Yesterday someone who spent a year in TikTok Shop creator operations shipped something actually useful. Not a course. Not a PDF. A free, open-source three-layer Claude Skill that pulls knowledge out of your head and turns it into something other people can use.
Step 2 is where it gets interesting.
What shipped
The system is called experience-to-asset. Three layers, each doing one job:
🗂️ Layer 1 (experience-to-asset): Lowers the barrier. Shows you the frame before asking you anything. Figures out what you have and where to go. Think of it as an orientation call before the real work starts. It asks enough to understand your context, then routes you to the right next step instead of dumping a blank canvas in your face. Most people quit knowledge capture tools in the first five minutes because the opening question is too broad. This layer fixes that.
Layer 2 (experience-deep-extract): Pulls out your real stories, judgment calls, and mistakes. One question at a time. Conversational, not an interrogation. Combines what you say with documents you upload. So if you have a Notion doc, a Slack archive, a process doc from a previous job, or even a voice memo transcript, you can feed it in. The AI uses those artifacts to ask better follow-up questions and fill in gaps. It’s not just listening to you. It’s reading your notes and asking about the parts that seem incomplete.
📦 Layer 3 (experience-package-build): Matches your content to the right output format. Follows Audience → Value Promise → Content Density → Format → Build. Then generates the actual deliverable.
Outputs: SOP doc, Excel toolkit, PDF guide, interactive website, or article framework. The format selection isn’t arbitrary. It’s based on who will consume the thing and how. A field-ops checklist and a thought leadership article need very different containers. Layer 3 figures that out before it builds anything.
The twist
Most knowledge capture tools fail at the same thing: they ask you to dump everything at once. Brain dump, then we’ll organize it. This one slows down. One question, then the next. That pacing is what gets the tacit stuff out.
There’s a reason for this. When someone asks you to explain everything you know about a job, you give them the official version. The clean story. When someone asks you a specific question about a specific situation, you give them the real version. The one with the workaround you figured out at 11pm on a Friday. The one with the client you almost lost and what you actually said to pull it back. That’s the version worth packaging, and it only comes out through sequential, patient questions.
The core idea here is worth sitting with. You don’t need to be the world’s foremost expert. You need to be 2-3 steps ahead of someone who was where you were a year ago. Your workarounds, your mistakes, your hard-won judgment calls, none of that exists in any AI’s training data. That’s the gap. That’s what makes it worth packaging.
A year in TikTok Shop creator operations means you’ve seen creator onboarding go sideways in ways no blog post covers. You know which metrics actually predict whether a creator will ghost you. You know what the contract clause everyone ignores actually means in practice. That specific, situational, hard-to-Google knowledge is exactly what this system is designed to surface.
How to use it
- 🔗 Download the
.skillfiles from GitHub (link below) - Go to Claude.ai → Settings → Skills → Upload the files
- Start with Layer 1. Let it orient you before moving forward. Don’t skip this step thinking you already know where you’re going. The orientation changes what Layer 2 asks you.
- Move to Layer 2. Don’t rush it. The questions are doing the heavy lifting. If a question feels obvious, answer it anyway. The specificity of your answer feeds what comes next.
- Layer 3 picks your format and builds the deliverable. Review the format selection before you let it build. If the audience framing is off, correct it here rather than editing the final output.
Pro tip
Run this on one specific role you’ve held for at least 6 months. Not your whole career. One focused job, one clear audience. That’s where the output gets actually useful instead of generic.
For example: your eight months managing onboarding for a SaaS support team. Your year running paid social for a single DTC brand. Your six months as the only ops person at a 12-person startup. The narrower the container, the denser the insight. A guide for “people who want to get into marketing” has no value. A guide for “first-time paid social managers at brands under $5M in revenue” is something people will actually pay for or share widely.
Try it free
Open source on GitHub: github.com/bruiandy/experience-to-asset 🚀
Frequently Asked Questions
Q: How does Layer 2 (deep extract) actually pull out deep insights instead of just surface-level tips?
Layer 2 uses a conversational approach, asking one question at a time, rather than a formal interrogation. It combines your answers with documents you upload, which helps surface the actual mistakes, workarounds, and judgment calls you made. This is what makes your knowledge valuable, not just rehashed best practices everyone already knows.
Q: Do I need Claude Pro or the Claude API to use these skills?
You just need Claude Pro. Download the .skill files from GitHub and upload them to Claude.ai Settings → Skills. No API key, no additional cost beyond your subscription.
Q: What output formats can Layer 3 actually create?
SOP docs, Excel toolkits, PDF guides, interactive websites, or article frameworks, Layer 3 matches your content to whichever format fits your audience and message best.
Q: Do I need to be an expert to make something valuable?
Not at all. The whole point is you only need to be 2, 3 steps ahead of where you were a year ago. Your specific mistakes and workarounds are gold, they don’t exist in any AI training data, which is exactly why they’re worth packaging and sharing.
A Three-Layer Claude Skill System
Turn your job experience into a reusable knowledge asset
by u/SnooPaintings9788 in PromptEngineering