gpd-quick

Execute single-step research tasks with atomic commits and STATE.md tracking.

1|Updated Mar 29, 2026
One-click install
npx skills add https://github.com/CharlieGreenman/roomtemp-superconductor-gpd --skill gpd-quick
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: gpd-quick
Source: https://github.com/CharlieGreenman/roomtemp-superconductor-gpd/tree/main/.agents/skills/gpd-quick
Command: npx skills add https://github.com/CharlieGreenman/roomtemp-superconductor-gpd --skill gpd-quick

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Automates fast, ad-hoc research tasks with guaranteed atomic commits and durable state tracking, reducing manual coordination in experimental workflows.

Core Features & Use Cases

  • Atomic planning and execution for single-step tasks
  • Stateful tracking via STATE.md updates and commit history
  • Skip optional agents for fast, targeted tasks

Quick Start

Provide a concise quick-task description (e.g., 'estimate the tunneling rate for a given potential') and I will execute it with GPD guarantees.

Frequently Asked Questions about gpd-quick

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

FAQPage Schema
How do I automate quick research tasks with atomic commits?

To automate quick research tasks with atomic commits, provide a concise task description like a dimensional check. The system initializes quick task state, spawns planner and executor agents, and outputs a summary with a durable commit.

What is state tracking for ad-hoc research workflows?

State tracking for ad-hoc research workflows is the process of recording task progress via STATE.md updates and commit history. It ensures durable state persistence for single-step experimental tasks, reducing manual coordination between planning and execution phases.

Does GPD support rapid literature lookups within a constrained time window?

Yes, GPD supports rapid literature lookups within a constrained time window by targeting single-step ad-hoc tasks. It skips optional agents to execute fast, targeted research queries while maintaining durable state tracking and atomic commit guarantees.

What is the best way to execute single-step derivations with durable state tracking?

The best way to execute single-step derivations with durable state tracking is using an automated planning and execution flow. This approach skips optional agents for fast, targeted task completion while guaranteeing atomic commits and STATE.md updates.

When should I not use atomic commits for experimental workflows?

You should not use atomic commits for experimental workflows requiring multi-step or complex iterative research outside a constrained time window. This approach targets single-step, quick tasks like rapid dimensional checks rather than extensive, multi-phase experimental coordination.