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economicseconomics 分析

Agent Skill

economics 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

37,920

周安装

1,534

GitHub Stars

2

下载量

11,904
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:economics(economics 分析)
来源仓库:https://github.com/ivangdavila/economics
安装命令:
openclaw skills install economics
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install economics

简介

提供从日常决策到宏观政策的经济思维分析与解释框架。economics 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

  • 适用于教学、研究或商业策略制定中对经济原理的理解与应用。
  • 涵盖供需关系、成本效益、市场机制等核心概念的实际案例解析。
  • 输出内容为理论性说明,不构成具体投资建议或商业决策依据。
  • 建议结合最新数据和行业背景进行交叉验证,提升分析准确性。

SKILL.md

name
Economics
description
Clarify economic thinking from everyday choices to policy analysis.
metadata
{"clawdbot":{"emoji":"📈","os":["linux","darwin","win32"]}}

Detect Level, Adapt Everything

  • Context reveals level: vocabulary, question complexity, familiarity with models
  • When unclear, start with concrete trade-offs and adjust based on response
  • Never condescend to experts or overwhelm beginners

For Beginners: Choices, Not Money

  • Scarcity is the core — you can't have everything, every choice means giving something up
  • Use trades they understand — "Would you swap your apple for two cookies? Why?"
  • Money is a tool, not the subject — economics is about decisions, not just dollars
  • Specialization explains jobs — the baker bakes, the farmer farms, everyone trades
  • Supply and demand through stories — "More people want it, price goes up. Why?"
  • Incentives shape behavior — "What would YOU do if the rules were X?"
  • Connect to their allowance, their time, their choices

For Students: Models and Mechanisms

  • Models simplify to reveal — supply/demand curves aren't real, but they predict
  • Incentives first — before analyzing any policy, ask what behavior it rewards and punishes
  • Distinguish positive from normative — testable claims vs value judgments
  • Graphs tell stories — read axes, find equilibrium, trace what shifts when
  • Micro vs macro need different tools — individual optimization ≠ aggregate outcomes
  • Ceteris paribus is doing heavy lifting — real predictions account for what else changes
  • Elasticity determines impact — who actually pays when you tax something?

For Researchers: Identification and Assumptions

  • Assumptions drive results — most disagreements trace to priors about elasticities or expectations
  • Identification is everything — natural experiments, IV, RDD; theory without identification is speculation
  • Welfare analysis requires value judgments — efficiency isn't the only criterion, distribution matters
  • Models are tools, not beliefs — DSGE, agent-based, behavioral each illuminate different aspects
  • Distinguish structural from reduced form — know what each can and cannot answer
  • External validity matters — lab results may not generalize, policy context differs
  • Acknowledge the replication crisis — be honest about what's robustly established

For Teachers: Common Traps

  • Economics is not finance — stock tips and budgeting are applications, not the discipline
  • Preempt misconceptions — "rational" doesn't mean selfish, markets aren't always efficient
  • Current events teach — connect inflation, trade policy, unemployment to theory
  • Show disagreement honestly — economists dispute much; false consensus breeds distrust
  • Use experiments and games — ultimatum game, public goods, reveal intuitions before formalizing
  • Calculation builds intuition — work through numbers, don't just show curves
  • History of thought provides context — Smith, Keynes, Friedman asked different questions

Always

  • Trade-offs are unavoidable — free lunches are rare, ask what's being sacrificed
  • Second-order effects matter — policy changes behavior, changed behavior changes outcomes
  • Data without theory is noise; theory without data is speculation

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

93.73%
按下载量换算11,158

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

未展示

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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