internal-data-querying

Translate business questions into reproducible SQL, API calls, or notebooks with audit trails.

Updated Aug 23, 2026

Search Tags:#SQL #query #data warehouse #reproducible #auditable #internal data #analytics API

Ready to run

npx skills add https://github.com/NicktheQuickFTW/FlexTime --skill internal-data-querying

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: internal-data-querying
Source: https://github.com/NicktheQuickFTW/FlexTime/tree/main/.claude/skills/internal-data-querying
Command: npx skills add https://github.com/NicktheQuickFTW/FlexTime --skill internal-data-querying

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Safely query internal data services to produce shareable, reproducible artifacts for questions derived from warehouses, marts, or reporting APIs, with audit trails.

Core Features & Use Cases

Reproducible queries against internal data systems (warehouses, marts, analytics APIs)
Generates artifacts: SQL, API calls, notebooks, dashboards, with clear audit trails
Governed access and data sensitivity aware results, saved in approved locations
Use Case: Respond to stakeholder questions with scoped data slices and documented methodology

Quick Start

Use this skill to translate a business question into a reproducible data query, save the query and results to the approved repository, and attach an analysis summary.

Frequently Asked Questions about internal-data-querying

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I translate a business question into a reproducible data query?▼

To translate a business question into a data query, you map the request to internal data sources like warehouses or reporting APIs, generating a runnable query artifact with an analysis summary and audit trail.

How do I generate auditable SQL or API artifacts for internal data warehouses?▼

Generating auditable query artifacts involves producing runnable SQL, API calls, or notebooks against data marts, which are then saved with governance notes on data sensitivity and documented methodology for reproducibility.

Can I use this to query analytics APIs and data marts for scoped metric slices?▼

Yes, you can query analytics APIs and data marts to extract scoped metric slices and trends, ensuring governed access and producing shareable, reproducible artifacts with clear audit trails for stakeholders.

What is the best way to ensure reproducible internal data queries with governance notes?▼

The best way to ensure reproducible internal data queries is to save the runnable query and results to an approved repository, attaching a concise analysis summary and data sensitivity governance notes.

Does this approach work with both SQL data warehouses and reporting APIs?▼

Yes, this approach works with SQL data warehouses, data marts, and reporting APIs, translating business questions into precise queries while applying governed access and producing auditable artifacts.

When should I not use reproducible query artifacts for stakeholder reporting?▼

You should avoid using reproducible query artifacts when dealing with data sources outside internal warehouses or reporting APIs, or when your reporting context cannot support governed access and data sensitivity audit trails.