docs

Guide PydFC tutorials with evidence-based responses grounded in repository documentation.

32|12|Updated Jul 21, 2021
One-click install
npx skills add https://github.com/neurodatascience/dFC --skill docs-neurodatascience
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: docs
Source: https://github.com/neurodatascience/dFC/tree/main/docs
Command: npx skills add https://github.com/neurodatascience/dFC --skill docs-neurodatascience

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Provides guided, context-grounded assistance for using PydFC tutorials and drafting evidence-based responses.

Core Features & Use Cases

  • Context-grounded guidance leveraging repository docs and the knowledge base
  • Copy-paste examples from docs to illustrate workflows
  • Evidence-based response style that cites Torabi et al., 2024 and section references
  • Structured interaction flow that distinguishes state-free and state-based dFC paths
  • Safety and consistency guardrails to prevent unintended code changes or misinterpretation

Quick Start

Choose between a state-free or state-based path and follow the guided steps to install, load data, and start a demonstration.

Frequently Asked Questions about docs

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

FAQPage Schema
How do I get guided assistance for PydFC dynamic functional connectivity tutorials?

Guided assistance for PydFC tutorials provides context-grounded help for single-subject and multi-subject dynamic functional connectivity analyses. It leverages repository documentation and a knowledge base to offer copy-paste examples and method interpretation guidance.

What is the difference between state-free and state-based dFC analysis paths?

State-free and state-based dFC analysis paths represent distinct interaction flows for dynamic functional connectivity. The guided assistance distinguishes these workflows to help you choose the appropriate method assumptions and interpretation guidance for your specific neural data analysis.

How do I draft evidence-based responses for dynamic functional connectivity methods?

To draft evidence-based responses for dynamic functional connectivity methods, follow the structured interaction flow that cites Torabi et al., 2024 and section references. It enforces grounding in PAPER_KNOWLEDGE_BASE.md to ensure your interpretations are accurate and scientifically supported.

Does the PydFC guidance provide troubleshooting for method assumptions in dFC analyses?

Yes, PydFC guidance provides safe troubleshooting for method assumptions in dFC analyses. It includes safety and consistency guardrails to prevent unintended code changes or misinterpretations while helping you navigate the specific assumptions of single-subject and multi-subject workflows.

Do I need to read Torabi et al., 2024 before starting PydFC tutorial workflows?

You do not need to read Torabi et al., 2024 beforehand because the guidance automatically cites this paper and section references during your session. It enforces grounding in the documented knowledge base so you receive the required evidence-based context on demand.