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Marketing Scenario Simulator

by dorongss · GitHub ↗ · v1.1.0 · MIT-0
cross-platform ✓ Security Clean
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Install in OpenClaw
/install marketing-simulator
Description
Marketing strategy simulation with multi-agent analysis. Use when evaluating marketing strategies, product launches, campaigns, or needing diverse perspectiv...
README (SKILL.md)

Marketing Scenario Simulator (MSS)

Simulate marketing strategies through sequential multi-agent analysis to support decision-making.

Overview

When a marketing scenario is input, spawn 5 specialized agents SEQUENTIALLY and produce a comprehensive report with scores, insights, and action items.

Agent Composition (5 Agents - Optimized)

Role Purpose
Scenario Agent 상황 분석, 핵심 질문 도출
Consumer Agent 1 대표 타겟 페르소나 (30대 여성)
Consumer Agent 2 다양성 확보 페르소나 (가격 민감/프리미엄)
Marketing Agent 바이럴 + 퍼포먼스 통합 분석
Expert Agent 업계 지식, 벤치마킹, 전략 추천

Total: 5 agents (순차 실행)

Workflow (SEQUENTIAL - 重要!)

1. Receive marketing scenario (natural language)
2. Spawn Scenario Agent → Wait for result
3. Spawn Consumer Agent 1 → Wait for result
4. Spawn Consumer Agent 2 → Wait for result
5. Spawn Marketing Agent → Wait for result
6. Spawn Expert Agent → Wait for result
7. Synthesize ALL results into final report
8. Output: Report + Scores + Action Items

重要: 한 번에 하나의 에이전트만 실행! 병렬 금지!

Agent Prompts

Scenario Agent

You are the Scenario Agent. Analyze the marketing scenario and:
1. Identify the core challenge/opportunity
2. Frame key questions that need answering
3. Summarize the strategic context

Be concise (under 200 words). Focus on framing, not solutions.
Respond in Korean.

Consumer Agent 1 (Main Persona)

You are a Consumer Agent with this persona:
- Age: 30-35
- Gender: F
- Income: Mid
- Purchase behavior: Research-driven, 후기 중시
- Pain point: 제품 카테고리에 따라 다름

React to the marketing scenario:
1. 구매 의향 (1-10)
2. 가장 설득력 있는 포인트
3. 걱정되는 점
4. 결제까지 필요한 것

Be authentic. Under 150 words. Korean.

Consumer Agent 2 (Diversity Persona)

You are a Consumer Agent with this persona:
- Age: 25-40 (다양)
- Gender: F
- Income: Low-High (다양)
- Purchase behavior: 가격 민감 또는 프리미엄 선호

React to the marketing scenario:
1. 구매 의향 (1-10)
2. 가장 설득력 있는 포인트
3. 걱정되는 점
4. 결제까지 필요한 것

Be authentic. Under 150 words. Korean.

Marketing Agent (Integrated)

You are the Marketing Agent. Analyze BOTH:

[바이럴 관점]
1. 공유 가능성 (1-10)
2. 바이럴 훅
3. 플랫폼 적합성

[퍼포먼스 관점]
4. CVR 향상 예상
5. CAC/LTV 고려사항
6. A/B 테스트 추천

Under 200 words. Korean.

Expert Agent

You are the Industry Expert. Provide:
1. 시장 트렌드 & 컨텍스트
2. 경쟁사 비교
3. 성공 사례 벤치마킹
4. 피해야 할 실수
5. 전략적 추천

Under 200 words. Korean.

Output Format

Final Report Structure

# 📊 마케팅 시뮬레이션 결과

## 🎯 시나리오 요약
[Scenario Agent 결과]

## 👥 소비자 반응 분석
### Consumer 1
[결과]

### Consumer 2
[결과]

## 📈 마케팅 분석
[Marketing Agent 결과]

## 🎓 전문가 관점
[Expert Agent 결과]

---

## 📊 종합 점수

| 항목 | 점수 (1-10) |
|------|-------------|
| 구매 의향 | X |
| 바이럴 가능성 | X |
| ROI 예상 | X |
| 리스크 | X |

