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derive-physical-architecture

Map logical components to deployment targets, resources, and communication edges.

3|Updated Jan 25, 2026
Search Tags:#architecture#deployment targets#NFR mapping#resource sizing#decision manifest#system inventory#comms wiring
One-click install
npx skills add https://github.com/kapilvirenahuja/garura --skill derive-physical-architecture
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: derive-physical-architecture
Source: https://github.com/kapilvirenahuja/garura/tree/main/core/components/skills/derive-physical-architecture
Command: npx skills add https://github.com/kapilvirenahuja/garura --skill derive-physical-architecture

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

It prevents architectural drift by turning a logical architecture into a grounded, deployable physical runtime—selecting deployment targets, sizing resources, wiring communication edges, and mapping each refined NFR to concrete delivery mechanisms.

Core Features & Use Cases

  • Runtime realization of logical components: Converts every logical component into one or more physical components while inheriting system_ref and layer from inventory grounding to keep the architecture consistent.
  • Deterministic physical decisions with traceability: Produces a physical-architecture.yaml plus a decision manifest that records cardinality, deployment targets, resource sizing, comms protocol, retry/idempotency stance, and NFR delivery mechanisms.
  • Quality profile delivery mapping: Ensures every refined quality characteristic with relevance is delivered by named mechanisms in the correct components, preventing “unmapped” quality targets.
  • Comms graph validation: Wires outbound edges with explicit protocol/sync mode and validates runtime cycles (sync-only cycles forbidden) to avoid unsafe runtime feedback loops.

Quick Start

Invoke derive-physical-architecture via tech-architect Stage 4 to generate physical-architecture.yaml at {product_base}architecture/physical-architecture.yaml along with its decision-manifest file.

Frequently Asked Questions about derive-physical-architecture

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

FAQPage Schema
How do I map logical components to physical deployment targets?▼

To map logical components to physical deployment targets, you derive a physical architecture by inheriting inventory-grounded system references and recording decisions in a manifest. This process converts logical elements into deployable runtime components with specific resources.

What is physical architecture derivation in the AI-Native SDLC?▼

Physical architecture derivation is the Stage 4 process of turning a logical architecture into a grounded, deployable runtime. It selects deployment targets, sizes resources, wires communication edges, and maps refined NFRs to concrete delivery mechanisms.

How do I validate communication edges and prevent unsafe runtime feedback loops?▼

To validate communication edges and prevent unsafe runtime feedback loops, you wire outbound edges with explicit protocols and sync modes. The derivation process validates runtime cycles to ensure no sync-only cycles exist, preventing unsafe feedback loops.

Do I need a logical architecture file and quality profile to generate a physical architecture?▼

Yes, you need a logical architecture file, a refined quality profile, an inventory grounding set, and candidate catalogs to generate a physical architecture. These inputs ensure deterministic physicalization and NFR delivery coverage validation.

Why does architectural drift occur and how do I prevent it during runtime realization?▼

Architectural drift occurs when logical designs are not grounded in deployable runtimes. You prevent it by deriving a physical architecture that inherits system references, wires communication edges, and maps every refined NFR to named delivery mechanisms.

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