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winston-ai-architecture

Map Winston's AI architecture paths, ownership surfaces, and key files.

Updated Jan 22, 2026
Search Tags:#ownership#audit#rag#ai-architecture#maps#gateway
One-click install
npx skills add https://github.com/paulmalmquist/Consulting_app --skill winston-ai-architecture
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: winston-ai-architecture
Source: https://github.com/paulmalmquist/Consulting_app/tree/main/skills/winston-ai-architecture
Command: npx skills add https://github.com/paulmalmquist/Consulting_app --skill winston-ai-architecture

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Winston's AI architecture is multi-path and ownership-fragmented; this skill maps Winston's architecture to reveal active paths and ownership boundaries.

Core Features & Use Cases

  • Identify the active AI path and its owning surface across gateway routing, RAG, tool-calling, and lane-model analysis.
  • Catalog key files and boundary points to inform handoffs and ownership decisions.
  • Provide a durable map for architecture reviews and incremental hardening efforts.

Quick Start

Identify the active Winston AI path and owning surface, then map key files and surfaces.

Frequently Asked Questions about winston-ai-architecture

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

FAQPage Schema
How do I map AI architecture paths and identify ownership boundaries in a fragmented system?▼

To map AI architecture, you identify the active AI path and its owning surface across gateway routing, RAG, and tool-calling. Cataloging key files and boundary points provides a durable map for architecture reviews and hardening.

What is an AI architecture audit and when do I need one for RAG and gateway routing?▼

An AI architecture audit identifies active paths and owning surfaces across gateway routing, RAG, and tool-calling topology. You need one when architecture is multi-path and ownership-fragmented to inform handoffs and ownership decisions.

How do I audit RAG pipelines and tool-calling topology to find owning surfaces?▼

Auditing RAG pipelines and tool-calling topology involves identifying the active AI path and its owning surface. Cataloging key files and boundary points informs handoffs and lane-model ownership decisions.

Can I use this approach for repo-grounded AI maps and lane-model ownership decisions?▼

Yes, this approach applies to repo-grounded AI maps, gateway routing, RAG audits, and lane-model ownership decisions. It identifies the active AI path, lists key files, and provides handoff flows to specialized subskills.

What's the best way to harden multi-path AI architecture with fragmented ownership?▼

The best way to harden multi-path AI architecture is mapping it to reveal active paths and ownership boundaries. Cataloging key files creates a durable map for incremental hardening efforts and architecture reviews.

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