I Let an AI Agent Prep My Workshop. Prep Took 20 Minutes.

A developer built a workflow that lets an AI agent prepare a workshop in about 20 minutes by making prep materials machine-readable: each activity folder ships a SKILL.md file with frontmatter (name, group size, duration, props) plus runnable prep commands, so an agent can discover, install and run the prep without chat explanation. The workflow pairs with FormLM's open-source CLI and MCP server, installed via `npx -y @formlm/cli mcp`, which lets the agent generate a registration form, pre/post measure and feedback form with live URLs. The developer reports that a single prompt produced a props checklist, print specs, a run sheet summary and three live form URLs.

Series: How to Run a Workshop People Remember 7/10 Workshop prep is the part nobody teaches and everybody dreads: read the run sheet, list the props, check print specs, build the sign-up and feedback forms, write the invite. It's all mechanical work that takes an evening — which is exactly the kind of work an AI agent should be doing while you do the human parts. The blocker was always that AI couldn't see your materials. It could draft you an email, but it couldn't open your activity folder, know the group size, count the props, or tell you that the A3 poster needs a color printer. So I made the materials machine-readable, and this post shows the workflow — because it generalizes to any prep materials you keep in files. Every folder on WorkshopSkill https://workshopskill.com/en/ ships with a SKILL.md file — frontmatter name, description, group size, duration, props plus runnable prep commands. The point of the format: an AI agent that can read files can discover the activity, install it, and run the prep without you explaining any of it in the chat. The three-step workflow, in practice: files/SKILL.md at a predictable URL — The skills-for-agents page https://workshopskill.com/en/skills.html documents the workflow for humans, and the skill tutorials https://workshopskill.com/en/skill-guides/ walk through it per client and per scenario 28 tutorials at time of writing — Claude, Cursor, and the rest, each with its quirks . There's also a plain guide on AI agent workshop prep https://workshopskill.com/en/guides/ai-agent-workshop-prep/ for the concept without the tooling. The prep checklist has always ended with the annoying tail: "build the registration form, build the pre/post measure, build the feedback form." Those are all form-shaped, and form-building is now an MCP-shaped problem. FormLM ships an open-source CLI and MCP server the npm package @formlm/cli https://www.npmjs.com/package/@formlm/cli . If you use Claude, Cursor or any MCP-compatible client, the whole install is: npx -y @formlm/cli mcp One command, stdio transport, no API keys to wire up — a client with no token signs in through the chat. Then your agent can build the workshop's forms and assessments as part of the same prep session: describe the pre/post measure once, get the live scored form, the registration page and the feedback form — each with a URL you can drop onto a printed card part 3 or into the invite email. So the whole prep conversation with the agent ends up being one message: "Install the blind-portrait folder from skills.json, give me the prep checklist, then build the registration form and the pre/post measure on FormLM for my 16-person session Thursday." Twenty minutes later you have: props checklist, print specs, a run sheet summary, and three live form URLs. The evening you would have spent on this is now the evening you spend rehearsing the debrief questions — the part that actually decides whether the workshop is any good. Next in the series: the debrief — the beat where the learning actually happens, and the one most workshops skip. Tools in this post: npx -y @formlm/cli mcp Disclosure: I'm one of the makers — the tools from my own shop named across this series.