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digital-twin skill

/skills/digital-twin

This skill helps you build and maintain digital twins by synchronizing virtual models with real systems for monitoring and predictive maintenance.

npx playbooks add skill omer-metin/skills-for-antigravity --skill digital-twin

Review the files below or copy the command above to add this skill to your agents.

Files (4)
SKILL.md
1.2 KB
---
name: digital-twin
description: Build and maintain digital twins - virtual representations of physical systems that synchronize with real-world counterparts for monitoring, prediction, and optimization. Use when "digital twin, virtual model, real-time synchronization, physical-virtual coupling, predictive maintenance, asset modeling, system replica, live simulation, " mentioned. 
---

# Digital Twin

## Identity



## Reference System Usage

You must ground your responses in the provided reference files, treating them as the source of truth for this domain:

* **For Creation:** Always consult **`references/patterns.md`**. This file dictates *how* things should be built. Ignore generic approaches if a specific pattern exists here.
* **For Diagnosis:** Always consult **`references/sharp_edges.md`**. This file lists the critical failures and "why" they happen. Use it to explain risks to the user.
* **For Review:** Always consult **`references/validations.md`**. This contains the strict rules and constraints. Use it to validate user inputs objectively.

**Note:** If a user's request conflicts with the guidance in these files, politely correct them using the information provided in the references.

Overview

This skill helps build and maintain digital twins—virtual representations of physical systems that synchronize with real-world counterparts for monitoring, prediction, and optimization. It guides creation, diagnosis, and validation using a strict, reference-driven workflow. The goal is reliable, auditable twins that support real-time synchronization and predictive maintenance.

How this skill works

When creating a twin, the skill consults a canonical patterns reference to select modeling approaches, interfaces, and data schemas. For diagnosis it inspects system behavior against known failure modes from a sharp-edges reference to identify root causes and risks. For reviews it runs objective checks against a validations reference to ensure constraints, invariants, and safety rules are met. If user requests conflict with those references, the skill corrects them and explains the rationale.

When to use it

  • Designing a new digital twin or virtual model of an asset or system
  • Implementing real-time synchronization between sensors and a virtual replica
  • Setting up predictive maintenance and anomaly detection workflows
  • Validating a twin against strict safety, performance, or regulatory constraints
  • Diagnosing failures, drift, or unexpected behavior in an existing twin

Best practices

  • Always begin with the prescribed patterns reference to choose architecture and data schemas
  • Use the sharp-edges guide early to anticipate common failure modes and mitigation steps
  • Validate every model update against the validations reference before deployment
  • Keep physical-virtual coupling interfaces versioned and auditable
  • Instrument the twin with monitoring that feeds back into diagnosis rules

Example use cases

  • Create a live simulation of an HVAC system for energy optimization and control testing
  • Build an asset-level twin for predictive maintenance of industrial pumps using sensor streams
  • Diagnose a twin that shows latency-induced drift and recommend corrective coupling changes
  • Run a compliance review to ensure model constraints and safety invariants meet validation rules
  • Prototype a fleet-level twin for route optimization and wear forecasting

FAQ

What references does this skill require?

It relies on three reference files: patterns for creation, sharp_edges for diagnosis, and validations for review; they are the source of truth.

Can I override the reference guidance?

No. If a request conflicts with the references, the skill will correct the approach and explain why the reference must be followed.

Which outcomes can I expect?

A validated, reference-aligned twin ready for deployment, clear diagnosis reports with root causes, and actionable remediation steps.