data-organizer

Organize freeform data in a JSONB entity store with schemas and workflows.

Updated Feb 9, 2026
One-click install
npx skills add https://github.com/Tzeusy/butlers --skill data-organizer
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: data-organizer
Source: https://github.com/Tzeusy/butlers/tree/main/roster/general/.agents/skills/data-organizer
Command: npx skills add https://github.com/Tzeusy/butlers --skill data-organizer

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill provides structured patterns and workflows to organize arbitrary data within the General butler's freeform entity store, ensuring consistency and facilitating efficient querying.

Core Features & Use Cases

  • Collection Design: Establishes naming conventions for organizing entities by domain, type, or status.
  • Entity Schema Templates: Offers pre-defined JSON structures for common data types like Projects, Bookmarks, Notes, Lists, Recipes, and Contacts.
  • Data Hygiene Workflows: Includes practical scripts for deduplication, archiving stale data, normalizing tags, and validating schemas.
  • Query Patterns: Demonstrates effective JSONB querying techniques for efficient data retrieval.
  • Use Case: You need to store and manage a growing list of research papers. This Skill helps you define a research-paper collection, provides a schema for storing metadata like title, authors, and abstract, and offers workflows to keep your collection clean and searchable.

Quick Start

Use the data-organizer skill to set up a new collection for tracking personal projects.

Frequently Asked Questions about data-organizer

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

FAQPage Schema
How do I organize freeform data in a JSONB entity store?

To organize freeform data in a JSONB entity store, you need structured patterns and naming conventions. This approach uses pre-defined schema templates for common types like projects and notes, ensuring consistency and facilitating efficient querying using JSONB containment operators.

What is the best way to structure JSONB schemas for projects and contacts?

The best way to structure JSONB schemas for projects and contacts is using pre-defined entity templates. These templates standardize metadata fields, which streamlines collection management and makes your data easier to search and maintain.

How do I perform data hygiene and deduplication on a JSONB collection?

Data hygiene and deduplication on a JSONB collection require specific workflows that normalize tags and archive stale data. By validating entities against schema templates, you can identify duplicate records and maintain a clean, efficient data store.

Can I use JSONB containment operators for querying unstructured data?

Yes, you can use JSONB containment operators for querying unstructured data effectively. When your entities follow a structured schema template, containment operators allow rapid retrieval of nested metadata without scanning entire documents.

Does this data organization approach work for managing research papers and bookmarks?

Yes, this data organization approach works for managing research papers and bookmarks by defining a dedicated collection. It provides schema templates for storing metadata like title and authors, alongside workflows to keep the collection clean and searchable.