Anthropic’s New Claude Skills: Teaching Your AI Reusable Workflows Without Losing Your Mind

Last month Anthropic quietly dropped something that made my coffee go cold on my desk: Claude Skills becoming an open standard for teaching AI reusable workflows across tools and platforms.[5] My inbox was already a mess of “AI update” newsletters, but this one actually changed how I set up my day-to-day work.

New Feature / Update: Claude Skills as an Open Standard

What is it?

In simple terms, Claude Skills let you teach Claude a repeatable workflow, save it as a named “skill”, then reuse it whenever you want.[5] Think of it like creating a template brain for specific tasks instead of explaining the same thing to your AI every single morning with half a croissant in your hand.

The important bit for automation nerds is this: Anthropic has opened the Skills format as a standard, so these defined workflows can be portable and used across different tools and platforms that adopt it.[5]

In practice, a skill is usually a small set of:

• Instructions for how the AI should behave for a task
• Inputs it expects, like a brief, a CSV export, or a meeting transcript
• Outputs that are predictable enough to plug into other tools

I tried it first with a very boring but very real workflow: turning messy brainstorm notes in Notion into a neat campaign brief. Instead of retyping my “how I like briefs” rant every time, I saved it as a skill and now I just call it when I need it.

Key facts at a glance

Why does it matter?

I spend too much time copy pasting “my way” of doing things into different AI tools. ChatGPT for writing, Canva for assets, Zapier for glue, Notion AI for quick drafts. Every tool wants me to explain myself again like it is a first date.

Claude Skills do not magically fix all of that, but they move work from one-off chatting to reusable building blocks. And because the format is open, those blocks can be wired into real workflows.[5]

Here is why that matters in normal human work, not just in AI-land marketing slides.

Use case 1: Campaign briefs on autopilot (for marketers and content teams)

Last Tuesday, I watched a friend who runs a small agency try to stitch together a product launch brief. She had:

• Slack screenshots from a client call
• A Google Doc with half-baked positioning
• Three Canva moodboards titled “final”, “final v2”, and “actual final”

Her current workflow with AI was very comme ci, comme ça. She would open ChatGPT, paste a chunk of context, type a long prompt, tweak the tone, then try again next week from scratch because she forgot what worked.

With Claude Skills, she can define a single “Campaign Brief Skill” that expects:

• Inputs: target audience notes, product features, launch date, channel list, screenshots of client notes
• Process: extract key facts, resolve contradictions, highlight unknowns, then structure into a standard brief format
• Output: a clear brief with sections for background, goals, audience, messaging, channels, deliverables, timeline

Then, instead of a new mega prompt every time, she just:

• Dumps her raw notes from Slack and Google Docs into Claude
• Calls the “Campaign Brief Skill”
• Gets a consistent brief that is close enough to start work

The quiet win is consistency. Her team can share that same skill with freelancers, so everyone is working from the same structure instead of reinventing the brief with each project.

I will admit I was sceptical at first. My own prompts are chaotic and slightly dramatic. The first time I tried to turn my briefing style into a skill, it was too rigid. I had to iterate a few times so it would still leave space for nuance. The nice part is that once you get over that setup hump, it saves real brain space.

Use case 2: Data review on rails (for analysts and operations folks)

On Wednesday afternoon my laptop was doing its little fan opera while I exported a chunky CSV from Shopify. Typical ecommerce scene. A friend who runs operations for a mid sized brand wanted to:

• Spot low stock items
• Identify products with high returns
• Prepare a quick summary she could paste into Slack for the founder

Her usual setup involved Google Sheets formulas, a bit of Looker, and some swearing. She uses AI sometimes but never the same way twice. It depends on which tab is already open.

Here is what a Claude Skill can do in that scenario:

• Input: latest CSV export from Shopify with columns for product, stock, sales, returns
• Logic: apply a consistent checklist every time
• Output: a summary plus a short, plain English recommendation section

For example, the skill might always:

• Flag items below a certain stock threshold
• Calculate return rate by SKU and highlight the worst offenders
• Draft a Slack ready summary: what to reorder, what to review, and what to stop promoting

Because Skills are defined in a structured way, they can be plugged into tools like Zapier, Make, or Pabbly Connect once the ecosystem catches up. That is where it gets interesting for automation:

• New Shopify data triggers a Zap
• The Zap calls Claude with your inventory review skill
• Claude returns a neat summary that is auto posted into a Slack channel

Is it perfect? Non. Sometimes the AI over explains simple points or misses a weird edge case in the data. I found that I still skim the CSV directly for high stakes decisions. But for day to day “what should I look at first” triage, the skill feels like an extra ops assistant who does not call in sick.

