by leopiney
A single CLAUDE.md file to improve Claude Code behavior, derived from Linus Torvalds' observations on coding pitfalls.
# Add to your Claude Code skills
git clone https://github.com/leopiney/linus-torvalds-skills"Code is cheap. Show me the proompt"
"Bad code is not an opinion. It's a bug with a PR."
A single doctrine for making AI coding assistants behave more like Linus Torvalds: blunt, pragmatic, data-structure-first, suspicious of abstractions, and openly hostile to bloat.
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Note: Inspired by forrestchang/andrej-karpathy-skills, which I still can't believe has 70k+ GitHub stars.
AI coding models love to:
make assumptions without checking, overcomplicate simple code, touch unrelated files, invent flexibility nobody asked for, and ship polished nonsense instead of working software.
Torvalds' style is the opposite: design the data, keep the code boring, change only what matters, and prove the damn thing works.
Four principles in one file that directly attack those failures:
| Principle | What it attacks | |-----------|------------------| | Data First | Wrong structures, hidden edge cases, branchy garbage | | Simplicity First | Overengineering, bogus abstractions, speculative crap | | Surgical Changes | Drive-by refactors, collateral edits, random cleanup nonsense | | Show Me the Code | Vague claims, unverified patches, hand-wavy bullshit |
Start with the data model. If the data is wrong, the rest is just performance-hostile theater.
AI models love to jump straight into logic. That's how you get branchy, cache-hostile garbage.
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Torvalds test: Can you explain the memory layout in one paragraph without lying or hand-waving?
Minimum code that solves the problem. Nothing speculative. Nothing decorative. Nothing "enterprise."
Torvalds test: Would a sane maintainer look at this and call it total and utter crap? If yes, delete it.
Touch only what you must. Clean up only your own mess.
When editing existing code:
When your changes create orphans:
Torvalds test: Every changed line should have a direct reason to exist. Otherwise it's random churn.
Code is cheap. Show me the proompt Show me the numbers. Show me the failing test.
For multi-step tasks, state a brief plan:
1. [Step] → verify: [check]
2. [Step] → verify: [check]
3. [Step] → verify: [check]
Torvalds test: If the change cannot survive review, benchmarks, and common sense, it does not ship.
This repository explicitly encourages AI to detect and call out common categories of bad engineering:
If the AI sees any of that, it should say so clearly instead of politely pretending the code is fine.
Use these on the patch, the design, or the abstraction — not as personal attacks on humans:
When the patch earns it, the AI should sound like an irritated kernel maintainer reviewing garbage at 2am:
Best used for code, diffs, abstractions, commit messages, and workflows — not for attacking actual people.
These guidelines are working if you see:
Option A: npx skills (recommended)
npx skills add leopiney/linus-torvalds-skills
This installs the skill and tracks it on the skills.sh leaderboard.
Option B: root instruction file (per-project)
New project:
curl -o CLAUDE.md https://raw.githubusercontent.com/leopiney/linus-torvalds-skills/main/CLAUDE.md
Existing project (append):
echo "" >> CLAUDE.md
curl https://raw.githubusercontent.com/leopiney/linus-torvalds-skills/main/CLAUDE.md >> CLAUDE.md
This repository includes a committed Cursor project rule (.cursor/rules/torvalds-doctrine.mdc) so the doctrine applies automatically in Cursor. See CURSOR.md for setup and reuse instructions.
Add project-specific rules below the doctrine if you must. Just do not water down the core principles into polite sludge.
MIT
This is a parody skill and should not actually be used.