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LLM Council

Five AI advisors debate a business decision, each analyzing from a different angle to produce a more well-rounded recommendation.

Business Opsbusiness-opsstandard
by AgentVoltv1.0.0Published 1y ago
Free to sign up · every skill included with AgentVolt Pro

Before & after

Same prompt, same agent — the only difference is the skill.

Prompt“Should we expand to the enterprise market or double down on SMB”
Beforegeneric AI agent
That's a big strategic decision. Both directions have pros and cons. Going enterprise means higher deal sizes but longer sales cycles and more support overhead. SMB is faster to close but requires more volume. I think you should consider your current sales team, your product roadmap, and your financial runway. Different companies make this choice differently depending on their circumstances. Have you looked at your customer acquisition cost for each segment? And what does your product differentiation look like in each market? I'd be happy to explore this more if you want to share more details about your situation.
Afterwith LLM Council
ADVISOR PANEL DEBATE — Market Expansion Decision:

ENTERPRISE ADVOCATE: 'Enterprise contracts average 85K annual vs. 8K for SMB. Three accounts replace 30 SMB customers. Your 12-person team cannot support both simultaneously. Choose now. Expand enterprise: hire two enterprise sales reps, build security compliance module (SOC2, HIPAA), extend contract value to 36 months. ROI: 18 months.'

GROWTH OPERATOR: 'SMB scales faster. You ship one feature; it multiplies across 100+ accounts. Enterprise stalls on feature requests. Your analytics show SMB cohort retention is 78 percent; enterprise churn is higher. Double SMB: invest in product-led growth, self-serve analytics, lower onboarding friction. ROI: 6 months.'

FINANCE LEAD: 'Enterprise is a hedge. SMB revenue is lumpy. One churn event kills three months of SMB growth. Enterprise stabilizes revenue. Risk: 40 percent of enterprise pipelines stall in negotiation.'

TECH LEAD: 'Enterprise requires architecture work. Your codebase isn't multi-tenant yet. Estimate 10 weeks before enterprise-ready. SMB can proceed immediately.'

CONVERGED RECOMMENDATION: SMB first, parallel enterprise pilot. Prove SMB retention at scale; use that data to justify enterprise investment. Revisit in Q2.

About this skill

name: llm-council description: Use when Five AI advisors debate a business decision using the original author's method, each analyzing from a different angle to produce a more well-rounded recommendation.

LLM Council

Instead of asking Claude one question and getting one answer, LLM Council runs the question past five distinct advisor personas that debate it out, surfacing disagreement and blind spots before converging on a recommendation.

What you get

  • A multi-advisor debate transcript plus a final recommendation.

Customize your output

  • Which advisor personas to include
  • the specific decision being analyzed.

Example output

A written debate between 5 advisors culminating in a recommendation.

Best for

Founders and operators who want a 'board of advisors' effect without hiring one.

SKILL.md preview

SKILL.md
---
name: llm-council
description: Use when a business decision needs multiple distinct analytical perspectives debating it out before converging on a recommendation, rather than a single pass of analysis.
version: 1.0.0
category: Business Ops
author: AgentVolt
license: proprietary
tags:
  - business-ops
  - standard
---

# LLM Council

Runs a business decision past five distinct advisor personas who debate it from different angles, surfacing disagreement and blind spots before converging on a single recommendation.

## When to use

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