consulting-analysis by bytedance/deer-flow
npx skills add https://github.com/bytedance/deer-flow --skill consulting-analysis本技能生成专业的、咨询级别的 Markdown 格式研究报告,涵盖市场分析、消费者洞察、品牌战略、财务分析、行业研究、竞争情报、投资研究、宏观经济分析等领域。它分两个不同的阶段运行:
输出遵循麦肯锡/波士顿咨询公司的咨询语调标准。报告语言遵循 output_locale 设置(默认:zh_CN,即中文)。
严格遵守规则:报告中呈现的所有数据以及图表中可视化的数据必须直接来源于提供的数据摘要或外部搜索结果。
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output_locale 指定的语言输出报告,并采用专业咨询语调在以下情况始终加载此技能:
给定一个研究主题(例如,“Z世代护肤市场分析”、“新能源汽车行业竞争格局”、“品牌X消费者画像”),生成一个完整的分析框架,作为下游数据收集和最终报告生成的蓝图。
| 输入 | 描述 | 必需 |
|---|---|---|
| 研究主题 | 待分析的主题或问题 | 是 |
| 范围 / 限制 | 地理范围、时间范围、行业细分、目标受众等 | 可选 |
| 特定角度 | 用户希望探索的任何特定角度或假设 | 可选 |
| 领域 | 分析领域:市场、金融、行业、品牌、消费者、投资等 | 推断 |
| 领域 | 典型维度 |
|---|---|
| 市场分析 | 市场规模、增长趋势、市场细分、增长驱动力、竞争格局、消费者画像 |
| 品牌分析 | 品牌定位、市场份额、消费者认知、营销策略、竞争对手比较 |
| 消费者洞察 | 人口统计画像、购买行为、决策旅程、痛点、场景分析 |
| 财务分析 | 宏观环境、行业趋势、公司基本面、财务指标、估值、风险评估 |
| 行业研究 | 价值链分析、市场规模、竞争格局、政策环境、技术趋势、进入壁垒 |
| 投资尽职调查 | 商业模式、财务健康状况、管理层评估、市场机会、风险因素、退出途径 |
| 竞争情报 | 竞争对手识别、战略比较、SWOT分析、差异化定位、市场动态 |
基于识别的领域和研究主题,选择一个或多个专业的分析框架来构建每个章节的推理逻辑。所选框架指导章节骨架中的分析逻辑(步骤 1.3)。
| 框架 | 描述 | 最佳适用场景 |
|---|---|---|
| SWOT 分析 | 优势、劣势、机会、威胁 | 品牌评估、竞争定位、战略规划 |
| PEST / PESTEL 分析 | 政治、经济、社会、技术(+ 环境、法律) | 宏观环境扫描、市场进入评估、政策影响分析 |
| 波特五力模型 | 供应商议价能力、买方议价能力、新进入者威胁、替代品威胁、行业竞争 | 行业竞争格局、进入壁垒评估、利润率分析 |
| 波特钻石模型 | 生产要素、需求条件、相关及支持产业、企业战略、结构与同业竞争 | 国家/地区竞争优势分析 |
| VRIO 分析 | 价值性、稀缺性、难以模仿性、组织性 | 核心竞争力评估、资源优势分析 |
| 框架 | 描述 | 最佳适用场景 |
|---|---|---|
| STP 分析 | 市场细分、目标市场选择、市场定位 | 市场细分、目标市场选择、品牌定位 |
| BCG 矩阵(增长-份额矩阵) | 明星、现金牛、问号、瘦狗 | 产品组合管理、资源配置决策 |
| 安索夫矩阵 | 市场渗透、市场开发、产品开发、多元化 | 增长战略选择 |
| 产品生命周期 | 引入期、成长期、成熟期、衰退期 | 产品策略制定、市场时机决策 |
