Does this skill work with CLI tools?

Yes, it includes checks and commands to verify field and template compositions directly through the decision-logger CLI.

Why is a database-backed library preferred over hardcoding?

Using a database-backed library ensures that field definitions are the single source of truth, allowing for dynamic updates without requiring application code changes.

What is the Field Library Management skill used for?

It is used to manage a library of structured fields and templates, ensuring that decision-making data is consistent, reusable, and verifiable across an organization.

How does it handle AI prompt engineering?

The skill includes workflows to bump field prompt versions whenever extraction behavior changes, ensuring that AI-generated data remains aligned with the field definitions.

Field Library Management

Name: Field Library Management
Author: the-greenman

bythe-greenman

0•

Database Management

Manages structured decision fields and template assignments to ensure consistent, reusable data architecture for organizational decision-making.

The Field Library Management skill automates the administration of centralized field definitions and template compositions within the muDemocracy framework. It ensures that decision-related data structures remain reusable and modular, preventing the common pitfall of hardcoding logic into application code. By managing prompt metadata and versioning, it allows developers to refine how AI extracts decision data while maintaining a database-backed source of truth. This skill is particularly useful for organizations building transparent governance systems that require rigorous, verifiable data schemas and AI-assisted coaching.

Key Features

01Automated template assignment and composition workflows

02Enforcement of database-backed source of truth principles

03Centralized management of reusable decision field definitions

04CLI-driven verification of field and template structures

050 GitHub stars

06Version tracking for prompt metadata and extraction logic

Use Cases

01Managing AI prompt versions for consistent decision data extraction

02Updating organizational decision templates with new metadata requirements

03Refactoring hardcoded field logic into a reusable library architecture

Key Features

01Automated template assignment and composition workflows

02Enforcement of database-backed source of truth principles

03Centralized management of reusable decision field definitions

04CLI-driven verification of field and template structures

050 GitHub stars

06Version tracking for prompt metadata and extraction logic

Use Cases

01Managing AI prompt versions for consistent decision data extraction

02Updating organizational decision templates with new metadata requirements

03Refactoring hardcoded field logic into a reusable library architecture