🧰 AI Agents For Smarter Marketing Work


🧰 Smart tools. Useful tips. Weekly.

Hola friend 👋,

I’m Josep. Each week, I hunt down practical tools and productivity hacks to help digital doers like you do more with less effort.

This week: a beginner-friendly look at advanced AI for marketing, without the developer jargon.

For a long time, using AI for marketing meant asking ChatGPT for headline ideas, blog outlines, or a slightly less boring email. Useful, yes. But the newer wave is different: AI can now work inside projects, reuse specialist instructions, and connect to the tools where your real business data lives.

So today is more of a map than a normal tool roundup. We’ll break down all the components (skills and connections) that make this feel like magic in the best way.

Plus: an AI ad tool, a safer way to choose AI skills, and a plot twist about an old credential that opened the wrong doors.

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Local AI Agents

Normal chatbots are great for quick writing, brainstorming, summaries, and questions. Local or workspace AI agents are different: they work on your own computer, close to your actual project and files. That means they can inspect folders, edit drafts, run checks, and keep context across a project instead of starting from a blank chat every time. They can also use your computer to do useful work:

For marketers, that can mean reviewing a landing page, updating a content brief, cleaning CSV exports, building a small calculator as a lead magnet, drafting newsletter sections, or automating reporting.

The important beginner translation: these tools are more powerful because they touch real work and real files. That also makes them less casual than a chat window. It can feel intimidating at first, but once you get used to having AI inside the actual project, it is hard to go back.

🛠️ Examples: Codex, Claude Code, Gemini CLI, Cursor, Windsurf

👉 Good starting point: put one newsletter draft, brand notes, and assets in a folder; ask the agent to improve the draft, then review every change in the document it generates.

⚠️ Watch out for: file edits, command permissions, and changes you did not review

Skills

If an AI agent is the worker, a skill is more like the playbook it follows.

A skill usually packages instructions, examples, templates, and sometimes small scripts for one repeated job. In normal-person language: instead of explaining your newsletter style, SEO process, or YouTube script structure every time, you give the assistant a reusable recipe to produce exactly that.

You can find skills in official directories, curated plugin libraries, community repositories, or inside tools like Claude Code and Codex. You can check places like Skills.sh or Skillsmp.com – there are many more online.

🤓 A useful safety trick: if you did not create the skill, ask your AI assistant to scan it for risky instructions, scripts, links, or permission requests before you decide to use it. (More on that in the “Productivity Hack” section below!)

You can also create your own by saving your best instructions, examples, formatting rules, and quality checks into a small reusable folder. The easiest way is to ask the LLM to build a skill from the prompts, examples, and files you are working with right now.

🛠️ Examples: newsletter drafting, SEO refreshes, video scripts, competitor research

👉 Good starting point: one repetitive task you already do every week

⚠️ Watch out for: hidden instructions, stale examples, and skills that ask for too much access

Tool Connections

This part sounds technical, but it is simple to understand and simple to get running: tool connections let AI talk to the apps where your work already lives.

The name you will hear is MCP, short for Model Context Protocol. The official MCP intro describes it as a way for AI apps and agents to connect with data and tools. In practice, your assistant can use Gmail, Drive, Sheets, analytics, CRMs, email marketing, or SEO data instead of guessing from memory.

Online (web-based) assistants like ChatGPT or Claude can use some connections too. Local agents such as Codex and Claude Code usually give you more flexibility because they can combine connected data with your project files and actions.

My marketing examples:

  • Brevo: pull campaign numbers into a plain-English performance summary and create a report.
  • DataForSEO: fetch keyword or SERP data and turn it into content priorities.
  • G. Sheets or Drive: read a messy spreadsheet or folder and draft a report.

Permissions matter here: start read-only, ask before changes, and remove old connections.

🛠️ Examples: Brevo, DataForSEO, Gmail, Drive, Sheets, Canva, CRMs

👉 Good starting point: connect one read-only source, like campaign stats, and ask for a weekly summary you approve before using

⚠️ Watch out for: old credentials, broad access, and tools you forgot you connected

🗳️ Be honest...

This issue is a little different from our usual format. What do you think?

✨ Totally Off-Topic… But Brilliant

This week's off-topic tool still fits the marketing mood. Creatify turns product links into AI-generated video ads, which is useful if you want more creative ideas without organizing a mini production shoot every time.

The pitch is simple: paste a product URL, let the tool generate scripts and ad concepts, then customize the output with AI actors, voices, templates, and visuals. Creatify's site focuses heavily on social ads, UGC-style formats, product videos, AI image and video ads, and competitor/ad intelligence features.

Think of it as a fast creative testing tool, not a "publish blindly" machine. AI ads still need a human review for brand voice, product claims, compliance, and whether the result feels believable. And most likely, you will want to tweak the output before using it.

Best for ecommerce brands, agencies, solo founders, and marketers who need quick ad concepts before spending time or money on production.

🛠️ Alternative to: Arcads, HeyGen, CapCut
👉 Visit: creatify.ai
💰 From $39/month | Free plan (limited monthly credits)

⚡This Week’s Productivity Hack

Before you install a random AI skill… be suspicious.

That is the hack: use skills, but inspect them before you trust them. A skill can tell your assistant how to behave, what files to read, what scripts to run, and which workflow to follow. That is exactly why they are useful, and exactly why you should be picky.

My quick checklist:

  • Prefer official, curated, or well-known sources first.
  • Read the instructions file before using the skill.
  • Check whether it includes scripts, commands, or external links.
  • Be careful with anything asking for API keys, private files, email, or broad app access.
  • Test it in a dummy folder before pointing it at real client work.
  • Remove skills and connectors you no longer use.
  • When possible, create your own skills.

Small rule: if you would not give those instructions to a freelancer without reading them, do not give them to your AI assistant unread either.

🍿 Plot Twist of the Week

The scary part of AI tool connections is not always the shiny new thing. Sometimes it is the old connection nobody remembers.

As TechCrunch reports, Klue, a competitive intelligence company, was breached after hackers used a compromised legacy credential tied to an integration tool.

That access reportedly let attackers steal data from customer cloud services, including Salesforce databases, and affected several cybersecurity companies.

For freelancers and small teams, the takeaway is simple. Review old integrations, remove access you no longer use, and do not let yesterday's experiment keep a permanent key to today's business.

That's it for this week. Thanks for reading! Next time, we'll look at practical tools that help small teams make online work feel less scattered, without turning the workflow into a second job.

Cheers,

Josep

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Hey, I’m Josep Garcia. I’ve been testing digital tools for over a decade, and we put a lot of ❤️ into this newsletter at Tooltester.
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