| TAM-SAM-SOM | 总市场 / 可服务市场 / 可获得市场 | 市场规模估算、机会量化 |
| 技术采用生命周期 | 创新者 → 早期采用者 → 早期大众 → 晚期大众 → 落后者 | 新兴技术/品类渗透分析 |
| 框架 | 描述 | 最佳适用场景 |
|---|---|---|
| 消费者决策旅程 | 认知 → 考虑 → 评估 → 购买 → 忠诚 | 消费者行为路径映射、触点优化 |
| AARRR 漏斗(海盗指标) | 获取、激活、留存、收入、推荐 | 用户增长分析、转化率优化 |
| RFM 模型 | 最近一次消费、消费频率、消费金额 | 客户价值细分、精准营销 |
| 马斯洛需求层次理论 | 生理需求 → 安全需求 → 社交需求 → 尊重需求 → 自我实现需求 | 消费者心理分析、产品价值主张 |
| 待办任务 | 用户在特定情境下需要完成的“任务” | 需求洞察、产品创新方向 |
| 框架 | 描述 | 最佳适用场景 |
|---|---|---|
| 杜邦分析 | 净资产收益率 = 净利润率 × 资产周转率 × 权益乘数 | 盈利能力分解、财务健康状况诊断 |
| DCF(现金流折现) | 自由现金流折现 | 企业/项目估值 |
| 可比公司分析 | PE、PB、PS、EV/EBITDA 倍数比较 | 相对估值、同行对标 |
| EVA(经济增加值) | 税后营业利润 - 资本成本 | 价值创造能力评估 |
| 框架 | 描述 | 最佳适用场景 |
|---|---|---|
| 对标分析 | 关键绩效指标逐项比较 | 竞争对手差距分析、最佳实践识别 |
| 战略群组图 | 沿两个关键维度对竞争对手进行聚类 | 竞争格局可视化、空白市场识别 |
| 价值链分析 | 主要活动 + 支持活动的价值分解 | 成本优势来源、差异化机会识别 |
| 蓝海战略 | 价值曲线、四步动作框架(剔除-减少-增加-创造) | 差异化创新、新市场空间创造 |
| 感知图 | 沿两个消费者感知维度绘制品牌位置 | 品牌定位分析、市场空白发现 |
| 框架 | 描述 | 最佳适用场景 |
|---|---|---|
| 行业价值链 | 上游 → 中游 → 下游分解 | 行业结构理解、利润分配分析 |
| 高德纳技术成熟度曲线 | 技术萌芽期 → 期望膨胀期 → 泡沫破裂低谷期 → 稳步爬升复苏期 → 生产成熟期 | 新兴技术成熟度评估 |
| GE-麦肯锡矩阵 | 行业吸引力 × 竞争实力 | 业务组合优先级排序、投资决策 |
## 框架选择
| 章节 | 所选框架 | 应用方式 |
|---------|----------------------|-------------|
| 市场规模与增长趋势 | TAM-SAM-SOM + 产品生命周期 | TAM-SAM-SOM 用于量化市场空间,PLC 用于确定市场阶段 |
| 竞争格局评估 | 波特五力模型 + 战略群组图 | 五力模型用于评估行业竞争强度,群组图用于可视化竞争定位 |
| 消费者画像 | RFM + 消费者决策旅程 | RFM 用于细分客户价值,决策旅程用于识别关键转化节点 |
| 品牌战略建议 | SWOT + 蓝海战略 | SWOT 用于总结整体格局,蓝海战略用于指导差异化方向 |
生成一个层级化的章节结构。每个章节必须包含:
## 分析框架
### 章节 1: [标题]
- **分析目标**: [本章旨在...]
- **分析逻辑**: [使用的框架或推理链]
- **核心假设**: [待验证的假设]
- **数据需求**: (见步骤 1.4)
- **可视化计划**: (见步骤 1.5)
### 章节 2: [标题]
...
