mixture-of-experts

Audits plans, codebases, and evidence archives using multiple specialized expert lenses.

2|Updated Aug 15, 2026
One-click install
npx skills add https://github.com/Arenukvern/shortly --skill mixture-of-experts-arenukvern
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: mixture-of-experts
Source: https://github.com/Arenukvern/shortly/tree/main/.agents/skills/mixture-of-experts
Command: npx skills add https://github.com/Arenukvern/shortly --skill mixture-of-experts-arenukvern

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve? Single-perspective reviews of architectures, plans, or repositories often miss contradictions, duplicated intent, and maintenance traps. This Skill forces multiple independent expert personas to critique the same topic from orthogonal angles before synthesizing their findings. ## Core Features & Use Cases - Expert Persona Definition: Invents 2-4 specialized lenses (e.g., Security Specialist, Evidence / Retention QA, Generational Architecture Skeptic) each with an ownership contract covering scope, fallback, and integration surface. - Subagent Orchestration: Spawns independent subagents for parallel critique, or runs lenses sequentially with explicit labeling when no subagent tool is available. - Cross-Referenced Synthesis: Merges findings with a lens-status summary and ends with a disposition such as promote_to_artifact, convert_to_check, compress_existing, delete_or_retire, or leave_native. - Use Case: Ask for a MoE audit of a new caching architecture; the Skill spawns a Security Specialist, Scalability Engineer, and Cost Analyst, then synthesizes contradictions and actionable recommendations. ## Quick Start Ask the AI to run a mixture of experts audit on your architecture plan or repository skills to detect flaws and duplicated intent.

Frequently Asked Questions about mixture-of-experts

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

FAQPage Schema
How do I run a mixture of experts audit on an architecture plan?▼

Ask the AI to run a MoE audit on the plan. The Skill defines 2-4 orthogonal expert personas such as Security Specialist or Cost Analyst, spawns them as subagents, then synthesizes contradictions and recommendations.

What is a mixture of experts pattern for AI code review?▼

It is a critical-thinking framework where independent expert personas analyze the same codebase or plan from different angles, then cross-reference findings to detect flaws, overlap, and drift that a single review would miss.

Can I use MoE audits without subagent support in my AI tool?▼

Yes. When no subagent capability is available, the Skill runs the expert lenses sequentially and labels the output as a non-parallel MoE, preserving the same critique structure.

How many expert personas should a MoE audit spawn?▼

The default is 2-3 experts with a maximum of 4. More than 3 is used only when the user explicitly requests broad coverage or the domains are truly independent.

What happens when an expert lens times out or returns partial evidence?▼

The lens is labeled as missing_lens, partial_lens, timed_out_lens, or superseded_lens. The audit either retries, continues with downgraded confidence, or states that the missing lens blocks a stronger claim.

When should I not use a mixture of experts audit?▼

Avoid it for simple single-perspective tasks or installation questions. MoE findings are advisory critique only and do not authorize file writes or replace implementation handoff workflows.