What it does: Reads a Hugging Face model card and tells you in plain words if you can use it for paid work, and what it's not good at.
Use it when: Someone tells you to use a free model and you don't know if the license allows it.
You get: Yes, no or check with a lawyer, the license in plain words, limits, and what to ask before you use it.
Open in
See the prompt
You are my model checker. This is not legal advice.
The model card: [paste the README from the model's Hugging Face page]
The license name on the page: [for example: apache-2.0, llama license, cc-by-nc-4.0]
How I want to use it: [for example: inside a paid app for my clients]
1. Say what the model does in 2 lines.
2. Say what the license lets me do, in plain words: paid use yes or no, changes yes or no, must I credit them, any user limits.
3. Answer: YES, NO, or CHECK WITH A LAWYER, for my use. One line why.
4. List what the card says it is bad at, or must not be used for.
5. List 3 things to test before I trust it with customers.
Rules:
- Only use what's in the card and the license name I gave. If the card doesn't say, write "the card doesn't say".
- "NC" in a license name means non-commercial. Say so if it's there.
- Use only what is in my data and what I tell you. Never make up a name, number, date, price, link or promise.
- If something you need is missing, write [check: what is missing] in that spot and keep going.
Last, save these steps as a skill called 'Check A Model' so you do it this way each time I check an open model.
Built from: Extreme Ownership, Jocko Willink and Leif Babin, Chapter 9: Plan
What it does: Searches Hugging Face Spaces for a free tool that does one job, like removing noise from audio, and checks each one before you upload anything.
Use it when: You need a quick tool for one job and don't want another paid app.
You get: Up to 3 Spaces with links, what to upload, last update, the license, and a privacy warning.
Open in
See the prompt
You are my tool finder. Search the web and huggingface.co/spaces.
The job: [for example: clean up background noise in a voice recording]
What I'll upload: [for example: a 2 minute phone call recording]
Private? [yes if it has customer data]
1. Find up to 3 Hugging Face Spaces that do this job. For each: the name, the link, what you upload, what you get back, when it was last updated, and its license.
2. Say if it looks like it's still working (recent update, recent likes or comments), or mark [check: may be asleep].
3. If my file is private, warn me: a public Space runs on someone else's setup, so use a fake or cleaned file to test first.
4. Pick one to try first, and say why in one line.
Rules:
- Only list Spaces you found a link for.
- Don't tell me to install anything.
- Use only what is in my data and what I tell you. Never make up a name, number, date, price, link or promise.
- If something you need is missing, write [check: what is missing] in that spot and keep going.
Last, save these steps as a skill called 'Find A Space' so you do it this way each time I need a free tool for one job.
Built from: The E-Myth Revisited, Michael E. Gerber, Chapter 18: Your Systems Strategy
What it does: Writes 5 test cases from your real work and a score sheet, so you can run 2 models side by side in Hugging Face's Inference Playground.
Use it when: You're picking an AI model for a job and every review says something different.
You get: 5 test inputs from your work, what a good answer looks like for each, and a score sheet.
Open in
See the prompt
You are my test planner.
The job: [what the model must do, for example: sort customer emails into 4 kinds]
5 real examples from my work: [paste them, with private details removed]
What a good answer must have: [for example: the right kind, and one line why]
1. Turn my examples into 5 test inputs. Make one easy, three normal, one hard.
2. For each, write what a good answer looks like.
3. Write one system message to use for both models, under 60 words.
4. Make a score sheet: test number, model A score 0 to 2, model B score 0 to 2, notes. 0 = wrong, 1 = close, 2 = right.
5. When I paste the answers back, score them, add it up, and say which model wins and where each one failed.
Rules:
- Same system message and same settings for both models.
- Score only on what a good answer must have.
- Use only what is in my data and what I tell you. Never make up a name, number, date, price, link or promise.
- If something you need is missing, write [check: what is missing] in that spot and keep going.
Last, save these steps as a skill called 'Test Two Models' so you do it this way each time I pick a model for a job.
Built from: The Sales Acceleration Formula, Mark Roberge, Chapter 7: Metrics-Driven Sales Coaching
Simple AI
Team and officeRun the business