对于每个章节,明确指定需要收集哪些数据。这是连接下游数据收集技能的桥梁。
每个数据需求条目必须包含:
| 字段 | 描述 |
|---|---|
| 数据指标 | 所需的具体指标或数据点(例如,“2020-2025年中国护肤市场规模(单位:十亿人民币)”) |
| 数据类型 | 定量、定性或混合 |
| 建议来源 | 建议的来源类别:行业报告、财务报表、政府统计数据、社交媒体、电商平台、调查数据、新闻 |
| 搜索关键词 | 为数据收集代理建议的搜索查询 |
| 优先级 | P0(必需)/ P1(重要)/ P2(补充) |
| 时间范围 | 数据应涵盖的时间段 |
#### 数据需求
| # | 数据指标 | 数据类型 | 建议来源 | 搜索关键词 | 优先级 | 时间范围 |
|---|-------------|-----------|-------------------|-----------------|----------|------------|
| 1 | 市场规模(十亿人民币) | 定量 | 行业报告、政府统计数据 | "中国护肤市场规模 2024" | P0 | 2020-2025 |
| 2 | 复合年增长率 | 定量 | 行业报告 | "护肤 CAGR 增长率" | P0 | 2020-2025 |
| 3 | 子品类份额 | 定量 | 电商平台、行业报告 | "护肤品类份额 面霜 精华 防晒" | P1 | 最新 |
| 4 | 政策与法规更新 | 定性 | 政府公告、新闻 | "化妆品法规 2024" | P2 | 过去1年 |
对于每个章节,指定最终报告的计划可视化和内容结构:
| 字段 | 描述 |
|---|---|
| 可视化类型 | 图表类型:折线图、柱状图、饼图、散点图、雷达图、热力图、桑基图、对比表格等 |
| 可视化标题 | 图表的描述性标题 |
| 可视化数据映射 | 哪些数据指标映射到 X/Y 轴或分段 |
| 对比表格设计 | 数据对比表的列标题和比较维度 |
| 论证结构 | 计划的“是什么 → 为什么 → 所以呢”叙述大纲 |
#### 可视化与内容计划
**图表 1**: [类型] — [标题]
- X轴: [维度], Y轴: [指标]
- 数据来源: 对应数据需求 #1, #2
**对比表格**:
| 维度 | 项目 A | 项目 B | 项目 C |
|-----------|--------|--------|--------|
**论证结构**:
1. **观察(是什么)**: [数据揭示的表面现象]
2. **归因(为什么)**: [驱动因素或根本原因]
3. **启示(所以呢)**: [战略启示或建议行动]
将所有输出组合成一个结构化的分析框架文档:
# [研究主题] 分析框架
## 研究概述
- **研究主题**: [...]
- **范围**: [地理、时间范围、行业细分]
- **分析领域**: [市场 / 金融 / 行业 / 品牌 / 消费者 / ...]
- **核心研究问题**: [1-3个关键问题]
## 框架选择
| 章节 | 所选框架 | 应用方式 |
|---------|----------------------|-------------|
| ... | ... | ... |
## 章节骨架
### 1. [章节标题]
- **分析目标**: [...]
- **分析逻辑**: [...]
- **核心假设**: [...]
#### 数据需求
| # | 数据指标 | 数据类型 | 建议来源 | 搜索关键词 | 优先级 | 时间范围 |
|---|-------------|-----------|-------------------|-----------------|----------|------------|
| ... | ... | ... | ... | ... | ... | ... |
#### 可视化与内容计划
[图表计划 + 对比表格设计 + 论证结构]
### 2. [章节标题]
...
### N. [章节标题]
...
