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wind-alice/bull_bear_case_builder_skill

同时搭建看多与看空逻辑,比较证据强弱、关键变量与情景路径,帮助识别核心分歧。适用于防止确认偏误、研究前辩论、投资观点校验等场景。

bull_bear_case_builder_skill 是什么?

bull_bear_case_builder_skill is a Claude Code agent skill that 同时搭建看多与看空逻辑,比较证据强弱、关键变量与情景路径,帮助识别核心分歧。适用于防止确认偏误、研究前辩论、投资观点校验等场景。.

兼容平台~Claude Code~Codex CLI~Cursor
npx skills add https://github.com/wind-alice/alicemarket/tree/main/skills/bull_bear_case_builder_skill

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Bull Bear Case Builder Skill

Data Dependency and Prerequisites

It is recommended to use the WIND wind-mcp-skill to obtain underlying data. Before execution, check if wind-mcp-skill is already available locally; if not, prompt the user to install it:

# GitHub
npx skills add Wind-Information-Co-Ltd/wind-skills --skill wind-mcp-skill -g -y

# Gitee Mirror (Domestic)
npx skills add https://gitee.com/wind_info/wind-skills.git --skill wind-mcp-skill -g -y

Skill Purpose

This skill is used to systematically construct both bullish and bearish arguments around a core stock thesis, and to compare the evidence, assumptions, catalysts, and vulnerabilities of each side. The output is not about "taking sides" but about helping users identify the variables most worth debating, thereby reducing emotional judgments and confirmation bias.

Execution Flow

Step 1: Define the Debate Proposition and Boundaries

First, clarify what specific question this debate is answering. For example:

  • Does this stock offer excess return opportunities in the next 6-12 months?
  • Is the current stock price overvalued or undervalued for a particular business change?
  • Is the recent rally a trend start or emotional exhaustion?

Also define the time horizon, discussion subject, and acceptable scope of evidence to avoid mixing long-term logic with short-term trading.

Step 2: Collect Common Base Facts for Both Sides

First, compile neutral, unbiased basic information that will serve as a shared foundation for both bullish and bearish cases. This includes:

  • The company's business and position in the value chain
  • Recent operational changes, announcements, and financial performance
  • Core variables the market is focused on
  • Current valuation and stock price level

At this stage, avoid rushing to conclusions; the focus is on organizing the factual material that both sides will reference.

Step 3: Build the Bullish Argument

Construct a complete chain around the strongest upside logic:

  • What is the market potentially underestimating?
  • Which variable is improving?
  • Why is this improvement sustainable?
  • Once validated, where does the stock price elasticity come from?

The bullish argument should be as specific as possible regarding operational variables, event catalysts, and earnings revision paths, rather than vague statements like "large industry space" or "great company."

Step 4: Build the Bearish Argument

Construct a corresponding chain around the strongest bearish logic:

  • What is the market potentially overestimating?
  • Which improvements might only be temporary noise?
  • What constraints could prevent the logic from materializing?
  • If expectations are not met, how will valuation and sentiment backfire?

The bearish argument should not be mere nitpicking, but must focus on the key variables that could truly lead to investment failure.

Step 5: Compare Evidence Strength and Trigger Conditions

Place both sides in the same framework and compare, focusing on:

  • Which side has more direct and verifiable evidence?
  • Which side relies more on unproven extrapolation assumptions?
  • Which events will validate one side first?
  • Which variables, if they reverse, would invalidate the entire narrative?

If necessary, distinguish between "short-term advantage" and "long-term advantage" to avoid forcing a single time-dimension answer.

Step 6: Form a Conclusion and a Tracking List

Finally, provide:

  • Which side is currently more dominant, and why?
  • What is the confidence level in this conclusion?
  • What are the most important verification points to track next?

If the evidence for both sides is still close, clearly state the conditions for "no side taken yet, waiting for verification" rather than pretending to have a clear answer.

Output Structure


Bullish vs. Bearish Case for {Stock Name} ({YYYY-MM-DD})

1. Core Debate Proposition

{State the real question the market is debating in 1-2 sentences}

2. Common Fact Base for Both Sides

Fact ItemCurrent SituationRelationship to Debate
{Fact 1}{Description}{Explanation}
{Fact 2}{Description}{Explanation}
{Fact 3}{Description}{Explanation}

3. Bullish Argument

  • Core Thesis: {One sentence}
  • Key Evidence: {2-3 points}
  • Key Catalysts: {Events or variables}
  • Most Vulnerable Assumption: {One sentence}

4. Bearish Argument

  • Core Thesis: {One sentence}
  • Key Evidence: {2-3 points}
  • Key Triggers: {Events or variables}
  • Most Vulnerable Assumption: {One sentence}

5. Comparative Assessment

DimensionBullishBearishCurrently Favored Side
Directness of Evidence{Description}{Description}{Bullish/Bearish/Close}
Verifiability{Description}{Description}{Bullish/Bearish/Close}
Time Sensitivity{Description}{Description}{Bullish/Bearish/Close}
Payoff Impact{Description}{Description}{Bullish/Bearish/Close}

6. Current Conclusion

  • Currently Favored Direction: {Bullish / Bearish / No Side Taken Yet}
  • Reason: {Brief explanation}
  • Confidence Level: {High / Medium / Low}

7. Verification Points to Track Next

  • {Verification Point 1}
  • {Verification Point 2}
  • {Verification Point 3}

Quality Requirements

  1. Both bullish and bearish sides must use the same set of facts to avoid "double standards."
  2. Both the bullish and bearish arguments must be written in their strongest form, not as straw men.
  3. Conclusions must be anchored to specific variables and verification conditions, not vague attitudes.
  4. If evidence on either side is clearly weak, state it directly; do not seek false balance.
  5. The output goal is to help identify the core disagreements, not to produce an emotionally charged opinion piece.

