Yesterday a clever little build shipped on r/PromptEngineering. It’s called Philosopher Skill (Phil-OKF), and the pitch is simple: stop reading walls of AI text and get a proper study page instead. If you’ve ever asked a model to explain something, scrolled through twelve paragraphs, and come out the other side remembering nothing, this one is aimed squarely at you.
What’s new
You give your LLM a topic. Instead of a long chat reply, it builds a clean, readable guide page for that topic. Think headings, short sections, and a structure you can scan in a minute before you decide whether to dig in. The whole thing follows OKF, the Open Knowledge Format, which is a consistent way of laying out knowledge so the page looks and behaves the same no matter what you ask about. The author shared a sample that explains MCP and ACP, so you can see the output before you install anything.
That consistency is the real leverage. When every page has the same shape, your brain learns where to look. You stop hunting for the definition, the example, or the “so what,” because they always live in the same place. Chat replies never give you that, because every answer is shaped a little differently.
The twist
Step 2 is the surprise. This isn’t an app. It’s a tiny bundle of files: an eight-step workflow, a domain classifier, a page template and twelve study domains. The model only reads the file it needs for your question, so runs stay cheap. Ask about a programming concept and it pulls the matching domain. Ask about history or science and it grabs a different one. Nothing else gets loaded, which keeps your context window free for the actual content.
And you control the depth just by how you word the request:
- “quick” gives you a short page
- a normal question gives you a standard page
- “in depth” or “teach me” gives you a long one
No settings screen. Your wording is the dial. A few examples of how that plays out: “quick: what is retrieval augmented generation” gets you a page you can finish over a coffee. “How does retrieval augmented generation work” gets the standard version. “Teach me retrieval augmented generation in depth” gets the full walkthrough with more background and more worked detail.
Mini-workflow
🧭 Pick your setup:
- Code editors and agents (Claude Code, Cursor, Codex, opencode): run npx skills add frypan05/philosopher-OKF
- Chat apps with browsing: paste the link to philosopher.md from the repo and say “follow this, make a page about: …”
- Models with no network: paste the prompt from the project page
If you’re not sure which route fits, start with whatever you already use daily. The install route is the smoothest because the skill sits in your tools and loads on demand. The link-paste route works well when you’re on a phone or a borrowed machine.
📚 Ask for a topic, like “teach me how vector databases work.” Be specific about what you want to walk away with. “Teach me how vector databases work so I can choose one for a small project” will give you a more useful page than the bare topic alone.
🔍 Open the page the model builds and read it top to bottom. Resist the urge to skim for the one line you think you need. The structure is built to be read in order, and the early sections usually set up the vocabulary that makes the later ones click.
✅ Check the claims that matter against a source you trust. Pick the two or three statements your decision or your work depends on and confirm those. You don’t need to audit every line, just the load-bearing ones.
Pro tips
- Start with “quick” to see if the topic is even worth your time, then re-ask with “in depth” for the ones that are. This saves you from generating long pages you never finish.
- Open the MCP and ACP sample first. It shows you what good output looks like, so you can tell when your own run falls short. If your page is missing sections the sample has, that’s a sign the model skipped part of the workflow, and you can simply ask it to follow all eight steps.
- Keep a folder of the pages you like. Because the format is consistent, a collection of them turns into a personal reference library you can reread, which is far better than digging through old chat logs.
- Don’t skip the verification step. One commenter on the thread raised the sharpest point: the hard part isn’t generating the content, it’s knowing the output is correct for a given field. A pretty page can still be wrong. Treat it as a well-organized first draft, not a final authority. For anything medical, legal, or financial, treat the page as a map of questions to take to a real source.
The early reactions were friendly. People liked that it cuts the 37-tab spiral and that it stops the AI from burying you in so much info you end up more confused than when you started. Several readers also pointed out how little it costs to try, since there’s nothing to sign up for and nothing running in the background.
The repo is at github.com/frypan05/philosopher-OKF, and the author is asking for feedback. Try it on one topic you’ve been putting off and see if the page sticks better than the chat reply did. 🚀
Frequently Asked Questions
Q: How can a learner check that the content is actually correct?
One commenter pointed out that the harder problem is knowing whether the output is right for a given field, and that’s fair. Ask the model to name its sources and flag anything it’s unsure about, then check the key claims against official docs, specs, or a textbook before you rely on them. For technical topics, treat the page as a study map and verify the facts you’ll actually use in your work or exams.
Q: Where can I use it?
In a code editor or agent like Claude Code, Cursor, Codex, or opencode, run npx skills add frypan05/philosopher-OKF. In a chat app that can browse, paste the link to philosopher.md and say “follow this, make a page about” your topic. If the model has no network access, paste the prompt from the project page instead.
Q: Is this better than just asking the AI in a normal chat?
Readers in the thread liked that the output is one clean page instead of a wall of text or a pile of open tabs. Plain chat is still fine for a quick answer. Use the page when you want to study a topic properly and come away remembering why you started.
Philosopher Skill: Learn about almost any domain with a simple to read and understand UI.
by u/holyshitthatsucks in PromptEngineering