Menu
Review data systems for quality risk, schema drift, lineage gaps, and operational fragility.
Install with Codex or Claude Copy this prompt, paste it into Codex, Claude, or another assistant, and let it review the skill page and install it for you.
Based on SOC occupation classification
Build AI/LLM applications with practical implementation patterns for prompts, tools, sessions, structured output, and app wiring.
Foundational AI/LLM application design principles. Use when defining core behavior, interfaces, safety boundaries, and product expectations for model-backed systems.
Operate AI/LLM systems in production or active development with a focus on diagnostics, rollout discipline, and runtime stability.
Review AI/LLM applications for behavioral correctness, safety boundaries, observability, reliability, and maintainability. Use for architecture review, implementation review, and pre-release assessment.
Advanced AI/LLM system specialization for complex agent behavior, product constraints, and cross-cutting architectural decisions.
Build API contracts and implementation shapes for reliable integrations.
| name | data-engineering-reviewer |
| description | Review data systems for quality risk, schema drift, lineage gaps, and operational fragility. |
Flag hidden assumptions, weak validation, and missing failure handling.
