How to Share AI Workflows So Other People Can Run Them

To share an AI workflow so someone else can actually use it, package it in the format of the tool it runs in (a shared Claude Project, a Claude skill or plugin, a ChatGPT plugin, an exported n8n workflow or a Zapier template), or publish it as a runnable app so the other person doesn't have to rebuild your setup. Before you send anything, strip out your API keys, list what the workflow depends on, and include one example run.

Sending a prompt in a chat message almost never works. The prompt is the visible 10% of the workflow. The rest is your context, your keys, your files and your tools, and none of that travels with a copy-paste.

Here's the short version:

• Your team uses Claude: share a Project, or share a skill.
• Your team uses ChatGPT: share a plugin (custom GPTs are being moved to plugins).
• The workflow is an automation: export the n8n JSON or make a Zapier guided template.
• The other person isn't technical: publish it as an app they can run, edit and keep.

Why an AI workflow breaks when you share it

You built something that works. You send it to a colleague. They get an error, or worse, a mediocre answer, and they assume the workflow is bad.

It usually isn't. The workflow was leaning on four things that only exist on your side:

Every sharing route below is really an answer to one question: which of these four does the route carry for you, and which does the other person have to supply?

How to share an AI workflow: 5 routes

1. Share a Claude Project with your team

If the workflow is mostly instructions plus a few reference documents, a Claude Project is the simplest container. According to Anthropic's guide to Projects, sharing is a Team and Enterprise feature. You can share a project with specific teammates by email or make it available to everyone in your organization.

There are two permission levels:

• Can view: people see the project's knowledge and instructions and can chat inside it, but can't change it.
• Can edit: people can change instructions and knowledge and manage members.

Use Can view for a finished workflow you want people to use as-is. Use Can edit when you want help improving it.

The catch: Projects stay inside your organization. You can't hand one to a client or a friend on a different account, and a Project can't call your local scripts.

2. Share a Claude skill (zip, org library or plugin marketplace)

A skill is a folder with a SKILL.md file of instructions, plus any scripts or reference files the task needs. If you're new to them, start with our Claude skills explainer. Skills are the most portable way to share a Claude workflow, and there are three main routes.

In the Claude apps. Anthropic's skills help article says anyone on Free, Pro, Max, Team or Enterprise can upload a skill as a ZIP for personal use. Sharing goes further on Team and Enterprise: you can share a skill with specific people or a group, submit it to your organization's library, and admins can provision skills so they appear for everyone.

In a code repository. Claude Code loads skills from .claude/skills/ in a project, and its skills documentation tells you to commit that folder to version control so your team gets it too. Anyone who clones the repo gets the skill.

Through a plugin marketplace. For a wider audience, wrap the skill in a Claude Code plugin and list it in a marketplace. Per Anthropic's marketplace docs, a marketplace is a git repository with a .claude-plugin/marketplace.json file that lists your plugins. Push it to GitHub, and other people register it with claude plugin marketplace add owner/repo and install your plugin by name. If the repo is private, only people who can clone it can install from it.

One more reason to package your work as a skill: Claude Code skills follow the Agent Skills open standard, so the core of a skill isn't locked to one app.

3. Share a custom GPT, and the plugin alternative

For a long time, a custom GPT was the default way to share a ChatGPT workflow. That's changing. OpenAI's custom GPT migration guide, written for ChatGPT Enterprise workspaces, says OpenAI is transitioning custom GPTs to plugins and that custom GPTs will eventually be retired.

What that means if you're sharing:

• A plugin is the new package. It can hold skills (instructions and reference files) and apps (connections to other services).
• Your GPT's instructions become a skill. Knowledge files come along. Custom actions don't transfer and need to be rebuilt, for example with a supported app or a custom MCP server.
• Sharing doesn't carry over. The new plugin starts private. You share each replacement manually, and the people you share it with still have to install it.
• Permissions stay personal. A plugin works with the app access the user already has. It doesn't hand them yours.

So if you're searching for a custom GPT alternative to share, the honest answer is that OpenAI's own replacement is a plugin built around a skill. If your team works in both Claude and ChatGPT, writing the workflow as a skill first gives you the most reusable starting point.

4. Share an automation: n8n JSON and Zapier templates

Automations are easier to share in one way and harder in another. The steps travel cleanly. The connections never do.

n8n. The n8n export and import docs give you three practical options: copy and paste the nodes, download the workflow as a JSON file, or import from a file or URL. The docs also carry a warning worth taking seriously: the exported JSON includes credential names and IDs, and an HTTP Request node imported from cURL may contain authentication headers. Remove or anonymize those before you share. The recipient then connects their own credentials.

Zapier. If you share Zaps with a link, check your method. Zapier says shared Zap templates will be deprecated on December 15, 2026, and new ones can no longer be created. The replacement is a guided template, which walks the other person through setup and lets you choose which fields they can edit. You can share it with specific people on your account or through a link. The recipient connects their own app accounts, and they won't use your app connections.

