llm-council

📁 dnyoussef/context-cascade 📅 5 days ago
1
总安装量
1
周安装量
#50879
全站排名
安装命令
npx skills add https://github.com/dnyoussef/context-cascade --skill llm-council

Agent 安装分布

replit 1
windsurf 1
openclaw 1
opencode 1
cursor 1
codex 1

Skill 文档

LLM Council Skill


LIBRARY-FIRST PROTOCOL (MANDATORY)

Before writing ANY code, you MUST check:

Step 1: Library Catalog

  • Location: .claude/library/catalog.json
  • If match >70%: REUSE or ADAPT

Step 2: Patterns Guide

  • Location: .claude/docs/inventories/LIBRARY-PATTERNS-GUIDE.md
  • If pattern exists: FOLLOW documented approach

Step 3: Existing Projects

  • Location: D:\Projects\*
  • If found: EXTRACT and adapt

Decision Matrix

Match Action
Library >90% REUSE directly
Library 70-90% ADAPT minimally
Pattern exists FOLLOW pattern
In project EXTRACT
No match BUILD (add to library after)

Purpose

Run 3-stage multi-model consensus for critical decisions where:

  • Single-model hallucination risk is unacceptable
  • Multiple perspectives improve decision quality
  • High-stakes choices need validation

Architecture (Karpathy Pattern)

STAGE 1: COLLECT
  +---> Claude ---> Response A
  |
Query --+---> Gemini ---> Response B
  |
  +---> Codex ----> Response C

STAGE 2: RANK
  Each model reviews others (anonymized)
  Produces rankings with rationale

STAGE 3: SYNTHESIZE
  Chairman aggregates rankings
  Produces final answer with consensus score

When to Use

Perfect For:

  • Architecture decisions
  • Technology selection
  • Critical bug triage
  • Security assessment
  • High-risk deployments
  • Contentious design choices

Don’t Use When:

  • Simple, low-risk decisions
  • Time-critical responses
  • Single correct answer exists
  • Cost is a concern (3x API usage)

Usage

Basic Council

/llm-council "Should we use microservices or monolith for this system?"

With Threshold

/llm-council "Which auth approach is best?" --threshold 0.75

With Chairman Override

/llm-council "Architecture decision" --chairman gemini

Command Pattern

bash scripts/multi-model/llm-council.sh "<query>" "<threshold>" "<chairman>"

Configuration

Parameter Default Description
threshold 0.67 Minimum consensus score
chairman claude Model that synthesizes final answer
models [claude, gemini, codex] Participating models

Consensus Scoring

  • >0.80: Strong consensus – proceed with confidence
  • 0.67-0.80: Moderate consensus – consider minority views
  • <0.67: Weak consensus – escalate to human review

Memory Integration

Results stored to Memory-MCP:

  • Key: multi-model/council/decisions/{query_id}
  • Tags: WHO=llm-council, WHY=consensus-decision

Output Format

{
  "query": "Original question",
  "final_answer": {
    "synthesis": "Combined answer...",
    "chairman": "claude"
  },
  "consensus_score": 0.85,
  "responses": {
    "claude": "...",
    "gemini": "...",
    "codex": "..."
  },
  "rankings": [
    {"model": "A", "rank": 1, "rationale": "..."}
  ]
}

Failure Modes

Deadlock (No Consensus)

  • All models disagree
  • Consensus < threshold
  • Action: Store for human review

Model Unavailable

  • One model times out
  • Action: Continue with 2 models (2/3 quorum)

Chairman Failure

  • Synthesis fails
  • Action: Fallback to highest-ranked response

Integration Examples

Architecture Decision

const decision = await runCouncil(
  "Microservices vs Monolith for our scale?",
  { threshold: 0.75 }
);

if (decision.consensus_score >= 0.75) {
  proceed(decision.final_answer);
} else {
  escalateToHuman(decision);
}

Security Assessment

const assessment = await runCouncil(
  "Is this authentication approach secure?",
  { threshold: 0.80 }
);
// Higher threshold for security decisions

Sources