How do I install the Multi Agent Research skill?

Run npx skillmds@latest add thaolst/multi-agent-research in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Multi Agent Research safe to use?

This skill has not completed SkillMD's automated safety review yet. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Multi Agent Research?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Multi Agent Research free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Multi Agent Research?

thaolst (@thaolst) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Multi Agent Research by thaolst — Agent Skill

Name: Multi Agent Research
Author: thaolst

Multi Agent Research

Run multi-agent research-to-planning pipeline using two sequential agents. Use when the user has campaign data and needs a structured plan without code. Agent 1 (Research) analyzes campaign data and returns structured JSON insights. Agent 2 (Strategy) takes those insights and produces a complete campaign plan. Input: campaign data, target, budget, timeline. Output: research findings as JSON → executable campaign plan.

thaolst e8d5514 1.7 KB Updated Sep 17, 2026

File contents

Multi-Agent Research & Planning Agent

Bạn hướng dẫn marketer chạy hai agent nối tiếp nhau — không cần code, chỉ cần hai cuộc trò chuyện riêng trong Claude.

Context check: Reads .agents/product-marketing-context.md for market context. If growth-mcp connected, pulls market data before research phase.

Workflow

Agent 1: Research

Input: campaign data, target, budget. Output: structured JSON insights về market, segments, past performance, recommendations.

Agent 2: Strategy

Input: JSON từ Agent 1 + constraints. Output: executable campaign plan với timeline, budget, mechanics, risks.

Khi nào dùng

Có nhiều dữ liệu campaign cần phân tích trước khi lập kế hoạch
Muốn structured research notes (JSON) trước khi viết plan
Campaign phức tạp, cần separation of concerns

Related Skills

campaign-planning — tổng quan plan
campaign-brief — chi tiết từng campaign
growth-mcp-connect — pull research data

English

Guide the marketer through a two-agent sequential pipeline — no code required, just two separate conversations in Claude.

Agent 1 (Research) → Agent 2 (Strategy) = executable campaign plan.

Frequently asked questions