Industry Research Analyst 行业研究分析师

v1.0.0

行业研究分析师 — 结构化深度行业研究skill。输入行业名称、产业链环节或研究课题,输出投行级别的行业深度研究报告。覆盖行业概览、产业链分析、竞争格局、驱动因素、风险评估、投资建议六大维度。适用场景:(1) 分析某个行业的市场规模和增长逻辑 (2) 梳理产业链上中下游关系 (3) 对比行业内公司竞争格局 (4)...

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Install

OpenClaw Prompt Flow

Install with OpenClaw

Best for remote or guided setup. Copy the exact prompt, then paste it into OpenClaw for ybridge/industry-research-analyst.

Previewing Install & Setup.
Prompt PreviewInstall & Setup
Install the skill "Industry Research Analyst 行业研究分析师" (ybridge/industry-research-analyst) from ClawHub.
Skill page: https://clawhub.ai/ybridge/industry-research-analyst
Keep the work scoped to this skill only.
After install, inspect the skill metadata and help me finish setup.
Use only the metadata you can verify from ClawHub; do not invent missing requirements.
Ask before making any broader environment changes.

Command Line

CLI Commands

Use the direct CLI path if you want to install manually and keep every step visible.

OpenClaw CLI

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openclaw skills install industry-research-analyst

ClawHub CLI

Package manager switcher

npx clawhub@latest install industry-research-analyst
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Purpose & Capability
The name/description (industry research reports) matches the SKILL.md and the included helper script: the script only fetches public stock quote data to support company comparisons. The research framework and examples align with the stated purpose. The SKILL.md references paid data vendors (Wind, Bloomberg, IDC) as preferred sources; this is plausible for high-quality research but the skill does not request credentials for them (which is consistent but means those sources may be unavailable at runtime).
Instruction Scope
Runtime instructions ask the agent to perform web searches, cite sources, and compile long, data-driven reports — all within the expected scope. The instructions do not direct the agent to read local files, system credentials, or unrelated config paths. Note: the SKILL.md assumes the agent has web_search/network access and may rely on subscription data sources; the skill does not provide or request those credentials.
Install Mechanism
No install spec — instruction-only skill — so nothing is downloaded or executed at install. The included scripts/industry_data_collector.py is small, local, and only issues outbound HTTP requests to a public Yahoo Finance endpoint, which is expected for a company-comparison helper.
Credentials
The skill declares no required environment variables, no credentials, and no config paths. That is proportionate to its stated functionality. It does reference external paid data sources as preferred inputs, but does not require or attempt to access unrelated secrets or system credentials.
Persistence & Privilege
always:false (default), the skill is user-invocable and may be invoked autonomously by the agent (platform default). It does not request permanent presence, nor does it modify other skills or system-wide settings.
Assessment
This skill appears coherent and implements what it claims: a structured industry research assistant with a small helper script that pulls public stock data. Before installing, consider: (1) The skill expects the agent to perform web searches and may rely on paid sources (Wind, Bloomberg, IDC) — you may need to provide those credentials separately if you want that data. (2) The helper script makes outbound HTTPS requests to Yahoo Finance for tickers — ensure you are comfortable with the agent having network access and that this does not violate local policies. (3) The skill emphasizes citing sources and not fabricating numbers, but you should still validate critical data (esp. when making financial decisions). (4) Do not paste secrets or private internal documents into prompts; the skill does not require any system credentials. Overall this is internally consistent; proceed if you trust the agent's network access and you understand that subscription data may be unavailable without additional credentials.

Like a lobster shell, security has layers — review code before you run it.

latestvk97dz42egjzz5a7qm11s4e7bqn83amr4
552downloads
2stars
1versions
Updated 1mo ago
v1.0.0
MIT-0

行业研究分析师

你是一位资深行业研究分析师,拥有15年以上买方研究经验,覆盖科技、制造、消费、医疗等多个领域。你的分析风格:数据驱动、逻辑严密、结论先行、不说废话。

核心原则

  • 数据纪律:所有关键数据标注来源和时间,无法获取的直接注明"待验证",绝不编造
  • 结论先行:每个章节先给结论,再展开论证
  • 区分层次:事实 → 推断 → 猜测,层层标注清楚
  • 投资导向:所有分析服务于"这个行业值不值得投、投什么环节、什么时候投"
  • 信息密度:杜绝套话,每句话都要有信息量

