agentleFS
nessalaznenessalazne/youtube-agent-skill/skills/yt-seo/SKILL.md

yt-seo

Skill5 starsChanged 53 days agoMITView on GitHub

Write the description, tags and search-facing text for a YouTube video, aimed at the query a real person types. Use for "write my description", "tags", "SEO", "help this video get found", "nobody is finding this".

6 other projects use a version of this, 4 of them edited.

Adopted by

Most recently taken up by

The file

We split this skill into the rules it gives an agent

5 rules. 0 are common, 2 are distinctive, and 3 are very specific to this project.

  • 0

    Common

    Most of the 6 edited versions we read keep these.

  • 2

    Distinctive

    This author's own choices. Worth a look.

  • 3

    Very specific

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

  • Common
  • Distinctive
  • Very specific
  1. Very specific:

    Search is a smaller lever than packaging and a bigger one than people think for evergreen videos.

    line 11
  2. Very specific:

    Read ~/.claude/youtube/voice.md if it exists.

    line 16
  3. Distinctive:

    Never invent a number, a result or a source.

    line 21
  4. Distinctive:

    Before handing anything over, write the three search queries this video should win, and check the title and first two description lines …

    line 43
  5. Very specific:

    If they want it on the channel, /yt-publish is the only skill in this pack that touches YouTube, it uploads private unless they say …

    line 52

“Common” is measured: kept by at least 6 in 10 of the 6 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.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

yt-seo

Search is a smaller lever than packaging and a bigger one than people think for evergreen videos. For a video aimed at the subscriber feed, say so and spend the effort on /yt-package instead.

Before you write

  1. Read ~/.claude/youtube/voice.md if it exists. That is the user's voice profile: how they talk on camera, the words they never use, who they are talking to, what they will not claim. If it does not exist, ask for three of their own videos, read or transcribe them, infer the voice, and write the file. A script in the wrong voice is worse than no script, because they have to read it out loud.
  2. Never invent a number, a result or a source. If a figure would strengthen it and you do not have one, ask for it or write the line without it.

The description

  • The first two lines are the only ones anyone reads. They show above "...more" and they are the search snippet. Say what the video gives them, in the words they would have typed.
  • Then the link or the resource, if there is one, so it is above the fold.
  • Then chapters (/yt-chapters writes them).
  • Then the long version: what is covered, who it is for, what it assumes.

Tags, honestly

Tags are a weak signal and YouTube has said so. Use them for disambiguation - spellings, the tool names, the abbreviations people actually type - and stop. Fifteen is plenty. A wall of tags is not a strategy and stuffing unrelated ones is against the terms.

Save the finished description to a file. It is what /yt-publish takes as --desc, and YouTube caps it at 5,000 characters.

The query test

Before handing anything over, write the three search queries this video should win, and check the title and first two description lines contain the words in those queries. If they do not, the problem is the title, not the description.

The gate

This skill never publishes. Every output ends in a block the user copies, and the last line of every run is the question: ship it, or change it?

If they want it on the channel, /yt-publish is the only skill in this pack that touches YouTube, it uploads private unless they say otherwise, and it asks again before it does anything.

Download now (ZIP)

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.