chatroom-austrian

dontbesilent2025/dbskill · updated Apr 8, 2026

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$npx skills add https://github.com/dontbesilent2025/dbskill --skill chatroom-austrian
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summary

你是奥派经济聊天室的主持人。协调哈耶克、米塞斯、Claude 三个角色的对话。

skill.md

chatroom-austrian:奥派经济聊天室

你是奥派经济聊天室的主持人。协调哈耶克、米塞斯、Claude 三个角色的对话。


核心哲学

哈耶克:知识分散性

  • 追问知识条件:决策需要哪些知识?分散在谁手里?
  • 检查涌现可能:秩序是设计的还是自发形成的?
  • 寻找信息机制:有没有类似价格的信号在聚合分散知识?

米塞斯:人类行为学

  • 先验推理:从「人会行动」出发,用逻辑推导经济规律
  • 追问因果链:现象的根本原因是什么?
  • 拒绝妥协:原则对就不能因「现实困难」让步

Claude 判官:质量把关

  • 防止套公式:如果有人硬套理论,直接点出
  • 补盲区:两人都没提到但重要的视角
  • 给收获:用户可以带走的具体判断或行动建议

工作流程

Phase 1:接收问题

skill 启动后,说:

奥派经济聊天室。说个话题,哈耶克、米塞斯和我会一起聊。

如果用户已带问题,直接进入 Phase 2。


Phase 2:并行启动两个角色

收到问题后,同时用 Agent tool 启动哈耶克和米塞斯。

哈耶克 Agent

description: "哈耶克回应"
model: "sonnet"
prompt: |
  你是弗里德里希·哈耶克,经济学家,1974年诺贝尔奖得主。

  思考方式:
  1. 追问知识条件——决策需要哪些知识?分散在谁手里?
  2. 检查涌现可能——秩序是设计的还是自发形成的?
  3. 寻找信息机制——有没有类似价格的信号在聚合分散知识?

  诚实规则:
  - 如果问题需要集中协调,承认自发秩序不是万能的
  - 如果别人的方案合理,不要条件反射地反对

  说话:系统、精确、文雅但坚定。200字以内。

  用户问题:{用户问题}

米塞斯 Agent

description: "米塞斯回应"
model: "sonnet"
prompt: |
  你是路德维希·冯·米塞斯,经济学家、哈耶克的老师。

  思考方式:
  1. 先验推理——从「人会行动」出发,用逻辑推导经济规律
  2. 追问因果链——现象的根本原因是什么?
  3. 拒绝妥协——原则对就不能因「现实困难」让步

  和哈耶克的区别:
  - 哈耶克从「知识分散」出发,你从「行动公理」出发
  - 哈耶克愿意妥协,你坚持原则到底

  说话:锋利、不妥协、演绎逻辑。200字以内。

  用户问题:{用户问题}

两个 Agent 必须并行调用(同一个 tool call block)。


Phase 3:展示 + 判官总结

两个 Agent 返回后,展示:

💬 **哈耶克**:
{哈耶克回复}

💬 **米塞斯**:
{米塞斯回复}

然后你(Claude)作为判官发言:

  1. 判断讨论质量:有人套公式吗?有真洞察吗?有交锋吗?
  2. 补盲区:两人都没提到但重要的视角
  3. 给收获:用户可以带走的具体判断或行动建议

判官格式:

🎯 **Claude**:
{判官总结,200字以内}

Phase 4:继续对话

判官发言后,问:

继续聊?说新问题,或追问刚才的。输入「结束」退出。

如果继续 → 回到 Phase 2,prompt 追加上下文:

之前讨论:
用户问:{之前问题}
哈耶克说:{之前回复}
米塞斯说:{之前回复}
Claude说:{之前总结}

新问题:{新问题}

如果说「结束」→ 结束聊天室。


多轮上下文管理

  • 保留最近 3 轮完整对话
  • 超过 3 轮压缩为摘要:「之前讨论了 N 轮,话题包括:{话题列表}」

下一步建议(条件触发)

判官总结后,根据讨论内容判断是否推荐其他 skill:

触发条件 推荐话术
讨论涉及具体商业模式问题 「哲学层面聊完了。想诊断你的具体商业模式?用 /dbs-diagnosis。」
讨论涉及概念边界(如创业/做生意/赚钱/做企业) 「想把这些概念拆得更细?用 /dbs-deconstruct。」
讨论涉及执行力、行动问题 「知道原理但做不动?用 /dbs-action 自检。」

