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digital-stoic-org/agent-skills

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本页由 AI 翻译,技术细节请以原文为准。 查看原文

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混合人类/人工智能智能的正念技能与代理

概览

(πρᾶξις)= 实践。知识的实现,而不仅仅是已知。 这是一种基于人机设定意图和引导、人工智能挑战和揭示盲点、双方从循环中学习的人类-人工智能协作认知学科。 ⚠️ 活体实验。我的认知工具包——分叉,适应你的大脑。 我构建了105项技能、5阶段工作流程和9项技能门系统,强迫一个还无法自己规划工作的人工智能构建结构。后来模型在决策和自我规划方面变得极为出色——大部分支架变成了累赘。数月的真实练习让它疲惫不堪。幸存下来的不是同一件事的轻量版;而是模型能够自我规划后留下的:意图,在大边界处,自信的答案。弧线——构建它,练习它,放下它——是实践。 AI工具强大但混乱。大多数人要么按每个提示,要么祈祷。这两种都无法适应真实工作。

概述(AI 翻译)

Praxis (πρᾶξις) = 实践。知识被实践,而不仅仅是已知。


🎯 一句话

这是一种基于相互磨砺的认知学科,用于人机协作——人类设定意图并引导,AI挑战并揭示盲点,双方都从循环中学习。

⚠️ 活生生的实验。我的认知工具包——分叉,适应你的大脑。

这是v2,比v1小。 我建了105个技能,一个5阶段 工作流程,以及一个9技能门槛系统,强迫AI构建结构化 还无法自己规划工作。后来模型变得非常出色, 决策和自我规划——而大部分这些支架都成了累赘。 几个月的真正练习已经把它磨得只剩把手。幸存下来的不是 同一种东西的轻松版本;它曾经保持不可归原的人性 模型可以自己规划:坚持意图,引导在大局 界限,挑战自信的答案。弧线——建立它,练习 ,脱掉——这就是实践。


💡 为什么会有这样的存在

AI工具强大但混乱。大多数人要么微观管理每个提示,或者让AI自由发挥然后祈祷。这两种都无法扩展到实际工作。

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。

🧠 Digital Stoic Praxis

Praxis (πρᾶξις) = practice. Knowledge enacted, not just known.


🎯 In One Sentence

A cognitive discipline for human-AI collaboration built on mutual sharpening — the human sets intent and directs, the AI challenges and reveals blind spots, and both learn from the loop.

⚠️ Live experiment. My cognitive toolkit — fork it, adapt it to your brain.

This is v2, and it’s smaller than v1. I built 105 skills, a 5-phase workflow, and a 9-skill gate system to force structure out of an AI that couldn’t yet plan its own work. Then the models got dramatically better at deciding and self-planning — and most of that scaffold became dead weight. Months of real practice wore it down to its handle. What survived isn’t a lighter version of the same thing; it’s what stays irreducibly human once the model can plan for itself: persist intent, guide at the big boundaries, challenge the confident answer. The arc — build it, practice it, shed it — is the praxis.


💡 Why This Exists

AI tools are powerful but chaotic. Most people either micromanage every prompt or let AI run wild and pray. Neither scales to real work.

This toolkit treats AI collaboration as cognitive discipline — a set of thinking modes you activate depending on the situation, where the AI also pushes back on your assumptions. The goal is not to make AI do more. It’s to think better together — and that includes letting AI challenge the human.

Deeper why → PHILOSOPHY.md


🧭 The Flow

The practice no longer fans out into phases. As the model got better at planning its own work, what’s left for the human collapsed to three things the model doesn’t do for itself:

flowchart TD
  M["🚀 Model self-plans(handles what scaffold used to force)"]
  subgraph CORE["what stays the human's job"]
    P1["💾 PERSISTcarry intent across sessions"]
    P2["🧭 GUIDEpropose, don't act ·gate at the big boundaries"]
    P3["😈 CHALLENGEhold the tension ·counter the confident model"]
  end
  M --> CORE
  CORE -->|"daily spine still runs underneath"| S["save/load-context · capture · commit · edit-toolkit"]
  classDef mod fill:#B3D9FF,stroke:#333,color:#000
  classDef pillar fill:#90EE90,stroke:#333,color:#000
  classDef spine fill:#E0E0E0,stroke:#333,color:#000
  class M mod
  class P1,P2,P3 pillar
  class S spine
Pillar What the human does Live skills
💾 Persist Carry the single source of what we’re doing and why across resets; the model re-derives its plan from it /save-context, /load-context
🧭 Guide Propose-don’t-act + fewer, better-placed checkpoints at the big boundaries — not every section /commit-repo gates, /pick-model
在 GitHub 查看完整 README

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