gpd-research-phase

Research and plan a phase within a finite-capacity causal network.

Updated May 1, 2026
One-click install
npx skills add https://github.com/Unified-Field-Theory-Research/finite-capacity-causal-geometry --skill gpd-research-phase-unified-field-theory-research
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: gpd-research-phase
Source: https://github.com/Unified-Field-Theory-Research/finite-capacity-causal-geometry/tree/main/.agents/skills/gpd-research-phase
Command: npx skills add https://github.com/Unified-Field-Theory-Research/finite-capacity-causal-geometry --skill gpd-research-phase-unified-field-theory-research

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires cclab_accel, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill streamlines the process of researching and planning a specific phase within a complex causal network, ensuring thorough investigation and efficient execution.

Core Features & Use Cases

  • Research Phase: Investigate mathematical methods, physical principles, and computational tools for a given phase.
  • Validate Phase: Ensure phase input is correct and gather necessary context.
  • Spawn Researcher: Initiate a subagent to conduct in-depth research and produce a report.
  • Handle Return: Process the researcher's findings, including handling errors and checkpoints.
  • Plan Phase: Transition from research to planning, if applicable.
  • Use Case: For a scientific project with multiple stages, use this Skill to research the initial phase before planning or revisiting research after planning.

Quick Start

Run the 'gpd-research-phase' command with the specific phase number you wish to research.

Frequently Asked Questions about gpd-research-phase

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

FAQPage Schema
How do I research and plan a phase within a causal network?

Researching a phase in a causal network involves validating phase input, gathering context, and spawning a researcher subagent to investigate mathematical methods and physical principles before planning.

What is the process for validating phase input in a finite-capacity causal network?

Validating phase input in a finite-capacity causal network ensures the provided phase number is correct and gathers the necessary context to initiate the subsequent research and planning workflow.

Do I need Rust-based execution to compute mathematical physics phases?

Yes, researching computational tools and mathematical physics phases in this network requires Rust-based execution and specific project configuration to operate correctly.

How to transition from phase research to project planning after gathering findings?

Transitioning from phase research to project planning involves processing the researcher subagent's findings, handling any errors or checkpoints, and then initiating the planning phase if applicable.

Can I use this to investigate computational tools for a specific scientific project phase?

Yes, you can investigate computational tools, mathematical methods, and physical principles for a specific scientific project phase by spawning a researcher to produce an in-depth report.

What are the limitations of using a finite-capacity causal network for phase research?

Limitations include dependency on Rust-based execution, specific project configuration requirements, and the need to handle potential errors and checkpoints when processing researcher findings within the network.