karpathy-coder — Claude Code skill: what it does, how to install
Enforces Andrej Karpathy's 4 coding principles to prevent LLM over-engineering. Catches assumptions, keeps diffs surgical, and strips out unrequested abstractions.
/plugin marketplace add alirezarezvani/claude-skills
/plugin install karpathy-coder@claude-code-skillsWhat karpathy-coder does
This skill guides model behavior during writing, reviewing, and committing code. It stops the LLM from making silent assumptions, bloating architecture with single-use abstractions, or altering untouched lines. It cuts down bloated code. For multi-step tasks, it demands explicit success criteria and tests before proceeding.
Under the hood, the skill ships four Python scripts relying only on standard library modules. The complexity_checker.py script catches over-engineered classes, while diff_surgeon.py flags drive-by edits. It also bundles the karpathy-reviewer sub-agent, /karpathy-check slash command, and a hooks/karpathy-gate.sh hook.
You need standard Python to run the scripts. Install it for non-trivial diffs over 20 lines or multi-step tasks. Skip it for typo fixes.
What it helps with
- clean noise and unrelated refactoring from git diffs
- detect hidden assumptions before generating multi-step plans
- flag premature abstractions and high cyclomatic complexity
- verify staged code quality before committing
Example prompts for the agent
- /karpathy-check
- review my diff
- am I overcomplicating this
How to install karpathy-coder
1Plugin marketplace
/plugin marketplace add alirezarezvani/claude-skills/plugin install karpathy-coder@claude-code-skillsThis installs the whole karpathy-coder plugin with all its skills
2Skills CLI (Vercel)
npx skills add alirezarezvani/claude-skills --skill karpathy-coder -a claude-code3Manually: put the files in place
~/.claude/skills/karpathy-coder/SKILL.mdCopy the whole skill folder; for one project use .claude/skills/karpathy-coder/
Manually: put the files in place
.agents/skills/karpathy-coder/SKILL.mdFor all projects use ~/.agents/skills/
Manually: put the files in place
.cursor/skills/karpathy-coder/SKILL.mdCursor also reads .agents/skills/ and .claude/skills/
1GitHub CLI
gh skill install alirezarezvani/claude-skills karpathy-coder2Manually: put the files in place
.github/skills/karpathy-coder/SKILL.mdPlatform CLI
gemini skills install https://github.com/alirezarezvani/claude-skills --path engineering/karpathy-coder/skills/karpathy-coderManually: put the files in place
.devin/skills/karpathy-coder/SKILL.mdThe legacy .windsurf/skills/ path still works
Claude.ai
Zip the folder and upload it in Settings → Capabilities → Skills
From the same set349
The whole set →Similar
Questions about karpathy-coder
How do I install karpathy-coder in Claude Code?
Run /plugin marketplace add alirezarezvani/claude-skills and then /plugin install karpathy-coder@claude-code-skills inside Claude Code.
What does the /karpathy-check slash command do?
It triggers the karpathy-reviewer sub-agent to inspect staged changes against Karpathy's four principles: assumptions, simplicity, surgical diffs, and goal verification.
Do the bundled Python verification tools require extra dependencies?
No, all scripts in scripts/ use Python standard library modules only, with no pip packages required.
