agentleFS
Ar9avAr9av/framesmith/skills/archive-launch-film/SKILL.md

archive-launch-film

Skill1 starsChanged 49 days agoLicence not identifiedView on GitHub

Render a narrated archive-to-product launch film (about 60–90 s, 16:9). A dark documentary cold open plays single words synced to the voice over a falling dotted chart, archival engravings made with gpt-image-2, cutaway line drawings whose interiors flood yellow to red, and a document where everything greys out except one line that a highlighter sweeps. Black then dawns into a drifting pastel ground for a chrome-object brand reveal and light product UI driven by a cursor (live activity, cloaked secrets, approvals, a signed policy, audit records). Enterprise beats add a fleet wall that pulls back from one device to hundreds, a holographic "Enterprise" reveal on black, a terminal enroll with a device table, console panels, and an end card with the open source repo. Use when the user wants a launch film that opens on history or a documentary hook, "start with Titanic/Troy style failures then reveal the product", or a security or infrastructure product story told from past failures to the fix.

  • Reads credentials

The file

We split this skill into the rules it gives an agent

2 rules. About 0 are common, 0 are distinctive, and 2 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈0

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 2

    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 an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “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.