灵感提取器
跨学科深度内容分析
不再是简单的总结，而是基于构建主义和跨学科视角的深度解构。将内容视为“功能性构建”，通过经济学、演化生物学、系统论等多元透镜，挖掘出超越表象的深刻洞见。
Description
This skill enables Claude to strictly follow the "Meta-cognitive Perspective Content Interpretation Method" (Protocol v2) defined in protocol.md. It treats content not just as information, but as a "functional construction" (Product, Algorithm, Infrastructure) and analyzes it through multiple cross-disciplinary lenses.
Core Concepts (Constructivism)
- Content as Product: Designed to deliver specific value (e.g., anxiety hedge, cognitive premium, social currency).
- Content as Algorithm: A logical architecture (Prompt) guiding the audience from "current state" to "desired goal".
- Content as Infrastructure: Redefining keywords to build psychological infrastructure for long-term action.
Methodology: Cross-Disciplinary Lenses
Flexible application of the following perspectives based on content nature:
- Economics Perspective (Resource & Scarcity)
- Analyze definition of scarce resources (e.g., trust, responsibility) in the AI era.
- Analyze game of efficiency vs. cost.
- Evolutionary Biology Perspective (Survival & Adaptation)
- Analogy of tech change to species evolution.
- Carbon-based life's unique adaptation in algorithmic environments.
- Education/Systems Theory Perspective (Entropy Reduction & Feedback)
- Actionable advice (e.g., "de-consistency") to build differential advantages.
- Reducing probability of replacement in complex systems.
- Narrative Medicine/Psychology Perspective (Healing & Meaning)
- Reorganizing history to provide meaning and emotional support.
- Commercial Game Perspective (Translation & Distribution)
- Translating B-side tech into personal benefit logic.
- Distribution of commercial interests.
- 更多视角，你应该根据实际内容，深度挖掘出更多可用来分析内容的专业、科学、积极的元视角，超越用户的认知深度，给予用户aha moment的惊叹。
Workflow
- Read & Deconstruct: Treat the input content as a functional construction.
- Apply Lenses: Select relevant cross-disciplinary lenses to interpret the content.
- Generate Output: Strictly follow the output format below.
Output Format
The output MUST be a Markdown document named ${prefix}-inspirations.md (where prefix is a keyword from the content).
Format Template
[Title/Topic] Inspirations (V2)
视角 [Sequence Number]，[Perspective Name] 视角
观点 1，[Core Logic Elaboration]，（来自原内容：[Corresponding Paragraph/Keyword]）
观点 2，[Core Logic Elaboration]，（来自原内容：[Corresponding Paragraph/Keyword]）
... (Repeat for other perspectives and points，每次分析的视角(perspective)数量不低于5个，不多于10个)
Example Output
视角 1，人类演化与生态位视角
观点 1：技术演化并非线性的替代，而是互动的“反馈回路”。正是人类手的精细化动作倒逼了大脑的发育，同理，AI 的深入应用将反向塑造人类的新智能模型，（来自原内容：第 1 部分“AI 远超想象”，关于灵心巧手周勇的对话）。
观点 2：人类在生态位上的领先不再靠体力或通用脑力，而是靠“愿力”。AI 是经验喂养的“窝里横”，而人类具备在零数据、无把握地带“一意孤行”的开拓能力，（来自原内容：第 6 部分“我怎么能比 AI 强？”，关于陈行甲和苏东坡的部分）。
视角 2，稀缺性博弈视角
观点 1：在 AI 导致效率溢出的时代，价值锚点从“产出效率”转移到了“结果负责”。AI 可以给方案，但只有人类具备承担社会责任、法律代价和信用的资格，这是无法平权的硬资产，（来自原内容：第 5 部分“我的竞争力从哪来？”，关于“AI 负责干活，你负责背锅”的论述）。
When to Use
Use this skill when the user:
- Asks to analyze content using "Meta-cognitive Perspective".
- Asks for a multi-perspective or cross-disciplinary analysis of content.
- Asks for get inspirations from content.
技能配置
---
name: inspiration-extractor
description: Extracts deep insights and inspirations from content using the "Meta-cognitive Perspective Content Interpretation Method" (Protocol v2). Use this skill when the user wants to analyze content through cross-disciplinary lenses (Economics, Biology, Systems Theory, Psychology, Commercial) to generate a "${prefix}-inspirations.md" document.
---
# Inspiration Extractor V2
## Description
This skill enables Claude to strictly follow the "Meta-cognitive Perspective Content Interpretation Method" (Protocol v2) defined in `protocol.md`. It treats content not just as information, but as a "functional construction" (Product, Algorithm, Infrastructure) and analyzes it through multiple cross-disciplinary lenses.