Use case 3: Less soul destroying reporting (for agencies and freelancers)

If you are in agency land, you probably spend an unhealthy number of Thursday nights in Google Slides rushing out “monthly performance reports”. My own personal low point was copy pasting graphs from Google Analytics into a deck at 11 pm, then manually summarising them in three different client tones.

With Skills, you can define a standard “Client Report Skill” that:

• Takes as input: exported charts, KPI snapshots, and any notes from the last client call
• Applies rules: highlight what actually changed, not just “impressions are up 2.3 per cent”
• Outputs: a short summary for the email body plus a slide outline you can drop into Canva or PowerPoint

The repeatable part is key. You can tweak the skill per client, but you are no longer starting from a blank page every month. You call the same skill, get the same structure, then adjust details.

I still have mild trust issues here. Sometimes the AI description of a chart is technically right but misses the real story you know from context. I use the skill as a first draft and then layer in human judgement. It turns a 2 hour slog into a 30 minute clean up.

How this plays with the rest of your stack

Skills really start to earn their keep when you thread them into the tools you already live in. Here are some practical patterns that feel realistic, not sci fi.

With Zapier, Make, or Pabbly Connect

• Auto summarising call transcripts: Pull transcripts from Zoom or Google Meet, feed them into a “Client Call Summary Skill”, and post the result to a Slack channel and a Notion page.
• Syncing inventory with Shopify: Schedule a daily export through your data tool, run it through an “Inventory Risk Skill”, then send a short list of SKUs to review to your ops team.

With writing and creative tools

• Jasper or Copy.ai for drafts, Claude Skill for QA: Use your existing writing tool to generate ad copy, then run the results through a “Compliance and Tone Check Skill” in Claude to catch risky claims or off brand phrasing.
• Canva: Use a “Social Caption Skill” to create on brand captions from your Canva asset descriptions so you are not reinventing your tone on every post.

With data and coding tools

• GitHub Copilot to write code, Claude Skill to review: Set up a “Code Review Skill” for specific standards, like logging, error handling, or accessibility, then run diffs through it before pull requests.
• Deepnote or other notebooks: Use a “Notebook Summary Skill” to turn a messy analysis into a clean narrative your stakeholders can read without crying.

What to watch out for

It is not all croissants and clean workflows. A few rough edges I have hit or seen others trip over:

• Overfitting to your quirks: My first skills sounded like my most tired, over caffeinated self. It is tempting to bake in every preference, but that can make outputs brittle. Keep skills focused on structure and leave some room for improvisation.
• Version chaos: If you create “Campaign Brief Skill v1”, then “v2”, then “final”, you will confuse your future self and your team. Treat skills like real templates with simple version labels.
• Hidden assumptions: Skills can quietly encode assumptions that do not age well, like a default channel mix or audience definition. Add a small “assumptions” section inside the skill instructions so you remember to review them.

How to start without burning your weekend

If you are curious but low on energy, here is a very practical starting point that fits into a normal work week.

Step 1: Pick one task you repeat weekly

Some ideas:

• Generating campaign briefs from messy meeting notes
• Summarising sales calls for your CRM
• Preparing a short performance update for your boss or a client

Step 2: Write how you do it, as if you are training a junior

Open Claude and literally describe your process in plain English:

• What inputs you look at first
• Which parts you ignore
• How you structure the final result

Yes, it feels a bit “dear diary” at first. My pencil had opinions when I did this. But this becomes the skeleton for your skill.

Step 3: Turn that into a structured skill

Work with Claude to convert your description into:

• A clear name, like “Weekly Performance Snapshot Skill”
• A predictable input format, even if it is just “paste your notes here”
• A consistent output structure with headings

Run it on two or three old examples to see where it falls apart. Adjust. Try again. This part is a bit fiddly, but you only do it once.

Step 4: Use it for three weeks before you judge it

I nearly abandoned my first skill after day two. It felt slower than just prompting directly. By week three, it clicked. I knew exactly what to feed it and where I still needed to edit. That is the moment where the time savings show up.

Where this fits in the AI and automation puzzle

Anthropic opening up Claude Skills as a standard is part of a broader shift toward agentic AI, where AI agents coordinate more complex workflows instead of just answering questions.[5] Tools across the ecosystem are evolving in that direction, from enterprise agent frameworks to open protocols.

You do not need to care about the jargon to get value. For most of us, the practical takeaway is simple:

• Stop treating every AI interaction as a one off chat
• Start capturing your favourite workflows as reusable skills
• Gradually wire those skills into the automations you already use

If you have ever opened your laptop on a Monday, stared at a blank Google Doc, and thought “surely the robots can help more than this”, Claude Skills are one concrete step in that direction. Not perfect, not magic, but practical enough to earn a spot next to your other tabs.