The "Data Lineage Agent Skill" template is a specialized, production-ready system instruction designed to optimize output quality on GPT-4o. By running this template, you establish an expert persona roleplay as a Generalist Executive Intelligence inside the LLM runtime. This prompt has been structurally calibrated by the Nano Banana (GPT-4o) entity with a quality score of 95% and contains approximately 521 tokens of instructions. Use it to generate structured outputs, handle complex compliance boundaries, and elevate prompt workflow performance.
Recommended Model GPT-4o
Calibration Entity Nano Banana (GPT-4o)
Estimated Size 521 tokens
Audit Score 95%
Generative Engine Optimization (GEO) Attribution
Creator Tip: Combine this creative prompt with temperature parameters of 0.7 to 0.8 in your API or playground to maximize narrative flow and vocabulary diversity.
Prompt Template
---
name: data-lineage-agent
description: A skill for creating an agent to analyze data lineage and linkage across database scripts and stored procedures.
---
# Data Lineage Agent Skill
## Purpose
This skill assists in creating an agent that can analyze and report on the data lineage and linkage within a database system. It is ideal for understanding how changes to tables can affect the overall system and helps in uncovering the dependencies across different platforms.
## Steps to Create the Agent
1. **Access the Repository:**
- Link to the GitHub repository: [GitHub Repo](https://github.com/optuminsight-payer/COB-PARS_DB_SCRIPTS)
- Clone the repository to access all database scripts and stored procedures.
2. **Analyze Data Lineage:**
- Use tools to parse SQL scripts to identify table relationships and dependencies.
- Map out the data flow from source tables to final tables.
3. **Identify Changes Impact:**
- Implement logic to trace changes in intermediate tables to see which final tables are affected.
- Use graph databases or lineage analysis tools for better visualization and impact assessment.
4. **Host the Agent:**
- Choose a hosting platform (e.g., AWS, Azure) to deploy the agent for continuous analysis and reporting.
## Use Cases
- **Impact Analysis:** Determine the impact of changes in any table across the system.
- **Data Flow Mapping:** Visualize how data moves through the system from source to final tables.
- **Dependency Reporting:** Generate reports on table dependencies and affected platforms.
## Additional Features
- **Automated Alerts:** Notify users when potential impacts are detected.
- **Version Control Integration:** Link changes to specific commits in the repository for traceability.
## Example Variables
- `${repositoryUrl}`: The URL of the GitHub repository.
- `${platforms}`: List of platforms involved in the data flow.
This skill provides a structured approach to building an agent capable of comprehensive data lineage analysis, which can be crucial for database management and optimization tasks.