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MorganDevInSA
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ironmind-demo-data

Design and tune IRONMIND demo personas with synthetic weekly physique data.

Updated Aug 27, 2026
Search Tags:#firestore#data-generation#demo-data#seed-data#seed-modules#physique#seed-historical
One-click install
npx skills add https://github.com/MorganDevInSA/ironmind --skill ironmind-demo-data
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: ironmind-demo-data
Source: https://github.com/MorganDevInSA/ironmind/tree/main/.cursor/skills/ironmind-demo-data
Command: npx skills add https://github.com/MorganDevInSA/ironmind --skill ironmind-demo-data

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill provides canonical IRONMIND demo personas, hard-coded weekly physique rows, synthetic multi-week daily history, and coach-import alignment to seed realistic data without breaking Firestore schemas or the seed pipeline.

Core Features & Use Cases

  • Hard-coded weekly physique rows for demo rosters
  • Synthetic multi-week daily history aligned with coach workflows
  • Coach-import alignment and seed orchestration to keep prototypes production-friendly
  • Clear guidance for editing demo-data/physique, demo-historical, and seed modules under src/lib/seed/

Quick Start

Design and tune IRONMIND demo personas, synthetic weekly physique data, and coach-import alignment to seed realistic, production-ready demo athletes.

Frequently Asked Questions about ironmind-demo-data

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

FAQPage Schema
How do I generate realistic demo athlete data for Firestore without breaking the schema?▼

Generate demo athlete data by designing canonical personas and hard-coding weekly physique rows with synthetic multi-week daily history. Seed orchestration enforces type checks and coach-import alignment to maintain Firestore schema integrity.

What is the best way to seed synthetic physique history for prototype applications?▼

Seed synthetic physique history by extending demo-historical modules with multi-week daily records. This aligns with coach workflows and the production seed flow, ensuring prototype data remains production-friendly.

Can I use seed modules to hard-code weekly physique rows for a demo roster?▼

Yes, you can edit seed modules under src/lib/seed/ to hard-code weekly physique rows for demo rosters. The process enforces static profile, program, nutrition, and physique writes via seed orchestration and type checks.

How do I adjust realism for demo personas and synthetic weekly physique data?▼

Adjust realism by tuning demo personas and synthetic weekly physique data within demo-data/physique modules. Seed orchestration and type checks validate the adjusted data against the production seed flow.

Why does my seed pipeline break when adding demo athletes to Firestore?▼

Your seed pipeline may break due to schema misalignment when adding demo athletes. Using seed orchestration with coach-import alignment and type checks enforces static writes, preventing Firestore schema and pipeline breaks.

Do I need specific dependencies to run the seed orchestration for demo data?▼

No specific dependencies are required to run the seed orchestration for demo data. The skill operates independently to enforce static profile, program, nutrition, and physique writes aligned with the production seed flow.

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