agent-council
Skill0 starsChanged 9 months agoApache-2.0View on GitHub
5-Persona 전문가 토론 시스템 - Architect/CFO/DevOps/Security/PM 다관점 합의 의사결정 (800-1200 tokens). Team Attention 컨셉 구현, MCP collaborative_reasoning + bias-detection 활용. Agent Teams (2.1.32+) 지원.
5 other projects use a version of this.
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- Sentry01/copilot-cli-skillstheir own version, first seen Nov 8, 2026
- ntguion/perspective-gen-skilltheir own version, first seen Oct 15, 2026
- kartikkabadi/skillstheir own version, first seen Aug 10, 2026
- magnus919/agent-skillstheir own version, first seen Jul 21, 2026
- ClydeShen/AgentCounciltheir own version, first seen May 15, 2026
Other versions5 projects use a version of this.
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Wrote their own version · 5
- magnus919/agent-skills★ 172same name
- kartikkabadi/skills★ 9same name
- Sentry01/copilot-cli-skills★ 8same name
- ClydeShen/AgentCouncil★ 0same name
- ntguion/perspective-gen-skill★ 0same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository12 other files it gives its agents.
- CLAUDE.mdCLAUDE.md
- decision-workflowSkill
- deployment-checklistSkill
- frontend-designSkill
- implementation-workflowSkill
- mcp-management-workflowSkill
- mcp-selectorSkill
- multidimensional-analysisSkill
- prd-auto-executorSkill
- prd-implementation-trackerSkill
- research-workflowSkill
- session-continuitySkill
The file
Files
Agent Council Skill
Version: 1.0.0 Purpose: 5-Persona 전문가 토론을 통한 다관점 합의 의사결정
개요
Team Attention 컨셉을 MCP 기반으로 구현한 전문가 패널 시뮬레이션 시스템입니다.
5-Persona 구성
- 🏗️ Architect (기술 아키텍처 관점)
- 기술적 실현 가능성
- 시스템 설계 품질
- 기술 부채 영향
- 💰 CFO (비용/ROI 관점)
- 초기 투자 비용
- 운영 비용 (OpEx)
- ROI 및 payback period
- 🔧 DevOps (운영/배포 관점)
- 배포 복잡도
- 모니터링 요구사항
- 운영 안정성
- 🛡️ Security (보안 관점)
- 보안 취약점
- Compliance 요구사항
- 데이터 보호
- 📊 PM (일정/리소스 관점)
- 개발 일정
- 팀 리소스 할당
- 마일스톤 달성 가능성
워크플로우
Round 1 (Opinion): 각 페르소나별 초안 의견 (MCP: collaborative_reasoning) Round 2 (Challenge): 페르소나 간 반박 및 질문 (MCP: bias-detection) Round 3 (Consensus): 가중 합의 도출 (MCP: stochastic weighting)
MCP 통합
- clear-thought-1.5 (collaborative_reasoning): 페르소나 간 구조화된 토론
- clear-thought (collaborativereasoning): 페르소나 정의 및 역할
- model-enhancement-servers (bias-detection): 각 페르소나 의견 편향 검사
- stochastic-thinking (bayesian): 합의 가중치 계산
토큰 예산
| 단계 | 토큰 | 비고 |
| Persona 정의 | 50-100 | 5-persona 배경 |
| Round 1 | 200-300 | 5 × 40-60 tokens/persona |
| Round 2 | 250-350 | 반박/질문 |
| Round 3 | 200-300 | 합의 도출 |
| Final Synthesis | 100-150 | 최종 통합 |
| Total | 800-1200 | MCP overhead 포함 |
사용 시나리오
적합한 경우
- 고위험 의사결정 (팀 합의 필요)
- 이해관계자 충돌 예상
- 다관점 검증 필요 (기술/재무/운영/보안/일정)
- Production 배포 전 사전 검토
부적합한 경우
- 개인 의사결정 (→ decision-workflow 사용)
- 기술 심층 분석 (→ multidimensional-analysis 사용)
- 빠른 결정 필요 (800-1200 tokens 소요)
병렬 사용 (Multidimensional Analysis)
Agent Council과 Multidimensional Analysis는 상호 보완적입니다:
Case 1: 기술 + 인간 관점 병렬 분석
- multidimensional-analysis (Level 4): 기술 심층 분석 (3400-4600 tokens)
- agent-council: 이해관계자 합의 시뮬레이션 (800-1200 tokens)
- Total: 4200-5800 tokens
- 효과: 기술적 엄격성 + 조직 합의
Case 2: 순차 사용
- agent-council → 합의 도출 → multidimensional-analysis로 검증
- multidimensional-analysis → 기술 분석 → agent-council로 이해관계자 설득 시뮬레이션참조
상세 워크플로우: prompt.md
MCP Operations: clear-thought-1.5 collaborative_reasoning, bias-detection, stochastic bayesian
Release Date: 2026-01-25 Design Pattern: Composite Skill (decision-engine + session-memory) MCP Integration: 4 services, 4 operations Token Range: 800-1200 Confidence Range: 85-92% (합의 기반)
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