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NicktheQuickFTW
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data-querying

Query Supabase schemas to produce reproducible SQL artifacts and results.

Updated Aug 27, 2026
Search Tags:#dashboards#SQL#metrics#Supabase#reproducible#data-querying#internal-data
One-click install
npx skills add https://github.com/NicktheQuickFTW/FlexTime --skill data-querying
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: data-querying
Source: https://github.com/NicktheQuickFTW/FlexTime/tree/main/.factory/skills/data-querying
Command: npx skills add https://github.com/NicktheQuickFTW/FlexTime --skill data-querying

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill enables teams to turn internal data into reliable, reproducible answers by writing structured queries that pull from existing data sources rather than manual exports.

Core Features & Use Cases

  • Reproducible queries: Build precise queries against internal sources to answer well-scoped questions.
  • Source coverage: Works with Supabase-based schemas like competition, scheduling, and analytics to produce metrics, trends, or slices.
  • Artifacts: Generate both the results and a runnable query artifact (SQL, API call, or script) for auditing and reuse.
  • Use Case: A stakeholder asks for season-long team metrics, trends by sport, or snapshot comparisons across periods; this skill delivers a reproducible query and dashboard-ready data.

Quick Start

Draft a precise query spec (business question, time range/filters), select appropriate sources, and save a named, runnable SQL artifact that returns the requested metrics.

Frequently Asked Questions about data-querying

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

FAQPage Schema
How do I query Supabase schemas to extract reproducible internal metrics?▼

To query Supabase schemas for reproducible internal metrics, you translate a business question into a precise query spec, select sources like analytics.team_metrics, and generate a runnable SQL artifact for reuse.

What is the best way to build reproducible SQL queries for dashboard data?▼

Building reproducible SQL queries requires drafting a precise spec with business questions and filters, then saving a named, runnable SQL artifact that returns dashboard-ready data from scheduling or analytics sources.

Can I use this to extract season-long team metrics and trends by sport?▼

Yes, you can extract season-long team metrics and trends by sport by querying the competition.sportlogic_v and analytics.team_metrics schemas to produce snapshot comparisons across periods.

Does querying internal data services require manual exports to compare schedule quality?▼

No, querying internal data services replaces manual exports by directly pulling data slices from scheduling.schedule_quality to answer well-scoped questions and deliver reproducible results.

What formats are supported for the runnable artifact generated from Supabase data queries?▼

The runnable artifact generated from Supabase data queries can be delivered as SQL, an API call, or a script, ensuring the internal data extraction process is fully auditable and reusable.

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