KP

kgeoffrey/postmodernist

开发工具

本页由 AI 翻译,技术细节请以原文为准。 查看原文

20 stars 质量 54 趋势 10MIT

后现代主义批评技巧,适用于Claude和Codex。压力测试AI生成的策略和营销失误。调试现实。

概览

AI输出是平均的,自信且微妙地错误。这项技能会找出具体的问题,告诉你该怎么做。 一项适用于Claude Code、Codex、Gemini、Cursor、Windsurf以及任何LLM代理的技能。剥离平均的信心、普遍的主张和光鲜的虚无。 一个被已故欧洲哲学家缠绕的大型语言模型,批评那些从未听说过他们的大型语言模型的产出。无论如何,它依然有效。 :人力资源SaaS产品AI生成的使命宣言。 “这是一个扎实的使命宣言。你或许可以更具体地说明'更公平'在实践中的含义,并考虑加入具体的指标或结果以加强价值主张。语气专业,注重员工成长是很好的差异化因素。” “更公平”意味着做最多工作,也做得最少。任务假设人工智能默认让评论更公平——更一致、更少偏见。但对有缺陷的系统施加一致性只会扩大缺陷。

概述(AI 翻译)

AI输出是平均的、自信且微妙的错误。这项技能会找到具体的问题,并告诉你该怎么做。

一项去倾斜化技能,适用于Claude Code、Codex、Gemini、Cursor、Windsurf以及任何LLM代理。剥离平均自信、普遍宣称和打磨的虚无。

一个被死去的欧洲哲学家所困扰的大型语言模型,批评那些从未听说过他们的大型语言模型的产出。但它依然有效。


之前 / 之后

输入:人力资源SaaS产品AI生成的使命宣言。

正规分析(克劳德)

“这是一个扎实的使命宣言。你可能想让它更具体地说明’更公平’在实践中的含义,并考虑添加具体的指标或结果以强化价值主张。语气专业,注重员工成长是很好的差异化因素。”

后现代主义批判

“更公平”做了最多的工作,做得最少。任务假设人工智能默认让评论更公平——更一致、更少偏见。但对有缺陷的系统施加一致性只会放大缺陷。

本页由 AI 翻译,技术细节请以原文为准。

README

以下为原文 README 节选,完整内容请查看原文。

Postmodernist Critique

AI output is averaged, confident, and subtly wrong. This skill finds the specific thing that’s off and tells you what to do about it.

A deslopification skill for Claude Code, Codex, Gemini, Cursor, Windsurf, and any LLM agent. Strip the averaged confidence, the universal claims, the polished nothing.

An LLM haunted by dead European philosophers, critiquing the output of LLMs that have never heard of them. It works anyway.


Before / After

Input: AI-generated mission statement for an HR SaaS product.

To empower HR teams to run fairer, faster, and more meaningful performance
reviews by using AI to reduce administrative burden, improve consistency,
and help organizations invest in employee growth at scale.

Normal Analysis (Claude)

“This is a solid mission statement. You might want to make it slightly more specific about what ‘fairer’ means in practice, and consider adding a concrete metric or outcome to strengthen the value proposition. The tone is professional and the focus on employee growth is a good differentiator.”

Postmodernist Critique

“Fairer” is doing the most work and the least. The mission assumes AI makes reviews fairer by default — more consistent, less biased. But consistency applied to a flawed system just scales the flaw. The employee whose performance gets assessed on Slack response times and ticket velocity, who works fewer visible hours because they’re a caregiver, who writes less polished prose because English isn’t their first language — for them, faster and more consistent is worse, not better.

“Meaningful” has the same problem from the other direction. It assumes the purpose of a performance review is employee growth. For a significant portion of the organizations buying this, it’s legal documentation for a termination, a compliance checkbox, or a PIP trail. AI that makes those processes faster isn’t delivering meaning — it’s scaling a mechanism that was already doing damage, now with better audit logs.

The sentence is selling a product to the person holding the gun by describing how much better the bullet will fly.

在 GitHub 查看完整 README

推荐工具

换一个关键词,或者移除筛选条件。

安装

npx skillfish add kgeoffrey/postmodernist
新手?先看 mcpskill.org 教程 →