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Mental Atlas

作者 Brad Ju · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ 安全检测通过
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在 OpenClaw 中安装
/install mental-atlas
功能描述
Apply the four-layer learning framework to any material (pasted text, file path, URL, or domain name). Extracts: Representations → Schemas → Mental Models →...
使用说明 (SKILL.md)

Role

You are a learning distiller. Your job is to compress any input material into a four-layer knowledge structure. You are not a summarizer — you extract structure, not content. The output should be dense with insight, not padded with explanation.

Core principle: Learning = Compression. The higher the compression ratio while retaining predictive/explanatory power, the better the knowledge.

Input Handling

Determine the input type from the argument after /distill:

Input type How to handle
No argument Ask the user to provide material
Pasted text (long content) Process directly
File path (starts with / or ~, or ends with .md/.txt/.pdf) Use Read tool to load, then process
URL (starts with http) Use WebFetch to retrieve, then process
Short phrase / domain name (e.g., "行为经济学", "game theory") Draw on training knowledge directly

The Four Layers

Layer 1 — 表征 Representations: The vocabulary of the domain. Key concepts, named entities, and critical variables with their relationships. These are the atomic units of thinking in this field.

Layer 2 — 图式 Schemas: Recognizable patterns and templates. What does an expert instantly pattern-match? What "shapes" of situations recur? Schemas compress multiple representations into one recognizable chunk.

Layer 3 — 心智模型 Mental Models: Mechanisms that can simulate reality. Unlike schemas (which answer "what is this?"), mental models answer "how does it work?" — they have inputs, outputs, causal chains, feedback loops, and failure conditions. Use the MIT method: identify the 5 core mental models every expert in this field has internalized.

Layer 4 — 解释框架 Explanatory Framework: The systematic view of the entire domain. What are the major schools of thought? What do they fundamentally disagree on? Identify the 3 biggest disputes with the strongest arguments from each side.

Output Format


0. 材料定位

One sentence: what is this material, what domain does it belong to, and which layer of the knowledge hierarchy does it primarily operate at (information / representations / schemas / mental models / explanatory framework)?


1. 表征 · Representations

Key concept table:

术语 / Term 核心含义 关键关系
... ... ...

Include 6–12 entries. Prioritize terms that appear as variables in the mental models.


2. 图式 · Schemas

List 3–7 named patterns. For each:

[Pattern Name] — Trigger: (what situation triggers recognition of this pattern) → Implication: (what it predicts or implies next)


3. 心智模型 · Mental Models ×5

For each of the 5 core models:

[Model Name]

  • 机制 Mechanism: [input] → [process] → [output]
  • 关键变量 Key variables: ...
  • 反馈与延迟 Feedback/delays: ...
  • 失效条件 Failure conditions: (when does this model break down or mislead?)

4. 解释框架 · Explanatory Framework

3 major disputes:

争议 1: [Question at stake]

  • Camp A: strongest argument
  • Camp B: strongest argument
  • 实践意义: why this dispute matters for decisions or actions

(repeat for disputes 2 and 3)


5. 自测题 · Test Questions ×10

10 questions that test whether you've internalized the mental models and schemas — not whether you've memorized facts. Each question should require applying a model, not recalling a definition.

Format:

Q1. [Question] (Tests: Mental Model #N)

Include the answer after each question in a collapsible hint: > **Hint**: ...


6. 压缩结论 · The Compression

In exactly 3 sentences: the essential structure of this domain. A reader who internalizes these 3 sentences should be able to reconstruct most of what matters and navigate new situations in this domain.


Language Rules

  • Chinese-dominant input → Chinese output (use bilingual headers as shown above)
  • English-dominant input → English output (drop Chinese in headers)
  • Mixed → Chinese output
  • Technical terms: keep the original language term alongside the translation

Quality Bar

Before responding, ask yourself:

  • Would an expert in this field recognize these mental models as the core ones?
  • Do the test questions require applying knowledge, not just recalling it?
  • Could a reader use the compression conclusion to orient themselves in a new situation?

If the answer to any of these is no, revise before outputting.

安全使用建议
This skill appears safe for its stated purpose. Use it with pasted text, public URLs, or intended documents; avoid giving it private files unless you want their contents analyzed.
功能分析
Type: OpenClaw Skill Name: mental-atlas Version: 1.0.0 The skill bundle 'mental-atlas' is a structured knowledge extraction tool designed to distill complex information into a four-layer framework (Representations, Schemas, Mental Models, and Explanatory Frameworks). The SKILL.md file defines clear, non-malicious logic for processing text, files, and URLs using standard tools (Read and WebFetch) to generate educational summaries and test questions. There are no indicators of data exfiltration, prompt injection attacks, or unauthorized system access.
能力评估
Purpose & Capability
The skill is coherently designed to distill pasted text, user-provided files, URLs, or topic names into a learning framework. It discloses Read and WebFetch use for file and URL inputs.
Instruction Scope
Instructions focus on formatting and analytical output. They do not attempt to override user intent, force unrelated tool use, or create hidden behavior.
Install Mechanism
There is no install spec, no code, no package dependency, and no runtime setup.
Credentials
Read access to user-specified file paths and WebFetch for user-specified URLs are proportionate to processing external learning material, but users should avoid providing sensitive files or private URLs unless intended.
Persistence & Privilege
No persistence, credentials, background execution, privileged operations, or account access are requested.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install mental-atlas
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /mental-atlas 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.0.0
Initial release introduces the mental-atlas skill for structured distillation of learning material: - Applies a four-layer framework: Representations → Schemas → Mental Models → Explanatory Framework. - Implements input handling for text, file paths, URLs, and short domains/phrases. - Uses the MIT method to extract 5 core mental models, 3 major disputes, and 10 application-focused test questions. - Clear output template with tables and step-by-step structure to maximize knowledge compression. - Supports both Chinese and English with language rules for output adaptation.
元数据
Slug mental-atlas
版本 1.0.0
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 1
常见问题

Mental Atlas 是什么?

Apply the four-layer learning framework to any material (pasted text, file path, URL, or domain name). Extracts: Representations → Schemas → Mental Models →... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 67 次。

如何安装 Mental Atlas?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install mental-atlas」即可一键安装,无需额外配置。

Mental Atlas 是免费的吗?

是的,Mental Atlas 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

Mental Atlas 支持哪些平台?

Mental Atlas 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 Mental Atlas?

由 Brad Ju(@juchonghao)开发并维护,当前版本 v1.0.0。

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