That last point is a feature, not a limitation. Nobody should be running an automation on your Gmail.

5. Publish it as a runnable app

Every route above assumes the other person is willing to set something up: a Claude seat, a repo clone, a plugin install, a set of credentials. For a technical teammate, fine. For a client, a friend or a non-technical colleague, that setup is exactly where the workflow dies.

The alternative is to publish the workflow as an app that someone can run without rebuilding your environment. That's the route Taku takes. Creators publish to Taku with the Taku Publisher plugin from Codex, Claude Code or Cursor, and the work appears in the Taku marketplace. Other people can run it, edit it and save it as their own in a desktop workspace.

The marketplace is early. It carries free and paid apps, and creators have public profiles. If you're wondering how creator rewards work, they're set out in Taku's publisher terms, which don't promise sales or cash payouts.

Before you share: a 5-point checklist

Whatever route you pick, run through this list first. It takes ten minutes and saves the "it doesn't work for me" message.

1. Strip secrets and API keys. Search the workflow for keys, tokens, passwords, webhook URLs and personal email addresses. Check config files, .env files, HTTP headers and node settings, not just the prompt. If you ever pasted a real key into something you shared, rotate the key.

2. List the dependencies. Write down the model it was tested on, every app or account it connects to, any MCP servers or local scripts, and any files it expects. If it needs a paid account somewhere, say so up front.

3. Write down inputs and outputs. One line each: what the user provides ("a CSV of leads with a company column") and what they get back ("a ranked list with a one-line reason per lead"). This is the single most useful thing you can add.

4. Choose a licence. If you share publicly, tell people what they can do with it. Choose a License explains the common options in plain English, and the Agent Skills format has a license field for exactly this.

5. Add an example run. Include one real input and the output it produced. It shows the workflow works, sets expectations about quality, and gives the other person a test they can repeat after they change something.

If you want the workflow to be worth sharing in the first place, our guide to reusable AI workflows covers how to turn a one-off chat into something that runs the same way twice.

FAQ

How do I share an AI agent with my team?

Use the container your team already works in. On Claude Team or Enterprise, share a Project or a skill, or have an admin provision the skill organization-wide. On ChatGPT Enterprise, share a plugin under your workspace permissions. For a developer team, commit the skill to the repo or publish a plugin marketplace. Whichever you pick, make sure each teammate has the accounts and app access the agent needs.

Can I share a Claude skill with someone outside my organization?

Yes, but not through the in-app share menu, which works within a Team or Enterprise organization. For someone outside, send them the skill folder or a ZIP to upload themselves, or publish it in a public GitHub repo as a Claude Code plugin marketplace they can add.

Is there a way to share a workflow without giving away my API keys?

Yes. That should be the default. Zapier guided templates never use your app connections, Claude and ChatGPT sharing runs on each user's own account, and n8n leaves credentials for the recipient to connect. The risk is keys you hard-coded yourself, inside a script, a header or a prompt. Strip those before you share.

What's the best custom GPT alternative for sharing a workflow?

For ChatGPT Enterprise workspaces, OpenAI's own answer is a plugin, with your GPT's instructions turned into a skill. Outside ChatGPT, a Claude skill is a strong choice because it follows the open Agent Skills standard. If the people you're sharing with won't set anything up, publishing a runnable app is the simpler route.

Why does my shared workflow give worse results for other people?

Usually because it lost context: your custom instructions, memory, reference files or a specific model. Put that context inside the shared package as instructions and reference files, state the model you tested on, and include an example run so people can tell whether they're getting the intended output.

Can people edit a workflow I share?

It depends on the route. A Claude Project shared with Can view can't be edited, while Can edit allows changes. An exported n8n file or a cloned skill becomes the recipient's own copy. A Zapier guided template only lets them edit the fields you choose. On Taku, people can edit an app and save it as their own.

Key points

• A workflow is more than its prompt. It's context, keys, files and tools, and sharing only works if you package all four or tell people what to supply.
• Claude Projects and in-app skill sharing are for people in your Team or Enterprise organization. Skills in a repo or plugin marketplace reach anyone who can access the repository.
• Custom GPTs are moving to plugins. OpenAI's guide says sharing settings don't carry over, so each replacement has to be shared again.
• Automations share steps, not connections. Sanitize n8n JSON, and move from shared Zap templates to guided templates before December 15, 2026.
• Run the checklist before you send anything: no secrets, listed dependencies, clear inputs and outputs, a licence and an example run.

If the people you want to reach are never going to clone a repo or install a plugin, that's the gap Taku is built for. Creators publish a working setup with the Taku Publisher plugin, and other people can run it, edit it and save it as their own in a desktop workspace. Taku is in Beta, and the Mac app is available now.