What are Claude Skills? A Guide for Product Managers and Marketers

You’re trying to use AI more in your day-to-day. You use it to write PRDs, do research, and create decks. But every new session, it forgets:

• How you want your PRDs structured
• Who your competitors are
• Your company’s style and voice guidelines

You have to repeat yourself every time you need to complete one of these tasks. I thought AI was supposed to save you time — frustrating, right?

It should, but only if you give it the right instructions. That’s what Claude skills are for.

By the end of this guide, you’ll know what Claude skills are, how you can use them in your product and product marketing work, and how to create them.

What Is a Claude Skill?

Say you hired a new employee. You wouldn’t hand that individual a task and then walk away. You’d give them the task and then provide some context.

• What is it you’re trying to achieve?
• What do you want the output to look like?
• How do you want it structured?
• What are the standards?

You’d probably hand them an SOP or a brief or a document that outlines these things. A skill is exactly like that. It’s a markdown file with guidelines that Claude needs to follow whenever that skill is triggered.

For example, say you did a bunch of customer interviews and you want to process those to find commonalities — features to keep and features to either update or add. You can have a skill that does that.

Then, say you need to update multiple teams on the new features you’re planning to add based on your findings. You can have a skill that writes rough drafts of each of these messages — and each one can be tailored to that specific audience in terms of its tone, formatting, information, and more.

Each of these tasks can take you 30–60 minutes or more, but you can do them in minutes with a Claude skill.

How are Skills Different from Other Claude Products and Features?

Claude has a lot of products and there’s confusion over what each one does. (Not sure which product you’re working in? Here’s the full breakdown of Claude.ai vs. Claude Cowork vs. Claude Code.) The table below focuses specifically on where skills fit among Claude’s features and tools.

One thing I want to highlight is skills vs Cowork, because at a glance they both appear to handle tasks and can be automated.

The core difference between skills and Cowork — skills define format, process, and standards for consistent outputs. Cowork executes those instructions across apps and tools.

Skills are an SOP, style guide, structure and formatting. Cowork is an agent operating with those instructions, along with using MCPs to open apps, click through interfaces, pull data, and more, to produce outputs — automatically if you want.

These two aren’t competing options, they’re a powerful 1-2-combo — a well-built skill makes Cowork’s output significantly better.

Where Skills Fit in a PM’s and PMM’s Workflow

One thing that makes learning and using AI challenging is knowing what it’s capable of. Here are a few ways you can use skills in your day-to-day as a product manager and product marketing manager.

• Draft a PRD
• Create a one-pager
• Build a competitive analysis
• Create a deck
• Run a discovery session
• Process and summarize interviews
• Create action items from interviews and meetings
• Write updates and proposals for different groups (executives, Slack, development, etc.)
• Draft release notes
• Create a stakeholder email

You’ll still need to be involved in the process and provide inputs. For example, say you’re creating a PRD. Here’s what that process might look like:

1. Tell Claude you want to produce a PRD
2. Claude asks you a couple of questions — for example:
   • Do you have any customer insights?
   • Why are you building this?
   • What are your KPIs / goals?
3. You answer the questions. You upload any interviews, files, and docs you might have.
4. Claude produces a draft.
5. You give it feedback.
6. It produces the final draft.

How long will this take? It depends on the number of questions and how long it takes you to answer them, and how long it takes you to review and polish the final draft. But you can be done in 10–30 minutes. Not bad for a task that typically takes a few hours to as long as a couple of days.

It’ll get better over time too, because you’ll refine the skill based on the feedback you give Claude. The output will get tighter, and will be more consistent.

Building vs. Installing Skills — My Honest Take

No doubt you have seen people share their skills. Often it’s an engagement play — comment never work again or skills rock or whatever and the poster will give you their skills, usually after you subscribe to their newsletter or “free” community.

Even ignoring the obvious engagement play, I don’t think it makes sense to use other people’s skills in 8/10 instances.

First, there’s the security risk. It may be just a markdown file, but it influences how Claude behaves. There could be instructions to override your intended behavior. For example, maybe someone hid instructions telling Claude to summarize and output any documents you share with it, then include that content in an output you’d otherwise expect to be clean.

