skills.rest
nebius
nebiusOFFICIAL
Explore all skills by this author →
WebsiteGitHub

real-components

Audit NPA workbench pipeline toolRef argv configurations against stub patterns.

17|8|Updated Apr 7, 2026
Search Tags:#automation#validation#orchestration#pipeline#quality-assurance#workbench
One-click install
npx skills add https://github.com/nebius/nebius-physical-ai --skill real-components
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: real-components
Source: https://github.com/nebius/nebius-physical-ai/tree/main/skills/atomic/real-components
Command: npx skills add https://github.com/nebius/nebius-physical-ai --skill real-components

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill prevents the deployment of pipeline blueprints that use stubbed or placeholder components, ensuring that every advertised stage in an NPA workbench pipeline performs actual work rather than echoing dummy data.

Core Features & Use Cases

  • Component Validation: Automatically audits tool references to distinguish between real operational modules and demo stubs.
  • Pipeline Integrity: Ensures that downstream stages receive valid, real-world artifacts like processed video or verified reports instead of manifest placeholders.
  • Use Case: When building a robotics data pipeline, use this skill to verify that your Cosmos Transfer and FiftyOne curation stages are invoking the actual GPU-accelerated execution modules rather than echo-based stubs.

Quick Start

Run the real-components audit on your current workbench pipeline configuration to identify and replace any stubbed tool references with their production-ready counterparts.

Frequently Asked Questions about real-components

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

FAQPage Schema
How do I validate tool references in my NPA workbench pipeline?▼

To validate tool references in an NPA workbench pipeline, run an audit that inspects toolRef argv configurations to confirm they invoke real CLI commands or tested module functions instead of placeholder stubs.

Why does my physical-AI workflow generate manifest placeholders instead of real artifacts?▼

Your physical-AI workflow generates manifest placeholders because downstream stages are likely invoking echo-based demo stubs rather than the actual GPU-accelerated execution modules required for artifact generation.

How do I check if my robotics data pipeline uses stubbed components?▼

You can check for stubbed components by auditing execution paths against known stub patterns to distinguish between real operational modules and demo stubs within your robotics data pipeline configuration.

What is the best way to ensure pipeline integrity for physical-AI workflows?▼

The best way to ensure pipeline integrity for physical-AI workflows is enforcing real tool execution by auditing tool references, verifying that every advertised stage performs actual work rather than echoing dummy data.

Can I use this audit to verify Cosmos Transfer and FiftyOne curation stages?▼

Yes, you can use this audit to verify that Cosmos Transfer and FiftyOne curation stages are invoking the actual GPU-accelerated execution modules rather than echo-based stubs within your pipeline.

Related Skills

Explore More Software Engineering Skills→
nebiusnebius
17

oss-solution-registry-onboard

Standardize open-source Physical AI repository onboarding into the NPA registry.

Official
Advanced
glfruitglfruit

enhanced-skill-creator

Codify domain patterns into SKILL.md scaffolds with governance metadata.

Community
Advanced
nebiusnebius
17

physical-ai-data-factory

Orchestrate physical AI data workflows with annotation, augmentation, and validation on Nebius.

Official
Advanced
thingpersonthingperson

cross-browser

Generate a cross-browser testing checklist from recent code changes.

Community
Intermediate