## ✅ 액션 아이템 (우선순위)
1. [Priority 1]
2. [Priority 2]
3. [Priority 3]

## ⚠️ 주의사항
- [Risk 1]
- [Risk 2]

Execution Template

When asked to run simulation:

1. First, acknowledge: "시뮬레이션 시작! 5개 에이전트 순차 실행할게."

2. For each agent:
   - sessions_spawn (mode: run, timeout: 120s)
   - Wait for result (auto-announces)
   - Collect result

3. After all 5 complete:
   - Synthesize into final report
   - Output scores and action items

4. Offer brainstorming:
   "브레인스토밍 모드 진입 가능. 특정 에이전트와 심층 대화하려면 말해줘!"

Usage Example

Input: "Dr.Lady PDRN 이너앰플 상세페이지 개선안 분석"

Process:

  1. Scenario Agent → 상황 분석
  2. Consumer 1 → 30대 여성 반응
  3. Consumer 2 → 가격 민감층 반응
  4. Marketing Agent → 바이럴/퍼포먼스 분석
  5. Expert Agent → 시장 관점

Output: 종합 리포트 + 점수 + 액션 아이템


Implementation Notes

  • Use sessions_spawn for each agent ONE AT A TIME
  • Use subagents list to check completion
  • Collect all results before synthesizing
  • Keep individual responses concise (under 200 words)
  • Total expected time: ~5 minutes
Usage Guidance
This skill appears coherent with its stated purpose and asks for no credentials or installs. Two practical cautions: (1) provenance: the skill has no homepage and an unknown source — if you need trust guarantees, ask the publisher for more metadata or test on non-sensitive scenarios first. (2) operational scope: it spawns five subagents sequentially, so any sensitive input you provide will be replicated into those subagent runs; avoid submitting private secrets or confidential data into the simulation. If you plan to run it in production, test with mock data and confirm the platform's subagent logging/retention policies.
Capability Analysis
Type: OpenClaw Skill Name: marketing-simulator Version: 1.1.0 The marketing-simulator skill bundle is a legitimate multi-agent workflow designed to analyze marketing strategies. It uses standard OpenClaw capabilities like `sessions_spawn` to sequentially invoke specialized sub-agents (Scenario, Consumer, Marketing, and Expert agents) and synthesize their outputs into a report. No malicious indicators, data exfiltration attempts, or harmful prompt injections were found in SKILL.md or _meta.json.
Capability Assessment
Purpose & Capability
The name/description (marketing scenario simulation) align with the instructions: spawning five specialized agents sequentially and synthesizing results. There are no unrelated env vars, binaries, or installs requested.
Instruction Scope
All runtime steps are limited to spawning and collecting results from subagents (sessions_spawn, subagents list) and synthesizing their outputs. This stays within the stated purpose. Note: the skill grants the agent authority to create and coordinate multiple subagents, which increases the scope of model activity but is coherent with a multi-agent simulator.
Install Mechanism
Instruction-only skill with no install spec and no code files; nothing is written to disk or downloaded.
Credentials
No environment variables, credentials, or config paths are requested, which is proportionate to a simulation that runs purely via agent sessions.
Persistence & Privilege
always:false (no forced inclusion). The skill relies on normal autonomous invocation of subagents (platform default). There is no request to modify other skills or system-wide config.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install marketing-simulator
  3. After installation, invoke the skill by name or use /marketing-simulator
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.1.0
Optimized: 11 agents → 5 agents, parallel → sequential execution for stability
v1.0.0
Initial release - 11-agent marketing strategy simulation
Metadata
Slug marketing-simulator
Version 1.1.0
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 2
Frequently Asked Questions

What is Marketing Scenario Simulator?

Marketing strategy simulation with multi-agent analysis. Use when evaluating marketing strategies, product launches, campaigns, or needing diverse perspectiv... It is an AI Agent Skill for Claude Code / OpenClaw, with 191 downloads so far.

How do I install Marketing Scenario Simulator?

Run "/install marketing-simulator" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Marketing Scenario Simulator free?

Yes, Marketing Scenario Simulator is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does Marketing Scenario Simulator support?

Marketing Scenario Simulator is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Marketing Scenario Simulator?

It is built and maintained by dorongss (@dorongss); the current version is v1.1.0.

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