regulatory-templates-gate1

Map regulatory template placeholders to canonical data sources with snake_case field names.

Updated Aug 27, 2026
One-click install
npx skills add https://github.com/withmartian-sandbox/ghrc-x-3126672651424eddb640ecc81321a665 --skill regulatory-templates-gate1-withmartian-sandbox
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: regulatory-templates-gate1
Source: https://github.com/withmartian-sandbox/ghrc-x-3126672651424eddb640ecc81321a665/tree/main/finops-team/skills/regulatory-templates-gate1
Command: npx skills add https://github.com/withmartian-sandbox/ghrc-x-3126672651424eddb640ecc81321a665 --skill regulatory-templates-gate1-withmartian-sandbox

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Gate 1 provides the foundation for regulatory template accuracy by mapping placeholders from Gate 0 templates to canonical data sources, enforcing snake_case, and requiring interactive validation to prevent misconfigurations.

Core Features & Use Cases

  • Field-to-source mapping with per-field prefixes such as {{ midaz_onboarding.organization.0.legal_document }} and similar
  • Interactive dictionary-backed discovery to produce approved mappings for Gate 2
  • Emphasizes data lineage, consistency, and auditability for regulatory submissions

Quick Start

Map each placeholder to its primary data source using snake_case field names and prepare the Gate 1 mappings for review.

Frequently Asked Questions about regulatory-templates-gate1

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

FAQPage Schema
How do I map regulatory placeholders to canonical data sources for compliant submissions?

Regulatory placeholder mapping connects Gate 0 template fields to canonical data sources using strict snake_case names and data-source prefixes, producing audit-ready field mappings for Gate 1 review. Interactive validation ensures each mapping meets compliance requirements before submission.

What is snake_case field mapping and why is it needed for regulatory templates?

Snake_case field mapping enforces consistent lowercase naming with underscores for regulatory data sources. It ensures data lineage and auditability by applying strict prefixes like midaz_onboarding.organization.0.legal_document to prevent misconfigurations in compliance workflows.

How do I validate regulatory data mappings to ensure they are audit-ready?

Regulatory data mapping validation uses an interactive dictionary-backed discovery process to verify each field mapping. This mechanism applies confidence scoring and requires user validation to produce approved, audit-ready mappings suitable for Gate 2 submissions.

Can I use interactive validation with dictionary lookup for compliance template mapping?

Interactive validation with dictionary lookup is supported for compliance template mapping. The process combines dictionary-backed discovery with user validation and confidence scoring to ensure field-to-source mappings meet regulatory auditability standards.

What's the best way to prepare Gate 1 mappings for regulatory review?

Preparing Gate 1 mappings involves mapping each regulatory placeholder to its primary canonical data source using snake_case field names. This produces field mappings with strict data-source prefixes ready for interactive validation and Gate 2 production.

When do I need strict data-source prefixes for regulatory field mappings?

Strict data-source prefixes are required when mapping regulatory placeholders to ensure data lineage and consistency. Using formats like midaz_onboarding.organization.0.legal_document prevents misconfigurations and maintains auditability for compliant submissions.