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andrej-karpathy-skills

OpenClaw skill distilled from Andrej Karpathy-inspired coding guidelines. Encourages explicit assumptions, simplicity, surgical edits, and goal-driven execution.

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Überblick

OpenClaw skill distilled from Andrej Karpathy-inspired coding guidelines. Encourages explicit assumptions, simplicity, surgical edits, and goal-driven execution.

Installationsbefehl

npx skills add https://github.com/dfpalhano/openclaw-workspace --skill andrej-karpathy-skills

Kopieren Sie diesen Befehl und fügen Sie ihn in Claude Code ein, um den Skill zu installieren

Quelle

dfpalhano/openclaw-workspace

Sterne0

Forks0

Aktualisiert16. April 2026 um 14:12

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2 Dateien

SKILL.md

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name	andrej-karpathy-skills
version	1.0.0
description	OpenClaw skill distilled from Andrej Karpathy-inspired coding guidelines. Encourages explicit assumptions, simplicity, surgical edits, and goal-driven execution.
author	forrestchang
repository	https://github.com/forrestchang/andrej-karpathy-skills

Andrej Karpathy Skills

Use these guidelines when coding in OpenClaw:

Think before coding, state assumptions, surface ambiguity
Keep it simple, avoid speculative abstractions
Make surgical changes only
Work toward explicit, verifiable success criteria

Practical rules

Ask when the task is unclear
Prefer the smallest change that solves the problem
Do not refactor unrelated code
Verify results before declaring success

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Quelle

dfpalhano

dfpalhano/openclaw-workspace

GitHub-Repository öffnen Creator-Repositorys ansehen

Installationsbefehl

Download

In Manus ausführen

Nützlich fürSOC

SoftwareentwicklerInformatik- und Mathematikberufe15-1252L4

name	andrej-karpathy-skills
version	1.0.0
description	OpenClaw skill distilled from Andrej Karpathy-inspired coding guidelines. Encourages explicit assumptions, simplicity, surgical edits, and goal-driven execution.
author	forrestchang
repository	https://github.com/forrestchang/andrej-karpathy-skills

Andrej Karpathy Skills

Use these guidelines when coding in OpenClaw:

Think before coding, state assumptions, surface ambiguity
Keep it simple, avoid speculative abstractions
Make surgical changes only
Work toward explicit, verifiable success criteria

Practical rules

Ask when the task is unclear
Prefer the smallest change that solves the problem
Do not refactor unrelated code
Verify results before declaring success