agentleFS
Sign inStart free
AirsupHQAirsupHQ/factory-skill/SKILL.md

factory

Skill16 starsChanged 31 days agoLicence not identifiedView on GitHub

Turn a one line description of a factory ("a line that makes 2,000 e-bike motors a day", "a bakery that bakes 10,000 croissants an hour", "a battery cell gigafactory") into a single self-contained HTML page with a live 3D tilt-shift miniature of that factory, driven by a real discrete event simulation (stations, cycle times, batches, finite buffers, shifts, breakdowns, scrap) with a live HUD for throughput against target, takt, utilization, WIP, lead time and the bottleneck, where clicking a station lets you add a machine or change a cycle time and watch the bottleneck move. Use it whenever someone wants to see, size, explain or pitch a production line, plant, assembly line, process or factory, asks "how many machines do I need", "where is the bottleneck", "can this line make N a day", wants a factory simulation or digital twin demo, or describes a product and a volume, even if they never say "simulation".

15 other projects use a version of this.

Adopted by

Most recently taken up by

Used with

Projects with it also use status and implement.

Other files people use alongside this one.

Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
  • AnthropicSkill

    status

    Case status summary by audience — client-facing (plain language), internal (for the professor), or court-ready (formal caption format per local rules). Same facts, different framing and depth. Use when a student needs to update the client, brief the professor, or prepare a court status report.

    Also in 3 projects that use this

  • Hugging FaceSkill

    implement

    Make tests pass. Invoke after /write-tests produces failing tests.

    Also in 3 projects that use this

The file

We split this skill into the rules it gives an agent

4 rules. 0 are common, 3 are distinctive, and 1 is very specific to this project.

  • 0

    Common

    Most of the 14 edited versions we read keep these.

  • 3

    Distinctive

    This author's own choices. Worth a look.

  • 1

    Very specific

    Tied to their project's names, files or tools. Probably skip.

The licence could not be identified — read it at the source. We count its rules but don't quote them. Read them on GitHub.

“Common” is measured: kept by at least 6 in 10 of the 14 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

Check your setup, free