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Ootto-AIOotto-AI/claude-content-skills/skills/content-audit/SKILL.md

content-audit

Skill417 starsChanged 3 months agoMITView on GitHub

Reviews your last 30 posts to find what is worth doubling down on, what is dead weight, and the gaps to fill. Use when the user says "audit my content", "what is working on my account", "what should I stop posting", "review my last 30 posts".

25 other projects use a version of this.

Adopted by

Most recently taken up by

Used with

Projects with it also use asset-spec, create-control-manifest 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.
  • lilangMaxSkill

    asset-spec

    Generate per-asset visual specifications and AI generation prompts from GDDs, level docs, or character profiles. Produces structured spec files and updates the master asset manifest. Run after art bible and GDD/level design are approved, before production begins.

    Also in 10 projects that use this

  • lilangMaxSkill

    create-control-manifest

    After architecture is complete, produces a flat actionable rules sheet for programmers — what you must do, what you must never do, per system and per layer. Extracted from all Accepted ADRs, technical preferences, and engine reference docs. More immediately actionable than ADRs (which explain why).

    Also in 10 projects that use this

  • +10 more from lilangMax

The file

We split this skill into the rules it gives an agent

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

  • 0

    Common

    Most of the 24 edited versions we read keep these.

  • 2

    Distinctive

    This author's own choices. Worth a look.

  • 0

    Very specific

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

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Before making more, work out what to stop.

    line 23
  2. Distinctive:

    Honesty: Every multiple must come from the numbers pasted in.

    line 45

“Common” is measured: kept by at least 6 in 10 of the 24 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

Content Audit — what to double down on, and what to stop

Reviews your last 30 posts to find what is worth doubling down on, what is dead weight, and the gaps to fill.

When to use

Before making more, work out what to stop.

What you'll need

Your last 30 posts with views, saves, comments and shares. The Ootto MCP or your Instagram insights export.

Instructions

Give Claude the input and run this.

You are my content analyst. Here are my last 30 posts with their numbers: [paste].

1. MEDIAN FIRST: state my median views/saves so everything is judged against ME, not someone else.
2. OUTLIERS: the posts that beat it, and the trait they share.
3. DEAD WEIGHT: formats or topics I keep making that consistently underperform. Name them plainly.
4. BY TRAIT: score hook style, length, format and topic, each with its real multiple vs median.
5. STOP / KEEP / TEST: three short lists.
6. NEXT FIVE: five posts to make, each justified by a number above.

If a pattern isn't in the data, say "not enough signal" rather than guessing.

Honesty: Every multiple must come from the numbers pasted in. No estimated figures, and no advice that contradicts my own data.

Next: content-pillar-builder → content-calendar

Built by Ootto — the AI autopilot that connects your tools once and runs the busywork for you, automatically. Book a demo →

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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
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  • 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.

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