data-standards

Enforce canonical enums and classifications across backend and frontend data displays.

2|1|Updated Dec 15, 2025
One-click install
npx skills add https://github.com/sgpropertyanalytics/sg-property-analytics --skill data-standards
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: data-standards
Source: https://github.com/sgpropertyanalytics/sg-property-analytics/tree/main/.claude/skills/data-standards
Command: npx skills add https://github.com/sgpropertyanalytics/sg-property-analytics --skill data-standards

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Data classification, naming standards, and enum integrity guardrail to prevent taxonomy drift, hardcoding, and inconsistent labelling across backend and frontend.

Core Features & Use Cases

  • Single Source of Truth: centralizes classifications in backend (contract_schema) and frontend constants, preventing divergence.
  • Enum Integrity: enforces canonical bucket keys for regions, bedrooms, floor levels, sale types, tenures, and age bands.
  • Guardrails & Validation: provides automated checks and tests to ensure adherence before UI/chart creation.
  • Use Case: when introducing a new region or age band, update canonical enums in one place and propagate safely to all layers.

Quick Start

Activate the data-standards guardrail before creating any new chart, filter, or data display to enforce canonical enums.

Frequently Asked Questions about data-standards

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

FAQPage Schema
How do I prevent enum drift between backend and frontend data classifications?▼

To prevent enum drift, enforce canonical data classifications by centralizing enums in backend contract_schema.py and synchronizing frontend constants. Guardrails reject hardcoded strings during development and data rendering, ensuring taxonomy consistency across layers.

How do I enforce canonical enums for property categories like age bands and sale types?▼

Enforce canonical enums for property categories by applying guardrails that check backend contract_schema.py and frontend constants. This ensures consistent bucket keys for regions, bedrooms, floor levels, sale types, tenures, and age bands across all layers.

What is the best way to safely introduce a new region or age band across projects?▼

The best way to safely introduce a new region or age band is to update canonical enums in one place within backend contract_schema.py and propagate the synchronized frontend constants safely to all layers.

When should I activate data classification guardrails during UI or reporting development?▼

Activate data classification guardrails before creating any new chart, filter, or data display. This enforces canonical enums and prevents ad-hoc categories from entering backend and frontend data rendering workflows.

Why do my frontend data displays show inconsistent labels for tenures and floor levels?▼

Frontend data displays show inconsistent labels when hardcoded strings or ad-hoc categories bypass canonical enums. Enforcing synchronized frontend constants with backend contract_schema.py rejects this drift and ensures consistent labelling.

Can I use automated checks to validate taxonomy standards before chart creation?▼

Yes, you can use automated guardrails and validation checks to ensure adherence to taxonomy standards before UI or chart creation. These tests reject hardcoded strings and verify canonical bucket keys.