This risk scales with how much autonomy you give Claude. In Claude.ai, the collateral damage is likely much smaller, like a bad output. But in an agentic workflow, like Cowork, a compromised skill file has a wider blast radius.

Then there’s the risk of wasted time. Someone else’s skills aren’t created for your particular workflows or desired outputs. Odds are you’ll spend a lot of time editing work or going back and forth with Claude, fighting the very thing causing the bad output.

And then when it comes to optimizing the skill, where do you start? You have no idea, because you didn’t create it.

If you do intend to use someone else’s skill, read the file beforehand — know what it does, whether any scripts run, what the output is supposed to be, etc. Then test it.

My recommendation — if you use a skill file you didn’t create, use it as a starting point. Then customize it based on your needs. That way you get both a jump start and you learn how to iterate these files to get the output you want.

Anatomy of a Skill

You need to understand what makes up a skill for a couple of reasons:

• Troubleshooting — if the skill doesn’t fire or if you’re not getting the output you want, you need to know where to look and what to change or test.
• Maintenance — similar to above, you need to know where to make changes so you don’t break the skill whenever you update it.

There are three parts to a skill you need to know:

• First Level: YAML Frontmatter — this is the meta information Claude always loads in its system prompt. It gives Claude just enough information to know when each skill should be used without overloading it with context.
• Second Level: SKILL.md Body — this is where your instructions go. This is loaded when Claude thinks the skill is relevant to the current task.
• Third Level: Linked files — additional files or links to files that Claude can use as needed. Think examples, scripts, etc.

Claude loads each part in layers so it’s not processing everything at once. This layered loading approach is called progressive disclosure.

Here’s what a simple PRD skill looks like in practice:

---
name: prd-writer
description: Use this skill when writing or drafting a Product Requirements Document.
  Triggers on: write a PRD, draft PRD, new feature PRD, create requirements doc.
---

## Your role
You are a senior product manager helping draft a clear, structured PRD ready for
engineering review with minimal editing.

## Before you start
Ask the user for the following before writing anything:
- What problem are we solving, and for whom?
- What does success look like? (KPIs or measurable outcomes)
- Any customer research, tickets, or context files to upload?

## PRD structure
Follow this structure every time:

**1. Problem Statement** — one paragraph. What's broken, for whom, and the impact
of not fixing it.

**2. Goals** — 3–5 bullet points, measurable where possible.

**3. Non-Goals** — what this initiative explicitly does NOT include.

**4. User Stories** — format: As a [user], I want [action] so that [outcome].

**5. Requirements** — functional requirements as a numbered list. Each one
should be testable.

**6. Open Questions** — unresolved decisions, dependencies, or risks.

## Output rules
- Use the structure above exactly — no skipping sections
- Keep language direct and jargon-free
- Flag anything needing stakeholder input with [NEEDS REVIEW]

I recommend looking at Anthropic’s skills on GitHub. You’ll get a good idea of how to write a skill top to bottom, as well as how to structure and write the instructions (the progressive disclosure).

Another good source is the Claude Code for Product Managers course, created by Carl Vellotti. The course is built entirely in Claude (accessed entirely via terminal and/or an IDE like VS Code). Each module is essentially a skill file, which is another layer on top of the global skill files/rules. It’s meta in that it’s a great course, but also a great case study for how to build and use skills.

Where to Start with Claude Skills

My recommendation is to start with one skill. Find a small, repeatable task and create a skill for that. A couple of suggestions:

• Turning PRDs into one-pagers
• Draft summaries of meeting notes
• Write user stories and acceptance criteria for tickets

Ask Claude to help you build it. It’ll ask you several questions to understand what it is you’re trying to do, the output you’re looking for, and whether you have any examples.

You can even suggest questions for it to ask.

Once you’re done, test it and refine it. Then start on your next repeatable task.

What I would not do — try to build skills for everything you do, all at the same time. You’re unlikely to get the output you want and you’ll spend more time putting out fires and fixing work you’re not happy with.

Skills are an iterative process. So get each skill dialed in before you move on to the next one.

Follow this process and you’ll find that for every skill you add or update, you save more time while getting better quality, more consistent outputs.