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cccskills
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larp-detector

Review external pull requests and issues in public GitHub repositories by checking whether they address real user problems. It helps assess proposed improvements, question hypothetical issues, and inform prioritization or replies without treating AI use alone as suspicious.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

원문원문 설명 보기

Skeptical review of outside contributions to public repos. Use when reviewing, ranking, or replying to public GitHub pull requests or issues from outside contributors, or when the user says "larp-detector".

연동 도구GitHub
설치 방법 보기

이럴 때 유용합니다

  • Review an external pull request for a real user need
  • Assess whether a reported issue fits actual usage
  • Prioritize contributions by their practical value
  • Consider a reply based on the proposal's background

포함된 파일(1)

  • SKILL.md1.8 KB

SKILL.md(원문)

설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.

Larp Detector

When reviewing this code, be careful. A lot of people on public repos just use an AI coding agent to contribute to a codebase, only for the sake of their name being on the contributors list. They also have no taste and no product feel. They're not trying to fix any real issue, any real problem, or any real bug. They literally just want to contribute.

Another common thing they do is use an AI coding agent to analyze the repo for issues, problems, and security vulnerabilities. Even if our code is good, LLMs will hallucinate hypothetical issues that would really never happen.

So be careful when reviewing this. Check that it is actually a good idea, and think about the intention of the creator. What is the intention? Did they actually face a problem and then tell their coding agent to fix it? Everybody uses AI coding agents, so that alone is not a red flag.

Really try to figure out the intention and the origin of this PR, issue, or whatever you are reviewing:

  • Did it come from an actual bug that a user encountered?
  • Did it come from genuine care for the product and a really good idea for how to improve it?
  • Or is it just a fake improvement, or support for something we don't need?
  • Or does it try to fix issues that were artificially found by an LLM, but would never happen given the existing usage patterns of existing users?

Be careful. A lot of the code you're going to review is complete nonsense. It's created by people who have no product taste, are not technical, and just tell an AI coding agent to contribute something for the sake of contributing something.

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한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

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한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

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한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

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한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

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한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

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