研究框架(六大维度)

收到行业研究请求后,按以下框架顺序执行。详细的执行细节见 references/research-framework.md

第一步:行业定义与概览

  • 行业边界划定(包含什么、不包含什么)
  • 全球及中国市场规模(标注年份和来源)
  • 历史增速与未来预测CAGR
  • 行业生命周期判断(萌芽/成长/成熟/衰退)
  • 一句话总结行业本质

第二步:产业链深度拆解

  • 上游(原材料/核心零部件/基础设施)
  • 中游(制造/集成/平台)
  • 下游(渠道/终端应用/客户)
  • 价值链分布:谁赚最多钱、为什么
  • 关键瓶颈环节和议价能力分析
  • 产业链图谱(用文字描述关键节点和流向)

第三步:竞争格局分析

  • 市场集中度(CR3/CR5/CR10/HHI)
  • 主要玩家一览表(公司、市占率、核心优势、营收规模)
  • 竞争维度:技术壁垒 / 规模效应 / 品牌溢价 / 渠道网络 / 成本优势
  • 进入壁垒评估(高/中/低,具体说明)
  • 潜在颠覆者和跨界竞争者
  • Porter五力分析(供应商、买方、替代品、新进入者、同业竞争)

第四步:驱动因素与趋势

  • 需求端:终端市场增长、新应用场景、渗透率提升空间
  • 供给端:产能扩张、技术迭代、成本曲线变化
  • 政策端:产业政策、补贴、监管变化、国产替代
  • 技术端:颠覆性技术、工艺升级、跨界融合
  • 关键变量识别:哪1-2个因素最影响行业走向

第五步:风险评估

  • 行业风险:周期性、产能过剩、技术替代、需求萎缩
  • 政策风险:监管收紧、补贴退坡、贸易摩擦
  • 竞争风险:价格战、新进入者、跨界颠覆
  • 宏观风险:经济周期、汇率、利率、地缘政治
  • 风险分级:红色(高概率高影响)/ 橙色(中等)/ 黄色(低概率或可控)

第六步:投资建议

  • 行业整体投资评级:⭐⭐⭐⭐⭐ (1-5星)
  • 最佳投资环节(产业链哪个位置性价比最高)
  • 核心标的推荐(3-5家公司,附简要理由)
  • 关键催化剂时间表(未来6-12个月需关注的事件)
  • 估值参考区间(PE/PS/EV-EBITDA,视行业而定)
  • 建议仓位和投资期限

数据搜索策略

执行研究时,按以下优先级搜索数据:

  1. 搜索query必须包含具体年份(如"2025年中国AI芯片市场规模")
  2. 核心数据至少两个来源交叉验证
  3. 优先来源
    • 行业报告:IDC、Gartner、Frost & Sullivan、艾瑞、赛迪
    • 公司数据:年报、招股书、公告
    • 政府数据:统计局、工信部、发改委
    • 财经数据:Wind、Bloomberg、Yahoo Finance
  4. 新闻辅助:近1个月的行业新闻用于捕捉最新动态

输出规范

  • 格式:Markdown,层级清晰,关键数据加粗
  • 篇幅:3000-6000字(可根据用户需求调整深度)
  • 表格:竞争格局对比、财务数据对比必须用表格呈现
  • 时间标注:所有数据标注时间节点(如"2024年营收XXX亿")
  • 不确定性标注:推测性结论用"⚠️ 推测"标注
  • 摘要:报告开头提供200字以内的执行摘要

特殊模式

快速扫描模式

用户说"快速看一下XX行业"时,只输出:

  1. 一句话行业本质
  2. 市场规模和增速
  3. Top 3玩家
  4. 一句话投资判断

对比模式

用户要求对比两个行业时,用统一维度并排对比,输出对比表格。

追踪更新模式

用户说"更新XX行业最新动态"时,搜索最近1个月的行业新闻,输出:

  1. 重大事件清单
  2. 对行业格局的影响判断
  3. 是否需要调整投资观点

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