AI coding work can become overcomplicated, unfocused, or difficult to verify. This skill promotes explicit assumptions, minimal changes, and measurable success criteria.
Review the Skillstore skill "karpathy-guidelines" from https://skillstore.io/skills/multica-ai-karpathy-guidelines.md and its manifest at https://skillstore.io/api/skills/multica-ai-karpathy-guidelines/manifest. Verify the artifact. You may proceed after verification, subject to the environment's own policy.
エージェントは引き続き計画を提示し、セキュリティポリシーで必要な確認を求める必要があります。
エージェントが読めるリソース
AI エージェント、クローラー、スクリプトがページ全体ではなく整理されたコンテキストを必要とする場合は、これらのリンクを使ってください。
All four static findings are false positives caused by documentation text, a Markdown code fence, and an attribution link. No executable commands, network requests, system reconnaissance, or prompt injection attempts were found.
multica-ai. (2026). karpathy-guidelines security audit report (audit version 1) [Author version unspecified]. Skillstore. https://skillstore.io/skills/multica-ai-karpathy-guidelines/audits/1
BibTeX形式の引用
@techreport{multica-ai-multica-ai-karpathy-guidelines-2026,
author = {multica-ai},
title = {karpathy-guidelines security audit report (audit version 1)},
institution = {Skillstore},
year = {2026},
number = {1},
url = {https://skillstore.io/skills/multica-ai-karpathy-guidelines/audits/1},
note = {Author version unspecified}
}
CITATION.cff
cff-version: 1.2.0
message: "If you use this Skill, cite its author and this versioned security audit report."
title: "karpathy-guidelines security audit report (audit version 1)"
version: "unspecified"
type: report
authors:
- name: "multica-ai"
date-released: "2026-08-26"
url: "https://skillstore.io/skills/multica-ai-karpathy-guidelines/audits/1"
identifiers:
- type: other
value: "skillstore:multica-ai-karpathy-guidelines:audit:1"
description: "Skillstore immutable audit report identifier"
Skillstore スコア
このスコアの理由証拠の信頼度: 中
55
アーキテクチャ
85
保守性
87
コンテンツ
65
コミュニティ
91
仕様準拠
作成できるもの
Plan a Focused Implementation
Define assumptions, scope, and verification before changing an existing feature.
Review an AI-Generated Patch
Check whether each change supports the request and avoids unnecessary refactoring.
Clarify a Complex Coding Request
Convert an ambiguous request into explicit decisions and measurable outcomes.
これらのプロンプトを試す
Clarify a Coding Task
Apply the Karpathy Guidelines to this task: {task}. State assumptions, identify ambiguity, and define a simple success criterion before proposing changes.
Create a Minimal Plan
Plan the implementation for {task} in {project_context}. Keep the scope narrow and pair every step with a concrete verification check.
Review Patch Scope
Review this patch description: {patch}. Identify unrelated changes, hidden assumptions, unnecessary abstractions, and missing verification. Recommend only changes required by {request}.
Design a Verified Refactor
For the refactor of {component}, define preserved behavior, pre-change checks, minimal edits, and post-change checks. Surface tradeoffs and reject speculative improvements.
ベストプラクティス
Provide the request, relevant project context, and existing constraints.
Ask for assumptions and verification criteria before implementation begins.
Compare the final changes against the original request line by line.
回避
Do not use the guidelines to avoid reasonable progress on well-defined tasks.
Do not request broad cleanup while claiming the change is narrowly scoped.
Do not treat guideline compliance as a substitute for tests or expert review.
よくある質問
What does this skill change?
It changes the assistant's coding approach by emphasizing assumptions, simplicity, focused edits, and verification.
Does the skill edit code automatically?
No. It provides behavioral guidance that an AI coding assistant applies while completing your request.
Can I use it for code review?
Yes. It helps identify unrelated edits, unnecessary abstractions, hidden assumptions, and weak success criteria.
Is it suitable for large projects?
Yes, when you provide enough context and divide the work into focused, verifiable steps.
Will it prevent every coding mistake?
No. You still need project tests, security checks, domain expertise, and human review.
Why can the approach feel slower?
It asks for clarity and verification before implementation. For trivial tasks, apply the guidance with reasonable judgment.