agentleFS
kovrichardkovrichard/catalyst/.agents/skills/next-partial-prefetching-adoption/SKILL.md

next-partial-prefetching-adoption

Skill470 starsChanged 7 days agoNo licenceView on GitHub

Turn on Partial Prefetching in a Next.js app and work through the insights it surfaces. Use when the user wants to enable or adopt Partial Prefetching, flip the `partialPrefetching` flag, opt routes in with `export const prefetch = 'partial'`, audit `Link prefetch={true}` behavior, preserve existing prefetched UI with `instant()` tests, or resolve the instant-link-prefetch-partial and instant-shell-url-data insights.

10 other projects use a version of this, 10 of them edited.

Adopted by

Most recently taken up by

Used with

Projects with it also use create-vercel-ai-issue, dev-auth-bypass and 10 more.

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.
  • FranciscoMorettiSkill

    create-vercel-ai-issue

    Create a well-formed GitHub issue in vercel/ai using the gh CLI. Use when reporting an AI SDK bug or preparing an issue body that contains logs, code blocks, versions, reproduction steps, and shell-sensitive text.

    Also in 3 projects that use this

  • FranciscoMorettiSkill

    dev-auth-bypass

    Authenticate a browser against a local ChatJS app without OAuth. Use for development login, local auth bypass, authenticated browser or Playwright testing, and the /api/dev-login route.

    Also in 3 projects that use this

  • +10 more from FranciscoMoretti

The file

We split this skill into the rules it gives an agent

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

  • 1

    Common

    Most of the 10 edited versions we read keep these.

  • 4

    Distinctive

    This author's own choices. Worth a look.

  • 3

    Very specific

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

No licence file, so all rights are reserved — 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 10 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.

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  • 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.