gpd-debug

Name: gpd-debug
Availability: InStock
Author: CharlieGreenman

Diagnoses physics calculation discrepancies by orchestrating parallel subagents to isolate root causes.

1|Updated Mar 29, 2026

Search Tags:#automation #debugging #verification #distributed #physics #root-cause

Ready to run

npx skills add https://github.com/CharlieGreenman/roomtemp-superconductor-gpd --skill gpd-debug

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: gpd-debug
Source: https://github.com/CharlieGreenman/roomtemp-superconductor-gpd/tree/main/.agents/skills/gpd-debug
Command: npx skills add https://github.com/CharlieGreenman/roomtemp-superconductor-gpd --skill gpd-debug

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Debugging complex physics calculations by orchestrating parallel subagents that carry state across context resets, enabling systematic root-cause analysis.

Core Features & Use Cases

Orchestrated diagnostics: coordinate gpd-debugger agents, symptom propagation, and checkpoint handling.
Parallel root-cause discovery: run multiple investigations to identify conflicting hypotheses.
State persistence: maintain context between sessions and across restarts, with debug sessions saved locally.

Quick Start

Describe a new physics debugging scenario with symptoms and instruct the orchestrator to spawn investigators.

Frequently Asked Questions about gpd-debug

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

FAQPage Schema

How do I debug complex physics calculation discrepancies across distributed simulations?▼

Debug complex physics calculation discrepancies by orchestrating parallel subagents that isolate root causes through structured symptom input and evidence-driven diagnosis. This approach coordinates multiple investigations to identify conflicting hypotheses in iterative research workflows.

What is systematic root-cause analysis for divergent numerical pipelines?▼

Systematic root-cause analysis for divergent numerical pipelines involves coordinating parallel subagents that carry state across context resets, enabling structured diagnosis where calculations diverge across simulations, analyses, and numerical pipelines with traceable debug sessions.

How do I start a physics debugging session with persistent context?▼

Start a physics debugging session by describing a new scenario with symptoms and instructing the orchestrator to spawn investigators. The system maintains state between sessions and across restarts, saving debug sessions locally under the .gpd/debug directory.

Can I maintain debugging context across session restarts for iterative research workflows?▼

Yes, state persistence maintains context between sessions and across restarts for iterative research workflows. Debug sessions are saved locally, allowing orchestrated diagnostics to carry state across context resets and resume systematic root-cause analysis.

What's the best way to run parallel root-cause discovery for conflicting physics hypotheses?▼

Run parallel root-cause discovery by orchestrating gpd-debugger agents that execute multiple investigations simultaneously to identify conflicting hypotheses. This coordinated approach handles symptom propagation and checkpoint handling while isolating root causes through evidence-driven diagnosis.

Does physics debugging work without external dependencies for traceable root-cause reporting?▼

Yes, physics debugging operates without external dependencies, using modular agents and traceable debug sessions stored under .gpd/debug. The system provides documented root-cause reporting through evidence-driven diagnosis with structured symptom input and checkpoint handling.