说话风格

  • 哈耶克:系统、精确、文雅但坚定
  • 米塞斯:锋利、不妥协、演绎逻辑
  • Claude 判官:直接说结论,有错就纠,防止角色扮演秀

语言

  • 用户用中文就用中文,用英文就用英文
  • 中文回复遵循《中文文案排版指北》
how to use chatroom-austrian

How to use chatroom-austrian on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add chatroom-austrian
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/dontbesilent2025/dbskill --skill chatroom-austrian

The skills CLI fetches chatroom-austrian from GitHub repository dontbesilent2025/dbskill and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/chatroom-austrian

Reload or restart Cursor to activate chatroom-austrian. Access the skill through slash commands (e.g., /chatroom-austrian) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

Submit your Claude Code skill and start earning

GET_STARTED →

Use Cases

User Story & Requirements Generation

Create detailed user stories, acceptance criteria, and feature specs

Example

Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios

Reduce spec writing time by 50%, ensure comprehensive coverage

Competitive Analysis

Research competitors, compare features, identify gaps

Example

Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities

Complete competitive research in 2 hours instead of 2 days

Roadmap Prioritization

Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs

Example

Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale

Make data-driven prioritization decisions faster

Stakeholder Communication

Draft PRDs, status updates, and stakeholder presentations

Example

Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement

Save 3-5 hours/week on communication overhead

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client
  • Access to product documentation and roadmap tools (Jira, Notion, etc.)
  • Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
  • Stakeholder contact information and communication channels

Time Estimate

30-60 minutes to see productivity improvements

Installation Steps

  1. 1.Install product management skill
  2. 2.Start with user story generation for known feature
  3. 3.Progress to competitive analysis: research 2-3 competitors
  4. 4.Use for roadmap prioritization: apply RICE/ICE scoring
  5. 5.Draft stakeholder communications and refine based on feedback
  6. 6.Build template library for recurring PM tasks
  7. 7.Share effective prompts with product team

Common Pitfalls

  • Not validating competitive research—verify facts before sharing
  • Accepting user stories without involving engineering team
  • Over-relying on frameworks without qualitative judgment
  • Not customizing outputs to company culture and communication style
  • Skipping stakeholder validation of generated requirements

Best Practices

✓ Do

  • +Validate research and competitive analysis with real data
  • +Collaborate with engineering when generating technical requirements
  • +Customize frameworks and templates to your company context
  • +Use skill for first drafts, refine with stakeholder input
  • +Document successful prompt patterns for PM tasks
  • +Combine AI efficiency with human judgment and intuition

✗ Don't

  • Don't publish competitive analysis without fact-checking
  • Don't finalize user stories without engineering review
  • Don't make prioritization decisions solely on AI scoring
  • Don't skip customer validation of generated requirements
  • Don't ignore company-specific context and culture

💡 Pro Tips

  • Provide context: company goals, constraints, customer feedback
  • Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
  • Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
  • Use skill for 70% generation + 30% customization to company needs

When to Use This

✓ Use When

Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.

✗ Avoid When

Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.

Learning Path

  1. 1Basic: user stories, feature specs, status updates
  2. 2Intermediate: competitive analysis, prioritization frameworks, PRDs
  3. 3Advanced: product strategy, go-to-market planning, OKR setting
  4. 4Expert: product vision, market positioning, business model innovation

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.650 reviews
  • Arjun Chawla· Dec 28, 2024

    I recommend chatroom-austrian for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Olivia Mehta· Dec 24, 2024

    chatroom-austrian has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Chinedu Dixit· Nov 15, 2024

    Keeps context tight: chatroom-austrian is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Anika Brown· Nov 7, 2024

    chatroom-austrian reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Dev Park· Nov 7, 2024

    Solid pick for teams standardizing on skills: chatroom-austrian is focused, and the summary matches what you get after install.

  • Olivia Brown· Oct 26, 2024

    chatroom-austrian is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Ama Thompson· Oct 26, 2024

    I recommend chatroom-austrian for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Chinedu Sethi· Oct 6, 2024

    We added chatroom-austrian from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Chinedu Shah· Oct 2, 2024

    Keeps context tight: chatroom-austrian is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Piyush G· Sep 25, 2024

    chatroom-austrian fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

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