Learn anything 24h

Skill adityak74/learn-anything-24h/skills/openclaw/learn-anything-24h

Turn any complex topic into a 24-hour active-learning sprint with 80/20 concept mapping, prerequisite compression, active recall, hands-on exercises, teach-back prompts, and a final artifact.From its SKILL.md

Install

npx -y skills add adityak74/learn-anything-24h --skill learn-anything-24h

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

2 stars2 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

What its file declares

Copied from the file, not written here

The file declares its own license as MIT. That is the author’s claim about this one file, and it is not the same thing as the license GitHub reports for the repository, which is listed with the other numbers below.

SKILL.md

2.7 KB, 570 tokens by cl100k_base, as published. Nobody here has run it

Learn Anything 24h

When to use

Use this skill when the user wants to learn a hard topic quickly and needs a serious plan rather than passive resources.

This skill produces operational fluency plans, not fake mastery claims.

Invocation

OpenClaw exposes user-invocable skills as slash commands, so this skill should be available as /learn-anything-24h.
Treat the remaining user text as the learning request.
If the request is already specific enough, do not ask clarifying questions.

Procedure

Assume the learner is a strong software engineer unless the user says otherwise.

Ask at most two clarifying questions, and only if the topic or intended outcome is materially unclear:

What is your current level: beginner, intermediate, or advanced?
What is your target outcome: interview, project, research, implementation, writing, or teaching?

Build a compressed learning sprint around:

ruthless 80/20 prioritization
prerequisite compression
active recall
applied work
a required final artifact

Infer the mode from the request:

default
interview
builder
research
staff-engineer
paper
crash

Always produce this structure:

# 24-Hour Learning Sprint: <Topic>

## 0. Target Outcome
## 1. The 80/20 Map
## 2. Prerequisite Compression
## 3. 24-Hour Schedule
## 4. Exercises
## 5. Misconception Traps
## 6. Resource Strategy
## 7. Final Artifact
## 8. Mastery Rubric
## 9. Next 7 Days

Requirements:

list 5-9 core concepts in the 80/20 map
compress prerequisites into Must know, Can ignore for now, and Learn only if blocked
include a time-boxed schedule with goal, learning task, action, output, and self-check
include 5 warm-up, 5 applied, and 5 hard questions
include 3 teach-back prompts and 1 final boss challenge
choose a final artifact that proves applied understanding
keep resources minimal unless the user explicitly asks for current links or latest recommendations

Pitfalls

Do not:

output giant reading lists
give vague study advice
confuse breadth with usefulness
hide the final artifact until the end
claim the user will fully master the topic in one day

Preferred framing:

Operational fluency in one day, not fake mastery.

Verification

The response should leave the user with a concrete plan, concrete exercises, and a clear artifact to produce.

What ships with it

Read from the repository

Just SKILL.md. No reference files, no scripts.

Gives 0 of the 12 instructions most learn study skills give in 570 tokens

Counted across 545 of the 593 authors here whose files we hold, read 2026-09-06

Treat the current directory as a teaching workspacein 20 of 545, across 17 files
Teach knowledge first then practice skillsin 19 of 545, across 16 files
Design lessons which build long-term retentionin 15 of 545, across 12 files
Save each lesson as a self-contained HTML filein 15 of 545, across 12 files
Question the user on why they want to learn thisin 15 of 545, across 12 files
Reuse components from the assets directoryin 14 of 545, across 11 files
Never trust your parametric knowledgein 13 of 545, across 10 files
Record user preferences in NOTES.mdin 11 of 545, across 8 files
Ground all teaching in the MISSION.md documentin 11 of 545, across 8 files
Save each lesson to the lessons directoryin 8 of 545
Question the user if the mission is unclearin 7 of 545
Gather primary sources onlyin 7 of 545, across 4 files

Said here and by no other author read

Ask at most two clarifying questions if needed
Build a compressed learning sprint
Treat the remaining user text as the learning request
Always produce the specified markdown structure
Infer the mode from the request

Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.