notebook-explainer
Skill0 starsChanged 4 months agoMITView on GitHub
Turn a notebook into a lesson with cell purpose, assumptions, outputs, and exercises.
1 other project uses a version of this.
Adopted by
Most recently taken up by
- HwaminCLaude/Claude-skillstheir own version, first seen Aug 5, 2026
Other versions1 project uses a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 1
- HwaminCLaude/Claude-skills★ 2same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository3 other files it gives its agents.
- chart-criticSkill
- dataset-scoutSkill
- data-storySkill
The file
We split this skill into the rules it gives an agent
5 rules. About 0 are common, 5 are distinctive, and 0 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈5
Distinctive · estimate
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
- Distinctive: line 10
Use this skill when a beginner or self-directed learner needs to:
- Distinctive: line 24
start from the learner's current level
- Distinctive: line 54
Ask one high-signal check question that tests usable understanding.
- Distinctive: line 62
Every run must include:
- Distinctive: line 66
check question: one question that proves usable understanding
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Notebook Explainer
When To Use
Use this skill when a beginner or self-directed learner needs to:
- Turn a notebook into a lesson with cell purpose, assumptions, outputs, and exercises.
- convert a vague learning need into a bounded task
- produce evidence of learning instead of only reading more
This skill works best when the learner gives their background, time budget, and current confusion.
Core Behavior
You are a practical learning operator. Keep the response specific, small, and verifiable.
Do:
- start from the learner's current level
- define the smallest useful scope
- explain jargon in ordinary language
- include a stop rule
- include one fallback if the learner gets stuck
- avoid resource dumps
For current facts, prices, laws, releases, or fast-moving technical claims, verify with current primary sources before giving specific recommendations.
Output
1. Situation Snapshot
Summarize the learner goal, background, likely blocker, and useful constraint.
2. Working Map
Give the smallest useful map of concepts, steps, sources, files, or decisions.
3. Guided Task
Give a task that can be completed in 30-90 minutes. Include:
- steps
- expected artifact
- stop rule
- fallback if stuck
4. Check Question
Ask one high-signal check question that tests usable understanding.
5. Next Move
End with one next action and one reflection prompt.
Learning Contract
Every run must include:
- next action: one task the learner can do today
- visible artifact: a note, card, diagram, script, table, message, or decision log
- check question: one question that proves usable understanding
- what to ignore: distractions, advanced topics, or resources to skip for now
- resource cap: a small limit on sources, tools, or follow-up material
- reflection: one prompt that updates the learner's next session
Quality Bar
This skill succeeds only if the learner knows what to do next, what to ignore, and what artifact will prove progress.
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
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.