## 数据收集任务列表
[整合所有章节的 P0/P1 数据需求,形成结构化的任务列表,供下游数据收集技能执行]
分析框架生成后,将移交给其他数据收集技能(例如,深度研究、数据分析、网络搜索代理)以:
本技能不执行数据收集。 它只生成框架(第一阶段)和最终报告(第二阶段)。
图表生成:如果有可用的可视化/图表生成技能(例如,数据分析、图像生成),图表生成可以推迟到第二阶段开始时进行——参见步骤 2.3。
接收来自上游的完整分析框架和数据包,并将其综合成最终的咨询级别报告。
| 输入 | 描述 | 必需 |
|---|---|---|
| 分析框架 | 第一阶段生成的框架文档 | 是 |
| 数据摘要 | 数据收集阶段按章节组织的收集数据 | 是 |
| 图表文件 | 生成的图表图像的本地文件路径。如果未提供,将在步骤 2.3 中使用可用的可视化技能生成 | 可选 |
| 外部搜索结果 | 用于行内引用的 URL 和摘要 | 可选 |
验证所有必需的输入是否齐全:
如果缺少任何 P0 数据,请在报告中注明并提醒用户。
根据分析框架映射最终报告结构:
在撰写报告之前,根据分析框架的可视化与内容计划生成所有计划中的图表。此步骤确保在开始叙述性写作之前,每个子章节都有其“视觉锚点”准备就绪。
可视化与内容计划 条目,构建图表生成任务列表:---|---|---|---|---|---
1 | 2.1 | 折线图 | 2020-2025年市场规模趋势 | X: 年份, Y: 市场规模(十亿人民币) | 数据需求 #1, #2
2 | 3.1 | 饼图 | 消费者年龄分布 | 分段: 年龄组, 数值: 份额 % | 数据需求 #5
... | ... | ... | ... | ... | ...
关键:仅使用数据摘要中提供的数字。不要发明或“平滑”数据以使图表看起来更好。如果数据点缺失,图表必须反映这一现实(例如,断线或缺失的柱状),或者必须调整图表类型。
data-analysis),并提供: * 图表类型和标题
* 结构化数据
* 坐标轴标签和格式偏好
* 输出文件路径约定:`charts/chapter_{N}_{chart_index}.png`
4. 收集图表文件路径:记录所有生成的图表文件路径,以便在步骤 2.4 中嵌入:
## 生成的图表
| # | 章节 | 图表标题 | 文件路径 |
|---|---------|-------------|-----------|
| 1 | 2.1 | 2020-2025年市场规模趋势 | charts/chapter_2_1.png |
| 2 | 3.1 | 消费者年龄分布 | charts/chapter_3_1.png |
5. 验证:确认所有 P0 优先级的图表都已生成。如果任何图表生成失败,请注明并在该子章节回退到使用对比表格。
原则:在开始撰写报告之前完成所有图表生成。这确保了视觉叙述的一致性,并避免生成与写作交错进行。
对于每个子章节,遵循 “视觉锚点 → 数据对比 → 综合分析” 流程:
 嵌入图表——使用步骤 2.3 中收集的文件路径来源规则:表格中的每个数字都必须来自数据摘要。禁止虚构。
叙述规则:叙述必须解释提供的数据。不要做出没有输入支持的断言。
每个子章节必须以一个强有力的分析段落(至少 200 字)结束,该段落应:
>)在输出之前,确认报告包含所有按顺序排列的部分:
摘要 → 1. 引言 → 2...N. 主体章节 → N+1. 结论 → N+2. 参考文献
另外验证:
 引用中的图表文件路径有效报告不得在结论之后停止——它必须包含参考文献作为最后一部分。
output_locale 指定的语言1,000 而非 1,000)1.、1.1)直接后跟标题>)来锚定该部分。每个洞察都必须连接 数据 → 用户心理 → 战略启示:
❌ 差:“女性占 60%。战略:针对女性。”
✅ 好:“女性占 60%,目标群体指数高达 180。**这表明**购买决策是由审美和社会认同驱动,而非纯粹的功能性。**因此**,媒体支出应转向视觉主导的平台(例如,小红书/Instagram)以最大化点击率,仅将男性受众视为次要的礼品赠送细分市场。”
[来源标题](URL)),当使用外部搜索结果时# 报告标题 开始——没有介绍性文字---)# [报告标题]
## 摘要
[包含关键要点的执行摘要]
## 1. 引言
[背景、目标、方法论]
## 2. [主体章节标题]
### 2.1 [子章节标题]

| 指标 | 品牌 A | 品牌 B |
|--------|---------|--------|
| ... | ... | ... |
[综合叙述分析:是什么 → 为什么 → 所以呢,至少 200 字]
> [可选:一句话战略真相]
### 2.2 [子章节标题]
...
