agentsclimarketplace

Multi agent research

Skill thaolst/ai-growth-agents-for-marketers/skills/multi-agent-research

AI agents for growth marketing — built from real fintech campaigns. Prompts + Python.

Install
npx -y skills add thaolst/ai-growth-agents-for-marketers --skill multi-agent-research

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

  • 5 stars5 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

What its author says it does

Copied from the file, not written here

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.

SKILL.md

1.9 KB, as published. Nobody here has run it

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

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.

Keep looking

Skills are one crate of 328,083. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.