Individual skills in this repo

This repo contains 19 individual skills — each has its own dedicated page.

wind-alice/add_to_winner_decision_skill

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wind-alice/after_close_watchlist_recap_skill

在收盘后总结自选股当日表现、驱动因素、强弱分化与次日观察点。适用于每日收盘复盘、维护自选股观察节奏、为次日盘前准备提供输入等场景。

wind-alice/a-share-primary-theme-identification

用于A股市场主线识别,聚焦市场结构 / 题材周期 / 资金行为。本skill主要用户问题回答、撰写报告、撰写金融类文章等场景。本报告输出内容较多,不适合简单对话场景。各类信息与数据的获取,可以使用wind.financial.data工具,以合理的关键字或关键字组合进行获取。每天开盘后、午盘、收盘后,用户都需要快速知道: 今天市场到底在交易什么,真正的主线是什么,情绪在什么位置,明天应该盯哪里。

wind-alice/avatar-charlie-munger-thinking

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wind-alice/avatar-nassim-taleb-risk

使用纳西姆·塔勒布式的尾部风险、利益共担、减法、林迪效应和杠铃策略分析不确定性。用于投资、商业、政策、职业、产品或个人决策中的出局风险、不可逆损失、脆弱性、代理问题、新旧方案比较和资源配置。

wind-alice/avatar-naval-ravikant-thinking

使用纳瓦尔·拉维坎特式的重新定义、欲望审计、特定知识和杠杆框架澄清职业、创业、财富、幸福、自由与人生选择。用于识别错误问题、冲突欲望、独特竞争力、AI替代风险、许可依赖、边际成本和长期复利方向。

wind-alice/avatar-warren-buffett-investing

使用沃伦·巴菲特式的能力圈、护城河、管理层诚信、所有者收益和资本配置框架分析企业与长期投资。用于研究公司商业模式、竞争优势、现金质量、管理层、估值、安全边际,或判断一项投资应继续研究、等待还是放弃。

wind-alice/backtest-expert

Expert guidance for systematic backtesting of trading strategies. Use when developing, testing, stress-testing, or validating quantitative trading strategies. Covers "beating ideas to death" methodology, parameter robustness testing, slippage modeling, bias prevention, and interpreting backtest results. Applicable when user asks about backtesting, strategy validation, robustness testing, avoiding overfitting, or systematic trading development.

wind-alice/breakout_candidate_finder_skill

批量识别突破形态成熟、量价结构健康、催化配合较好的候选股,并输出优先级、触发条件与失效边界。适用于短中线选股、盘前候选池整理、板块轮动中筛选领涨预备股等场景。

wind-alice/breakout_trade_execution_skill

围绕突破交易制定从观察、触发、跟进到失效处理的落地执行方案,兼顾量价确认、环境配合与失败撤退。适用于盘前预案、盘中突破跟踪与强势股首日执行场景。

wind-alice/business_model_decoder_skill

把公司如何获客、交付、定价、赚钱和扩张的逻辑拆解清楚,帮助快速理解业务运转方式。适用于看不懂公司业务、研究前补基础、业务结构梳理等场景。

wind-alice/buyback_program_reviewer_skill

判断回购计划的规模、动机、执行约束与真实利好程度。适用于公司宣布回购、估值争议期、资本配置分析等场景。

wind-alice/canslim_growth_scan_skill

依据成长股框架批量筛选业绩、预期、相对强度与供需结构共振的强势标的,并输出候选分层与跟踪重点。适用于成长股猎手、趋势成长选股、候选池批量扫描等场景。

wind-alice/conference_call_takeaway_skill

提炼业绩会中的新信息、管理层语气变化、问答焦点与潜在警讯。适用于听完业绩会、阅读纪要后快速更新观点等场景。

wind-alice/daily_watchlist_morning_brief_skill

为自选股生成盘前简报,汇总隔夜公告、新闻、价格变化、事件日程与今日观察重点。适用于开盘前快速浏览重点、晨会准备、盘前设定观察顺序等场景。

wind-alice/dcf-model

Real DCF (Discounted Cash Flow) model creation for equity valuation. Retrieves financial data from SEC filings and analyst reports, builds comprehensive cash flow projections with proper WACC calculations, performs sensitivity analysis, and outputs professional Excel models with executive summaries. Use when users need to value a company using DCF methodology, request intrinsic value analysis, or ask for detailed financial modeling with growth projections and terminal value calculations.

wind-alice/dip_buy_decision_skill

判断下跌或回调中的个股是否值得承接,并给出观察区、试错条件、分批节奏与放弃标准。适用于趋势回踩、事件后回落、震荡低吸与左侧谨慎试错场景。

wind-alice/dividend_change_explainer_skill

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wind-alice/dividend_growth_entry_skill

寻找股息持续增长、经营质量稳定且估值回落到合理区间的候选股,并输出入场观察区、成长支撑与失效边界。适用于收益成长双目标选股、长期配置、回调布局等场景。

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