## N+1. 结论
[纯粹客观的综合,无要点列表,中性语调]
[段落 1:该群体/市场的根本性质]
[段落 2:核心矛盾或行为模式]
[最后:用一两句话陈述客观真相]
## N+2. 参考文献
[1] 作者. 标题[EB/OL]. URL, 日期.
[2] ...
用户提供:研究主题“Z世代护肤市场分析”
第一阶段输出(分析框架):
# Z世代护肤市场分析框架
## 研究概述
- **研究主题**: Z世代护肤市场深度分析
- **范围**: 中国市场,2020-2025年,18-27岁消费者
- **分析领域**: 市场分析 + 消费者洞察
- **核心研究问题**:
1. Z世代护肤市场的规模和增长动力如何?
2. Z世代消费者护肤行为模式有何独特之处?
3. 品牌如何有效触达并转化Z世代消费者?
## 章节骨架
### 1. 市场规模与增长趋势
- **分析目标**: 量化Z世代护肤市场规模并识别增长驱动力
- **分析逻辑**: 总市场 → 细分 → 增长率 → 驱动力分解
- **核心假设**: Z世代正成为护肤消费增长的核心引擎
#### 数据需求
| # | 数据指标 | 数据类型 | 建议来源 | 搜索关键词 | 优先级 | 时间范围 |
|---|-------------|-----------|-------------------|-----------------|----------|------------|
| 1 | 中国护肤市场总规模 | 定量 | 行业报告 | "中国护肤市场规模 2024 2025" | P0 | 2020-2025 |
| 2 | Z世代护肤支出份额 | 定量 | 行业报告、电商平台 | "Z世代护肤支出份额 年轻人" | P0 | 最新 |
#### 可视化与内容计划
**图表 1**: 折线图 — 2020-2025年中国护肤市场规模趋势
**论证结构**:
1. 是什么:市场规模和Z世代份额的量化现状
2. 为什么:消费升级、成分党消费者、社交媒体驱动
3. 所以呢:品牌应优先建设面向年轻人的产品线
### 2. 消费者画像与行为洞察
...
## 数据收集任务列表
[整合的 P0/P1 任务]
数据收集后,用户提供:分析框架 + 包含品牌指标的数据摘要 + 图表文件路径。
第二阶段输出(最终报告)遵循此流程:
# Z世代护肤市场深度分析报告 开始 1. 引言 — 市场背景、研究范围、数据来源
2. 市场规模与增长趋势分析 — 嵌入趋势图表、对比表格、战略叙述
3. 消费者画像与行为洞察 — 人口统计、购买驱动力、“所以呢”分析
4. 品牌竞争格局评估 — 品牌定位、份额分析、竞争动态
5. 营销策略与渠道洞察 — 渠道有效性、内容策略启示
6. 结论 — 以流畅的散文形式进行客观综合(无要点列表)
7. 参考文献 — GB/T 7714-2015 格式列表
 语法嵌入---)# 标题开始——无前言output_locale = zh_CN # 可根据用户请求配置
reasoning_locale = en
每周安装数
204
代码仓库
GitHub 星标数
27.8K
首次出现
Feb 14, 2026
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安装于
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amp194
This skill produces professional, consulting-grade research reports in Markdown format, covering domains such as market analysis, consumer insights, brand strategy, financial analysis, industry research, competitive intelligence, investment research, and macroeconomic analysis. It operates across two distinct phases:
The output adheres to McKinsey/BCG consulting voice standards. The report language follows the output_locale setting (default: zh_CN for Chinese).
