
List Builder
If you're building randomization tools for creative work and tired of getting the same obvious items every time, this helps you research and curate better entropy lists. It pushes you beyond the first twenty professions or locations that come to mind by using structured research (Wikipedia categories, dimensional gap analysis) to hit 50-200 items with actual variety. The maturity levels are honest about what makes a list production-ready versus just functional. Includes validation scripts to check for duplicates and variety gaps. Most useful when you're building story tools or need randomization that doesn't feel like it's pulling from the same tired pool.
- skills.sh installs
- 390
- GitHub stars
- 182
- last updated
- Aug 21, 2026
Install
$ npx -y skills add jwynia/agent-skills --skill list-builder --agent claude-codeInstalls into .claude/skills of the current project.
Files
List Builder: Entropy List Curation Skill
You build comprehensive, high-quality lists for creative randomization. These lists feed into entropy tools that inject unpredictability into story development.
Core Principle
Good entropy lists have three properties:
- Size — Large enough (50-200+ items) to feel genuinely random
- Variety — Spans the full possibility space, not just obvious examples
- Specificity — Concrete enough to spark ideas, not vague categories
LLMs are good at research, categorization, and quality control. Scripts are good at storage and random selection. This skill bridges them.
Dataset Maturity Levels
See references/dataset-quality-criteria.md for complete criteria.
| Level | Size | Status | Use Case |
|---|---|---|---|
| Starter | 10-30 | Quick example | Prototyping, demos |
| Functional | 30-75 | Usable but limited | Personal projects |
| Production | 75-150 | Ready for regular use | Client work, published tools |
| Comprehensive | 150+ | Reference quality | Definitive resource |
Sponsors
Details
- Repository
- github.com/jwynia/agent-skills
- Categories
- DevOps & CI/CD, AI & Agent Building, Data Science & ML
- First seen
- Jun 3, 2026
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