ai-agent-consultant

Help marketers choose the right type of AI agent for their workflow. Use when a marketer wants to automate a repetitive task but doesn't know what kind of agent to build, or what's even possible with AI agents. Input: task description, frequency, input format, output needed, coding ability. Output: recommended agent type, simplest starting point, full-automation path, risks.

Ir para a instalação

Repositório: thaolst/ai-growth-agents-for-marketers
Última atividade na origem: 1 de junho de 2026 às 14:53
Idioma detectado do SKILL.md: Vários idiomas
Estrelas: 5
Forks: 4

Opções de instalação

Por padrão, está selecionado o prompt que primeiro revisa a origem. Você pode mudar para um comando direto ou baixar uma cópia local.

Instalar com Codex ou Claude Copie este prompt, cole no Codex, Claude ou outro assistente e deixe que ele revise a página da skill e instale para você.

Um comando direto ignora o prompt de revisão. Verifique a origem antes de executá-lo.

npx skills add https://github.com/thaolst/ai-growth-agents-for-marketers --skill ai-agent-consultant

O comando permanece em uma só linha. Role horizontalmente para revisá-lo antes de copiar.

Prefere uma cópia local? Baixe os arquivos disponíveis atualmente no SkillsMP.

Revise os arquivos de origem

Leia o SKILL.md e os arquivos complementares exibidos pelo SkillsMP antes de decidir se vai instalar.

SKILL.md

Instruções da origem · Visualização somente leitura

Voltar à pesquisa Voltar à instalação

ab-test-analyzer

Analyze A/B test results and recommend next actions. Use when the user has A/B test data and needs to know: which variant won, whether the result is statistically reliable, and what to do next. Works for conversion rate tests, copy tests, mechanic tests, UI tests. Input: user counts and conversions for control and variant. Output: winner, confidence level, segment breakdown, recommended action. Includes effect size, p-value, and confidence intervals.

2026-06-01

agent-pre-deploy-review

Review an AI agent prompt and setup before deploying it in real work. Use when the user has built or customized an agent and wants a thorough review before depending on it for real campaign work. Input: agent description, system prompt, example input, example output. Output: prompt weaknesses, edge cases, improvement suggestions, monitoring plan, deploy/no-deploy recommendation.

2026-06-01

automation-scripter

Generate Python scripts to automate repetitive growth marketing tasks. Use when a marketer has a manual, repetitive data task (copy-paste, format, calculate) and wants a simple Python script to automate it — without needing to know how to code. Input: step-by-step description of manual task, data source, desired output, frequency. Output: ready-to-run Python script with Vietnamese comments, error handling, setup guide.

2026-06-01

Ver todas deste repositório

AI Agent Consultant

Bạn là AI agent consultant chuyên tư vấn cho growth marketer.

Context check: Reads .agents/product-marketing-context.md for workflow context.

Người dùng đến với bạn vì họ biết mình muốn tự động hóa một việc gì đó — nhưng chưa biết build agent kiểu nào, hoặc thậm chí chưa biết AI agent có thể làm gì.

Phân loại Agent Types

Type

Phù hợp

Cần code?

Prompt-based

Task đơn, output text

❌

Skill-based

Task chuyên môn, cần context

❌ (install skills)

Python script

Task data repetitive

🐍

Multi-agent flow

Task phức tạp, nhiều bước

❌ (prompt sequence)

MCP server

Task cần real data

🐍

Key Questions

Task này làm bao nhiêu lần? (once / weekly / daily / hourly)

Input là gì? (text / file / API / manual copy-paste)

Output mong muốn? (text report / file / decision / action)

Người dùng có code được không?

Task có cần real-time data không?

Related Skills

automation-scripter — khi cần Python script

campaign-synthesis — khi cần tổng hợp nhiều file

multi-agent-research — khi cần pipeline nhiều agent

name	ai-agent-consultant
description	Help marketers choose the right type of AI agent for their workflow. Use when a marketer wants to automate a repetitive task but doesn't know what kind of agent to build, or what's even possible with AI agents. Input: task description, frequency, input format, output needed, coding ability. Output: recommended agent type, simplest starting point, full-automation path, risks.
metadata	{"author":"thaolst","version":"1.1","license":"MIT","related_skills":["automation-scripter","campaign-synthesis","multi-agent-research"]}