Strict Adherence Rule : All data presented in the report and visualized in charts MUST be derived directly from the provided Data Summary or External Search Findings.
output_locale with professional consulting toneAlways load this skill when:
Given a research subject (e.g., "Gen-Z Skincare Market Analysis", "NEV Industry Competitive Landscape", "Brand X Consumer Profiling"), produce a complete analysis framework that serves as the blueprint for downstream data collection and final report generation.
| Input | Description | Required |
|---|---|---|
| Research Subject | The topic or question to be analyzed | Yes |
| Scope / Constraints | Geographic scope, time range, industry segment, target audience, etc. | Optional |
| Specific Angles | Any particular angles or hypotheses the user wants explored | Optional |
| Domain | The analytical domain: market, finance, industry, brand, consumer, investment, etc. | Inferred |
| Domain | Typical Dimensions |
|---|---|
| Market Analysis | Market size, growth trends, market segmentation, growth drivers, competitive landscape, consumer profiling |
| Brand Analysis | Brand positioning, market share, consumer perception, marketing strategy, competitor comparison |
| Consumer Insights | Demographic profiling, purchase behavior, decision journey, pain points, scenario analysis |
| Financial Analysis | Macro environment, industry trends, company fundamentals, financial metrics, valuation, risk assessment |
| Industry Research | Value chain analysis, market size, competitive landscape, policy environment, technology trends, entry barriers |
| Investment Due Diligence | Business model, financial health, management assessment, market opportunity, risk factors, exit pathways |
| Competitive Intelligence | Competitor identification, strategic comparison, SWOT analysis, differentiated positioning, market dynamics |
Based on the identified domain and research subject, select one or more professional analysis frameworks to structure the reasoning in each chapter. The chosen frameworks guide the Analysis Logic in the chapter skeleton (Step 1.3).
| Framework | Description | Best For |
|---|---|---|
| SWOT Analysis | Strengths, Weaknesses, Opportunities, Threats | Brand assessment, competitive positioning, strategic planning |
| PEST / PESTEL Analysis | Political, Economic, Social, Technological (+ Environmental, Legal) | Macro-environment scanning, market entry assessment, policy impact analysis |
| Porter's Five Forces | Supplier bargaining power, buyer bargaining power, threat of new entrants, threat of substitutes, industry rivalry | Industry competitive landscape, entry barrier assessment, profit margin analysis |
| Porter's Diamond Model | Factor conditions, demand conditions, related industries, firm strategy & structure | National/regional competitive advantage analysis |
| VRIO Analysis | Value, Rarity, Imitability, Organization | Core competency assessment, resource advantage analysis |
| Framework | Description | Best For |
|---|---|---|
| STP Analysis | Segmentation, Targeting, Positioning | Market segmentation, target market selection, brand positioning |
| BCG Matrix (Growth-Share Matrix) | Stars, Cash Cows, Question Marks, Dogs | Product portfolio management, resource allocation decisions |
| Ansoff Matrix | Market penetration, market development, product development, diversification | Growth strategy selection |
| Product Life Cycle (PLC) | Introduction, growth, maturity, decline | Product strategy formulation, market timing decisions |
| TAM-SAM-SOM | Total / Serviceable / Obtainable Market | Market sizing, opportunity quantification |
| Technology Adoption Lifecycle | Innovators → Early Adopters → Early Majority → Late Majority → Laggards | Emerging technology/category penetration analysis |
