing generated AI4S dataset entries.
Return actionable review notes. When rejecting a sample, explain the concrete reason and the minimum change required to repair it.
