/install map-domain-experts
Map Domain Experts
Overview
Use this skill to turn "I want to quickly learn X" into a compact expert map: who matters, what they agree on, where they disagree, and how to start learning. Optimize for accuracy, intellectual structure, and traceable evidence rather than a generic reading list.
Default to answering in the user's language.
Workflow
1. Scope the Field
If the user leaves the field as a placeholder, e.g. 【领域名称】, ask for the field. If the field is broad, proceed with a clear scope assumption unless that would make the answer misleading.
State the interpreted scope in 1-2 sentences before the main answer:
- domain boundary, such as subfield, time period, region, or applied vs academic angle
- whether "expert" includes scholars, builders, operators, critics, or public intellectuals
2. Build an Evidence Base
For current, niche, contested, or high-stakes domains, verify with browsing or available primary sources. Prefer:
- seminal papers/books and publisher pages
- university, lab, institutional, or official biography pages
- citation indexes, conference keynotes, standards bodies, widely adopted tools/frameworks
- reputable interviews, lectures, debates, or essays when they clarify a living practitioner's view
Do not fabricate expertise, works, citations, or consensus. If evidence is thin, say so and reduce confidence.
3. Select 5-10 Representative People
Choose people who collectively explain the field, not merely the most famous names. Balance:
- founders/seminal theorists
- method builders or empirical researchers
- practitioners who changed real-world practice
- critics or alternative schools that reveal fault lines
- current voices if the field is active and changing
For each person, capture why they matter in one concrete sentence: concept introduced, method created, institution shaped, tool built, policy changed, or debate reframed.
4. Extract Consensus and Disagreement
Core consensus must be a small set of propositions that most selected experts would recognize, even if they phrase them differently. Tie each consensus point to multiple experts.
Disagreements should be axes, not trivia. Look for:
- theory: what explains the phenomenon?
- method: what counts as valid evidence or good practice?
- values: what outcomes should be optimized, protected, or avoided?
- scope: where does the theory/method stop working?
- strategy: what should beginners, organizations, or policymakers do first?
For each disagreement, name the sides, the stakes, and a concrete example of how the disagreement changes action.
Output Format
Use this structure unless the user asks for another format:
范围说明: State the scope assumption.代表人物: List 5-10 experts with 1-2 sentences each on why they matter.核心共识: Summarize 3-6 shared claims.关键分歧: Summarize the most important disagreements by axis.对照表: Include columns:专家 | 代表作品/论文/观点 | 核心主张 | 与其他人的分歧入门学习路线: Give a staged path:先读/先看->再读/再看->对照阅读->继续追踪的问题资料来源: Include concise citations or links when sources were used.
Quality Bar
The result should feel like a map of the field's intellectual terrain. Avoid flat encyclopedia summaries. Make tradeoffs visible: why these people, why these disagreements, and why this learning order.
- 确保已安装 OpenClaw(本地或 Docker 部署)
- 在对话框中输入安装命令:
/install map-domain-experts - 安装完成后,直接呼叫该 Skill 的名称或使用
/map-domain-experts触发 - 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
领域专家地图 是什么?
Use when a user wants to quickly learn a domain/field/领域 by mapping representative experts, scholars, practitioners, seminal works, core consensus, major dis... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 35 次。
如何安装 领域专家地图?
在 OpenClaw 或 Claude Code 对话框中运行命令「/install map-domain-experts」即可一键安装,无需额外配置。
领域专家地图 是免费的吗?
是的,领域专家地图 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。
领域专家地图 支持哪些平台?
领域专家地图 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 领域专家地图?
由 haidong(@harrylabsj)开发并维护,当前版本 v1.0.0。