| Framework | Description | Best For |
|---|---|---|
| Consumer Decision Journey | Awareness → Consideration → Evaluation → Purchase → Loyalty | Consumer behavior path mapping, touchpoint optimization |
| AARRR Funnel (Pirate Metrics) | Acquisition, Activation, Retention, Revenue, Referral | User growth analysis, conversion rate optimization |
| RFM Model | Recency, Frequency, Monetary | Customer value segmentation, precision marketing |
| Maslow's Hierarchy of Needs | Physiological → Safety → Social → Esteem → Self-actualization | Consumer psychology analysis, product value proposition |
| Jobs-to-be-Done (JTBD) | The "job" a user needs to accomplish in a specific context | Demand insight, product innovation direction |
| Framework | Description | Best For |
|---|---|---|
| DuPont Analysis | ROE = Net Profit Margin × Asset Turnover × Equity Multiplier | Profitability decomposition, financial health diagnosis |
| DCF (Discounted Cash Flow) | Free cash flow discounting | Enterprise/project valuation |
| Comparable Company Analysis | PE, PB, PS, EV/EBITDA multiples comparison | Relative valuation, peer benchmarking |
| EVA (Economic Value Added) | After-tax operating profit - Cost of capital | Value creation capability assessment |
| Framework | Description | Best For |
|---|---|---|
| Benchmarking | Key performance indicator item-by-item comparison | Competitor gap analysis, best practice identification |
| Strategic Group Mapping | Cluster competitors along two key dimensions | Competitive landscape visualization, white-space identification |
| Value Chain Analysis | Primary activities + support activities value decomposition | Cost advantage sources, differentiation opportunity identification |
| Blue Ocean Strategy | Value curve, four-action framework (Eliminate-Reduce-Raise-Create) | Differentiated innovation, new market space creation |
| Perceptual Mapping | Plot brand positions along two consumer-perceived dimensions | Brand positioning analysis, market gap discovery |
| Framework | Description | Best For |
|---|---|---|
| Industry Value Chain | Upstream → Midstream → Downstream decomposition | Industry structure understanding, profit distribution analysis |
| Gartner Hype Cycle | Technology Trigger → Peak of Inflated Expectations → Trough of Disillusionment → Slope of Enlightenment → Plateau of Productivity | Emerging technology maturity assessment |
| GE-McKinsey Matrix | Industry Attractiveness × Competitive Strength | Business portfolio prioritization, investment decisions |
## Framework Selection
| Chapter | Selected Framework(s) | Application |
|---------|----------------------|-------------|
| Market Size & Growth Trends | TAM-SAM-SOM + Product Life Cycle | TAM-SAM-SOM to quantify market space, PLC to determine market stage |
| Competitive Landscape Assessment | Porter's Five Forces + Strategic Group Mapping | Five Forces to assess industry competition intensity, Group Mapping to visualize competitive positioning |
| Consumer Profiling | RFM + Consumer Decision Journey | RFM to segment customer value, Decision Journey to identify key conversion nodes |
| Brand Strategy Recommendations | SWOT + Blue Ocean Strategy | SWOT to summarize overall landscape, Blue Ocean to guide differentiation direction |
Produce a hierarchical chapter structure. Each chapter must include:
## Analysis Framework
### Chapter 1: [Title]
- **Analysis Objective**: [This chapter aims to...]
- **Analysis Logic**: [Framework or reasoning chain used]
- **Core Hypothesis**: [Hypotheses to validate]
- **Data Requirements**: (see Step 1.4)
- **Visualization Plan**: (see Step 1.5)
### Chapter 2: [Title]
...
For each chapter, specify exactly what data needs to be collected. This is the bridge to downstream data collection skills.
