GB

gbasin/balls-mode

Developer tools
46 stars Quality 70 Trend 70

Credit: Based on the original concept by @typememetics

Overview

Credit: Based on the original concept by @typememetics Decomposed reasoning with explicit confidence scoring for AI coding assistants. Standard prompting gives you an answer. Balls Mode gives you: - Multiple reasoning paths - Explicit uncertainty - Clear points of failure Copy the skill file to your Codex skills directory: Copy plugins/balls-mode/skills/balls/SKILL.md to your tool's skills directory. 1. - Is this trivial or complex? 2. - Break into verifiable units (balls) 3. - Answer each independently 4. - Assign confidence (0.0-1.0) 5. - Combine with uncertainty tracking - Architectural decisions - Debugging complex issues - Code review concerns - Technology choices - Any question where you want to see the reasoning, not just the answer - "What's 2 + 2?" - "How do I install npm?" - Simple factual questions

README

Balls Mode

Credit: Based on the original concept by @typememetics

Decomposed reasoning with explicit confidence scoring for AI coding assistants.

What is this?

Standard prompting gives you an answer. Balls Mode gives you:

  • Multiple reasoning paths
  • Explicit uncertainty
  • Clear points of failure

Installation

Claude Code

/plugin marketplace add gbasin/balls-mode
/plugin install balls-mode

Codex

Copy the skill file to your Codex skills directory:

mkdir -p ~/.codex/skills/balls-mode
cp plugins/balls-mode/skills/balls/SKILL.md ~/.codex/skills/balls-mode/

Manual

Copy plugins/balls-mode/skills/balls/SKILL.md to your tool’s skills directory.

Usage

/balls Should I rewrite this service in Go?

The Protocol

  1. CLASSIFY - Is this trivial or complex?
  2. DECOMPOSE - Break into verifiable units (balls)
  3. SOLVE & VERIFY - Answer each independently
  4. SCORE - Assign confidence (0.0-1.0)
  5. SYNTHESIZE - Combine with uncertainty tracking

Example Output

## Decomposition

| # | Ball | Why it matters |
|---|------|----------------|
| 1 | What's the current pain point? | Determines if rewrite addresses real issue |
| 2 | Team's Go experience? | Affects timeline and quality |
| 3 | Service complexity? | Rewrite effort estimation |

## Analysis

| Ball | Answer | Confidence | Notes |
|------|--------|------------|-------|
| Current pain point | Memory usage in Python | 0.7 | Based on user context |
| Team Go experience | Unknown | 0.2 | Need to ask |
| Service complexity | ~5k LOC, moderate | 0.8 | Reviewed codebase |

## Synthesis

**Answer**: Possibly worth it if the team has Go experience. Memory improvements would be significant.

**Overall Confidence**: 0.45

**Weakest Link**: Team experience unknown - this determines feasibility.

**To increase confidence**: Clarify team's Go background.

When to Use

  • Architectural decisions
  • Debugging complex issues
  • Code review concerns
  • Technology choices
  • Any question where you want to see the reasoning, not just the answer

When NOT to Use

  • “What’s 2 + 2?”
  • “How do I install npm?”
  • Simple factual questions

Confidence Score Guide

Score Meaning
0.9-1.0 Verifiable fact or logical certainty
0.7-0.89 Strong evidence, established patterns
0.5-0.69 Reasonable inference, some uncertainty
0.3-0.49 Educated guess, significant unknowns
0.0-0.29 Speculation, insufficient information

Philosophy

“What if a system could check its own work from multiple angles before giving you an answer? Not just ‘think step by step.’ Actually decompose. Actually verify. Actually flag uncertainty.”

License

MIT

View this README on GitHub

Recommended Tools

Try a different keyword or remove a filter.

Install

npx skillfish add gbasin/balls-mode