claude

digital-twin-engineering

Digital-twin engineering team — agents (digital-twin-architect, twin-integration-engineer) for the layer answering 'what should this twin MODEL, at what FIDELITY, and does it MATCH the real asset?': twin taxonomy (asset vs process vs system-of-systems; descriptive/predictive/prescriptive; digital-shadow vs true bidirectional), only-as-much-fidelity-as-the-decision-needs, modeling approach (physics vs data-driven/surrogate/reduced-order vs hybrid), telemetry ingestion (MQTT/OPC-UA/Kafka, edge vs cloud), state sync/drift/calibration, simulation & what-if, and fidelity validation. Fluent in DTDL + Azure Digital Twins, ISO 23247, AAS, Eclipse Ditto, NVIDIA Omniverse, Unity/Unreal, Bentley/Siemens. skills, a knowledge bank (decision tree + 2026 patterns), and templates. Distinct from embedded-iot-engineering (device firmware), robotics-autonomous-systems-engineering (robot control/autonomy), and data-platform (BI/warehouse). Requires ravenclaude-core@>=0.7.0.

9 on GitHubby Matt Corbettv0.1.2MITupdated today
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Plugin digital-twin-engineering from marketplace ravenclaude in mcorbett51090/RavenClaude. Commands read from the repo's manifest — today.

What it installs

Skills (3)

  • choose-digital-twin-architecture

    Scope and architect a digital twin for a described asset and decision by traversing the digital-twin architecture decision tree (decision it informs → twin type → shadow-vs-bidirectional → descriptive/predictive/prescriptive → modeling approach → fidelity → sync → platform), then return the twin sco

  • design-twin-data-and-sync-model

    From a physical asset and its telemetry, derive the twin's data and synchronization model — the signal list and sampling rates, the transport protocol (MQTT / OPC-UA / Kafka), the edge-vs-cloud split, the sync-latency budget the decision tolerates, the binding of each signal to the twin's model prop

  • implement-twin-integration-and-simulation

    Build a digital twin end to end — ingest the telemetry (MQTT / OPC-UA / Kafka, edge-vs-cloud) and bind it to the model (DTDL properties / AAS submodels), wire the physics or reduced-order/surrogate model, run simulation and what-if scenarios against live twin state, stand up 3D or dashboard visualiz

Subagents (2)

  • digital-twin-architect

    Use to choose the digital-twin SCOPE, type, and FIDELITY — asset vs process vs system-of-systems, digital-shadow vs bidirectional, modeling approach (physics/data-driven/hybrid), sync strategy, and platform. Decision-tree-driven. NOT for IoT device firmware → embedded-iot-engineering.

  • twin-integration-engineer

    Use to BUILD & VALIDATE a digital twin — telemetry ingestion (MQTT/OPC-UA/Kafka, edge vs cloud), model wiring (DTDL/AAS), simulation & what-if, drift/reconciliation, and fidelity validation (error bounds vs the real asset). NOT for robot control/autonomy → robotics-autonomous-systems-engineering.

View source on GitHub mcorbett51090.github.io

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finance

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23 skills · 7 commands · 7 agents · hooks

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Web design & build specialist team — web architect (IA, stack, hosting), UX designer (wireframes, flows, conversion), visual designer (brand, typography, tokens), frontend implementer (HTML/CSS/JS, React, Astro, Next), content strategist (copy, microcopy, SEO content), accessibility auditor (WCAG 2.2 AA/AAA), and performance engineer (Core Web Vitals, image/font optimization). skills (the gold-standard-website-pipeline gated build pipeline, static-site build, design-system audit, card/tile UI, accessibility review, Core Web Vitals tuning, technical SEO audit, information architecture, conversion design, content audit, design-tokens scaffolding, third-party hygiene, Fluent UI v9 + React implementation), templates, an advisory hook, and a knowledge bank seeded with a curated 2026 reference set of "cutting edge yet simple" marketing-site donors — the design agents carry compact inline priors plus a pointer to the full brief. Inherits ravenclaude-core protocols.

19 skills · 7 commands · 7 agents · hooks · LSP

9

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17 skills · 5 commands · 6 agents · hooks

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Financial-regulatory & compliance specialist team — function agents (AML/KYC, regulatory-reporting, risk-and-controls, policy & procedure, examination-prep, Bermuda-insurance) PLUS jurisdiction/regulator specialists: BMA financial-institutions (banking, trust, corporate-services, fund-admin, investment-business, money-service, digital-assets — the primary build-out, with deep AML/ATF + supervision/fees + licensing-classification trees), CIMA (Cayman), Bahamas, Channel Islands (Jersey JFSC + Guernsey GFSC), UK PRA, and US federal+state. primary-source-cited regulator knowledge files, best-practice rules, skills, templates, a defensive PreToolUse hook (PII scrub — SSN/IBAN/credit-card/Bermuda TIN/wire instructions). Positioning reflects field experience inside a Tier-1 financial regulator (BMA). Inherits ravenclaude-core protocols.

11 skills · 5 commands · 12 agents · hooks

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