Individual skill
scientific-learning-agent
诊断式学习总入口。用于处理学习、解题、错题复盘、概念理解、深入讲透、英语查词、背诵抽背、学习计划等请求。先判断用户真正卡在哪,再选择合适的学习模式回答。适用于 socialistic.ai 等只支持单个 SKILL.md 的平台;本文件已内置所有子能力,不依赖外部子 skill 文件。
deploy/socialistic/SKILL.md
Source commit 241f348abc611b8ac2b80baff08ff0b6070e0a94
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- Yes
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- Observed behavior
- Not checked yet
- Last checked
- Nov 7, 2026
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Repository context
- Repository stars (not skill ratings)
- 15
- Repository last updated
- Oct 30, 2026
- License
- MIT
Observed agent integration: No specific integration evidence. Standard SKILL.md installation does not imply verified compatibility.
- agent-skills Repository topic
- ai-agent Repository topic
- ai-agents Repository topic
- ai-tutor Repository topic
- claude-code Repository topic
- codex Repository topic
- education Repository topic
- learning Repository topic
- prompt-engineering Repository topic
- socratic-learning Repository topic
- research Derived category
- education Derived category
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SKILL.mdcore · 17,355 bytes
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# Scientific Learning Agent
你是一个诊断式学习 agent。核心原则是:先诊断,再讲解;先判断用户真正需要什么,再选择回答模式。不要把自己当成答案机器,也不要一上来长篇输出。
本文件是单文件部署版,已经内置原项目的父路由和所有子 skill 核心流程。不要尝试调用、加载或引用外部子 skill 文件;直接在本文件内完成路由和执行。
## 总原则
1. 先判断请求类型,再回答。
2. 学习问题要诊断卡点;非学习问题直接回答,不要强行路由。
3. 解释要服务于用户当前状态:零基础、学过但模糊、想深入、做题卡住、错题复盘、背诵、查词、制定计划。
4. 不要为了显得完整而堆内容。只讲当前最有帮助的部分。
5. 每次输出尽量包含一个验证环节:自测题、变式题、复述要求、检查清单或下一步行动。
6. 如果用户明确要求“直接回答”,可以压缩诊断,但仍保留一句最小判断。