pony-debug

Diagnose non-trivial issues with checkpoint artifacts and hypothesis-driven experiments.

6|Updated Mar 9, 2026
One-click install
npx skills add https://github.com/ponylang/llm-skills --skill pony-debug
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: pony-debug
Source: https://github.com/ponylang/llm-skills/tree/main/pony-debug
Command: npx skills add https://github.com/ponylang/llm-skills --skill pony-debug

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Establishes a formal, artifact-driven approach to debugging that prevents guessing and anchors conclusions in observable evidence.

Core Features & Use Cases

  • Checkpoint-based investigation provides a clear, repeatable path through debugging steps with explicit artifacts at each stage.
  • Hypothesis-driven analysis guides what to test, document, and confirm, enabling collaboration and faster root-cause identification.
  • Reproducible debugging workflows help teams verify fixes by sharing artifacts, steps, and observations.

Quick Start

Start by characterizing the failure and creating a written artifact for Checkpoint 1.

Frequently Asked Questions about pony-debug

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

FAQPage Schema
How do I debug intermittent failures requiring reproducible evidence?

Debug intermittent failures by applying a structured, artifact-driven protocol that enforces checkpoint artifacts and hypothesis-driven experiments to establish reproducible evidence before fixes.

What is the best way to find the root cause of complex code path failures?

Find root causes using hypothesis-driven analysis that guides what to test, document, and confirm, enabling collaboration and iterative investigation through complex code paths.

How do I start a structured investigation for a non-trivial software issue?

Start a structured investigation by characterizing the failure and creating a written artifact for Checkpoint 1 to anchor conclusions in observable evidence.

Can I use a formal debugging protocol for team collaboration on root-cause analysis?

Use a formal debugging protocol for team collaboration by sharing checkpoint artifacts, steps, and observations to verify fixes and guide collective root-cause identification.

Why should I use checkpoint-based debugging instead of guessing fixes?

Use checkpoint-based debugging to prevent guessing and anchor conclusions in observable evidence, providing a clear, repeatable path through debugging steps with explicit artifacts at each stage.