القائمة
Review AI4S generated data for structure, scientific consistency, and hallucination risk.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
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.