Source text
SKILL.md · MIT
--- name: karpathy-coder description: Use when writing, reviewing, or committing code to enforce Karpathy's 4 coding principles — surface assumptions before coding, keep it simple, make surgical changes, define verifiable goals. Triggers on "review my diff", "check complexity", "am I overcomplicating this", "karpathy check", "before I commit", or any code quality concern where the LLM might be overcoding. context: fork license: MIT metadata: version: 2.9.0 author: claude-code-skills tags: [code-quality, discipline, karpathy, simplicity, surgical-changes, anti-patterns, review] compatible_tools: [claude-code, codex-cli, cursor, antigravity, opencode, gemini-cli] --- # Karpathy Coder — Active Coding Discipline Derived from [Andrej Karpathy's observations](https://x.com/karpathy/status/2015883857489522876) on LLM coding pitfalls. This is **not just guidelines** — it ships Python tools that detect violations, a review agent, a slash command, and a pre-commit hook. > "The models make wrong assumptions on your behalf and just run along with them without checking. They don't manage their confusion, don't seek clarifications, don't surface inconsistencies, don't present tradeoffs, don't push back when they should." > > "They really like to overcomplicate code and APIs, bloat abstractions, don't clean up dead code... implement a bloated construction over 1000 lines when 100 would do." > > "LLMs are exceptionally good at looping until they meet specific goals... Don't tell it what to do, give it success criteria and watch it go." > > — Andrej Karpathy ## The four principles ### 1. Think Before Coding **Don't assume. Don't hide confusion. Surface tradeoffs.** - State assumptions explicitly. If uncertain, ask. - If multiple interpretations exist, present them — don't pick silently. - If a simpler approach exists, say so. Push back when warranted. - If something is unclear, stop. Name what's confusing. Ask. ### 2. Simplicity First **Minimum code that solves the problem. Nothing speculative.** - No features beyond what was asked. - No abstractions for single-use code. - No "flexibility" or "configurability" that wasn't requested. - No error handling for impossible scenarios. - If you write 200 lines and it could be 50, rewrite it. **The test:** Would a senior engineer say this is overcomplicated? If yes, simplify. ### 3. Surgical Changes **Touch only what you must. Clean up only your own mess.** - Don't "improve" adjacent code, comments, or formatting. - Don't refactor things that aren't broken. - Match existing style, even if you'd do it differently. - If you notice unrelated dead code, mention it — don't delete it. - Remove imports/variables/functions that YOUR changes made unused. - Don't remove pre-existing dead code unless asked. **The test:** Every changed line should trace directly to the user's request. ### 4. Goal-Driven Execution **Define success criteria. Loop until verified.** | Instead of... | Transform to... | |---|---| | "Add validation" | "Write tests for invalid inputs, then make them pass" | | "Fix the bug" | "Write a test that reproduces it, then make it pass" | | "Refactor X" | "Ensure tests pass before and after" | For multi-step tasks, state a brief plan: ``` 1. [Step] → verify: [check] 2. [Step] → verify: [check] 3. [Step] → verify: [check] ``` ## Slash command `/karpathy-check` — Run the full 4-principle review on your staged changes. ## Python tools (`scripts/`) All tools are stdlib-only. Run with `--help`. | Script | What it detects | |---|---| | `complexity_checker.py` | Over-engineering: too many classes, deep nesting, high cyclomatic complexity, unused params, premature abstractions | | `diff_surgeon.py` | Diff noise: lines that don't trace to the stated goal — comment changes, style drift, drive-by refactors | | `assumption_linter.py` | Hidden assumptions in a plan: unasked features, missing clarifications, silent interpretation choices | | `goal_verifier.py` | Weak success criteria: vague plans without verifiable checks, missing test assertions | ## Sub-agent `karpathy-reviewer` — Runs all 4 principles against a diff. Dispatched by `/karpathy-check` or manually before committing. ## Pre-commit hook `hooks/karpathy-gate.sh` — runs `complexity_checker.py` and `diff_surgeon.py` on staged files. Warns (non-blocking) when violations are found. Wire it via `.claude/settings.json` or Husky. ## References - `references/karpathy-principles.md` — the source quotes, deeper context, when to relax each principle - `references/anti-patterns.md` — 10+ before/after examples across Python, TypeScript, and shell - `references/enforcement-patterns.md` — how to wire hooks, CI integration, team adoption ## When to relax These principles bias toward **caution over speed**. For trivial tasks (typo fixes, obvious one-liners), use judgment. The principles matter most on: - Non-trivial implementations (>20 lines changed) - Code you don't fully understand - Multi-step tasks with unclear requirements - Anything that will be reviewed by humans ## Cross-tool compatibility Installs via plugin for Claude Code. For other tools, copy the principles into your schema file: | Tool | Schema file | |---|---| | Claude Code | `CLAUDE.md` (auto-loaded by plugin) | | Codex CLI | `AGENTS.md` | | Cursor | `AGENTS.md` or `.cursorrules` | | Antigravity / OpenCode / Gemini CLI | `AGENTS.md` | ## Related skills (chains via `context: fork`) - **`self-eval`** — honest quality scoring after completing work - **`code-reviewer`** — broader code review; karpathy-coder focuses on the 4 LLM-specific pitfalls - **`llm-wiki`** — compound knowledge; karpathy-coder ensures you don't overcomplicate while building it
© claude-code-skills · MIT · alirezarezvani/claude-skills