hcppipeline-tool

Name: hcppipeline-tool
Availability: InStock
Author: CUHK-AIM-Group

Orchestrates HCP-style preprocessing of multimodal MRI data with plan-driven safety checks.

78|3|Updated Mar 25, 2026

Search Tags:#connectivity #preprocessing #pipelines #hcp #diffusion #neuroimaging #fMRI

Ready to run

npx skills add https://github.com/CUHK-AIM-Group/NeuroClaw --skill hcppipeline-tool

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: hcppipeline-tool
Source: https://github.com/CUHK-AIM-Group/NeuroClaw/tree/main/skills/hcppipeline-tool
Command: npx skills add https://github.com/CUHK-AIM-Group/NeuroClaw --skill hcppipeline-tool

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

The HCP Pipelines wrapper provides a safe, plan-driven interface to orchestrate structural, functional, and diffusion preprocessing, reducing setup friction and long, error-prone manual steps.

Core Features & Use Cases

Prerequisite checks: verifies that HCP Pipelines and system dependencies are installed and ready.
Dependency planning: uses a safe plan to install or configure missing resources without surprises.
Input discovery & staging: detects BIDS- or HCP-style inputs and selects appropriate processing stages.
Execution orchestration: generates a clear, numbered command plan and delegates execution to claw-shell for long-running tasks.
Post-run verification: summarizes outputs and suggests next steps, including connective analyses or quality checks.

Quick Start

Prepare your dataset and request a safe, plan-driven HCP Pipelines execution through the wrapper.

Frequently Asked Questions about hcppipeline-tool

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

FAQPage Schema

How do I run HCP Pipelines preprocessing for multimodal MRI data safely?▼

HCP-style preprocessing for fMRI and diffusion MRI requires orchestration that manages prerequisite checks, generates explicit execution plans, and delegates long-running tasks to ensure safe multimodal MRI processing.

What is the best way to orchestrate HCP-style diffusion MRI preprocessing?▼

The best way to orchestrate HCP-style diffusion MRI preprocessing is using a plan-driven interface that provides input discovery, dependency planning, and post-run verification to reduce manual setup friction and errors.

Can I use BIDS-style datasets for HCP Pipelines structural and functional workflows?▼

Yes, you can use BIDS-style datasets for HCP Pipelines structural and functional workflows; the orchestration tool detects BIDS- or HCP-style inputs and automatically selects the appropriate processing stages.

Do I need to manually verify dependencies before starting HCP Pipelines neuroimaging tasks?▼

No, you do not need to manually verify dependencies before starting HCP Pipelines neuroimaging tasks because the wrapper performs automatic prerequisite checks and uses safe dependency planning for missing resources.

What should I do after completing HCP Pipelines fMRI preprocessing?▼

After completing HCP Pipelines fMRI preprocessing, you should review the summarized outputs and perform post-run verification, which suggests next steps like connectivity analyses or quality checks.