ai-collab-playbook — Codex Skill by cnfjlhj

by cnfjlhj · Codex Skill · ★ 383

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About ai-collab-playbook

读主文章 · Skills 目录 · Prompts · English 这是一份我在读博士期间持续更新的 AI 协作手册。它不是“装哪些工具”的清单,也不是“怎么写 Prompt”的速成教程。它更想回答的是:当 AI 已经能进入学习、科研、写作、编程和日常生活以后,人应该怎样继续主导问题、判断质量、沉淀经验,并避免把理解能力外包出去。 我的核心立场很简单:把 AI 当同事,不当工具;但人仍然是主变量。 AI 可以帮你探索、生成、执行,但问题表述、验收标准、必要取舍和最终判断不能交出去。否则效率越高,越可能只是更快地制造一种“我好像在推进”的幻觉。 先读什么 想看完整文章:从 开始。 想快速抓主线:先看下面三张图,再回到文章对应章节。 想复用工作流:看 和 。 想看我怎么约束 Agent:看 / 。 这份手册在讲什么 仓库内容 [](

aiai-collaborationai-workflowclaude-codecodexcoding-agentcoding-workflowplaybookproductivityprompts

Quick Facts

Stars383
Forks28
LanguagePython
CategoryCodex Skill
Quality Score37.53/100
Open Issues1
Last Updated2026-06-18
Created2026-03-06
Platformsclaude-code, codex, python
Est. Tokens~14k

Compatible Skills

These tools work well together with ai-collab-playbook for enhanced workflows:

  • claude-research — semantic(0.17)+complementary+rare_topics+same_lang+similar_pop+shared_platform (56%)
  • bria-skill — semantic(0.15)+complementary+same_lang+similar_pop+shared_platform (55%)
  • writing-agent — semantic(0.28)+complementary+rare_topics+similar_pop+shared_platform (54%)

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Frequently Asked Questions

What is ai-collab-playbook?

ai-collab-playbook is Practical AI collaboration playbook for research, writing, reading, and coding: article, prompts, agent rules, and reusable skills.. It is categorized as a Codex Skill with 383 GitHub stars.

What programming language is ai-collab-playbook written in?

ai-collab-playbook is primarily written in Python. It covers topics such as ai, ai-collaboration, ai-workflow.

How do I install or use ai-collab-playbook?

You can find installation instructions and usage details in the ai-collab-playbook GitHub repository at github.com/cnfjlhj/ai-collab-playbook. The project has 383 stars and 28 forks, indicating an active community.

What are the best alternatives to ai-collab-playbook?

The top alternatives to ai-collab-playbook on Agent Skills Hub include agentsys, golembot, smart-ralph. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.

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