ai-router-architect

Design a centralized AI routing layer with server-side credential custody and cost controls.

2|Updated Jul 6, 2026
One-click install
npx skills add https://github.com/nguyenpv1980-wq/Project-Aegis --skill ai-router-architect
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: ai-router-architect
Source: https://github.com/nguyenpv1980-wq/Project-Aegis/tree/main/.claude/skills/ai-router-architect
Command: npx skills add https://github.com/nguyenpv1980-wq/Project-Aegis --skill ai-router-architect

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill solves the problem of scattered AI provider calls by defining a single routing layer where every model request goes through one controlled interface. It helps teams avoid client-side key exposure, inconsistent retry behavior, and ungoverned model usage.

Core Features & Use Cases

  • Single routing choke point: Consolidates all model calls behind one internal gateway so credentials, model selection, cost limits, and failure handling are enforced consistently.
  • Server-side credential custody: Ensures provider keys stay off the client bundle and are managed through secure server-side handling with rotation support.
  • Deterministic routing and resilience: Selects models by task, cost, latency, and availability while supporting bounded retries, provider fallback, degraded responses, circuit breakers, and a kill switch.
  • Telemetry at the call level: Defines per-request metrics such as model, token counts, estimated cost, latency, correlation id, and fallback usage for observability and chargeback.
  • Use case: Use this Skill when replacing direct OpenAI and Anthropic calls with one governed AI gateway that enforces budgets and survives provider outages.

Quick Start

Ask the AI to design a server-side model routing layer that centralizes provider calls, keeps credentials out of the client, enforces budgets at one choke point, and includes fallback, telemetry, and a kill switch.

Frequently Asked Questions about ai-router-architect

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

FAQPage Schema
How do I centralize AI model calls to protect provider credentials and control costs?

You can centralize AI model calls by designing a single server-side routing layer that consolidates requests, keeps provider keys off the client bundle, and enforces budget limits at one internal gateway choke point.

How does provider fallback and circuit breaking work in an AI gateway?

Provider fallback and circuit breaking in an AI gateway select models by task, cost, and availability, rerouting requests to alternative providers and triggering a kill switch if failure thresholds are exceeded.

How do I implement telemetry and cost tracking for multi-model orchestration?

Implement telemetry for multi-model orchestration by emitting per-request metrics including model used, token counts, estimated cost, latency, correlation id, and fallback usage to enable observability and chargeback.

Can I use this AI routing layer to replace direct OpenAI and Anthropic SDK integrations?

Yes, you can replace scattered direct OpenAI and Anthropic SDK integrations with one governed AI gateway that enforces server-side credential custody, cost limits, and consistent failure handling.

What are the limitations of using a centralized model gateway for provider migration?

A centralized model gateway requires manual-only handling for live provider wiring and does not expose server-side keys to the client, meaning you must configure secure server-side credential rotation support yourself.