Each data requirement entry must include:
| Field | Description |
|---|---|
| Data Metric | The specific metric or data point needed (e.g., "China skincare market size 2020-2025 (in billion CNY)") |
| Data Type | Quantitative, Qualitative, or Mixed |
| Suggested Sources | Suggested source categories: Industry reports, financial statements, government statistics, social media, e-commerce platforms, survey data, news |
| Search Keywords | Suggested search queries for data collection agents |
| Priority | P0 (Required) / P1 (Important) / P2 (Supplementary) |
| Time Range | The time period the data should cover |
#### Data Requirements
| # | Data Metric | Data Type | Suggested Sources | Search Keywords | Priority | Time Range |
|---|-------------|-----------|-------------------|-----------------|----------|------------|
| 1 | Market size (billion CNY) | Quantitative | Industry reports, government statistics | "China skincare market size 2024" | P0 | 2020-2025 |
| 2 | CAGR | Quantitative | Industry reports | "skincare CAGR growth rate" | P0 | 2020-2025 |
| 3 | Sub-category share | Quantitative | E-commerce platforms, industry reports | "skincare category share cream serum sunscreen" | P1 | Latest |
| 4 | Policy & regulatory updates | Qualitative | Government announcements, news | "cosmetics regulation 2024" | P2 | Past 1 year |
For each chapter, specify the planned visualization and content structure for the final report:
| Field | Description |
|---|---|
| Visualization Type | Chart type: Line chart, bar chart, pie chart, scatter plot, radar chart, heatmap, Sankey diagram, comparison table, etc. |
| Visualization Title | Descriptive title for the chart |
| Visualization Data Mapping | Which data indicators map to X/Y axes or segments |
| Comparison Table Design | Column headers and comparison dimensions for the data contrast table |
| Argument Structure | The planned "What → Why → So What" narrative outline |
#### Visualization & Content Plan
**Chart 1**: [Type] — [Title]
- X-axis: [Dimension], Y-axis: [Metric]
- Data source: Corresponds to Data Requirement #1, #2
**Comparison Table**:
| Dimension | Item A | Item B | Item C |
|-----------|--------|--------|--------|
**Argument Structure**:
1. **Observation (What)**: [Surface phenomenon revealed by data]
2. **Attribution (Why)**: [Driving factors or underlying causes]
3. **Implication (So What)**: [Strategic implications or recommended actions]
Assemble all outputs into a single, structured Analysis Framework Document :
# [Research Subject] Analysis Framework
## Research Overview
- **Research Subject**: [...]
- **Scope**: [Geography, time range, industry segment]
- **Analysis Domain**: [Market / Finance / Industry / Brand / Consumer / ...]
- **Core Research Questions**: [1-3 key questions]
## Framework Selection
| Chapter | Selected Framework(s) | Application |
|---------|----------------------|-------------|
| ... | ... | ... |
## Chapter Skeleton
### 1. [Chapter Title]
- **Analysis Objective**: [...]
- **Analysis Logic**: [...]
- **Core Hypothesis**: [...]
#### Data Requirements
| # | Data Metric | Data Type | Suggested Sources | Search Keywords | Priority | Time Range |
|---|-------------|-----------|-------------------|-----------------|----------|------------|
| ... | ... | ... | ... | ... | ... | ... |
#### Visualization & Content Plan
[Chart plan + Comparison table design + Argument structure]
### 2. [Chapter Title]
...
### N. [Chapter Title]
...
## Data Collection Task List
[Consolidate all P0/P1 data requirements across chapters into a structured task list for downstream data collection skills to execute]
After the analysis framework is generated, it is handed off to other data collection skills (e.g., deep-research, data-analysis, web search agents) to:
This skill does NOT perform data collection. It only produces the framework (Phase 1) and the final report (Phase 2).
Chart Generation : If a visualization/charting skill is available (e.g., data-analysis, image-generation), chart generation can be deferred to the beginning of Phase 2 — see Step 2.3.
Receive the completed Analysis Framework and Data Package from upstream, and synthesize them into a final consulting-grade report.
| Input | Description | Required |
|---|---|---|
| Analysis Framework | The framework document produced in Phase 1 | Yes |
| Data Summary | Collected data organized per chapter from the data collection phase | Yes |
| Chart Files | Local file paths for generated chart images. If not provided, will be generated in Step 2.3 using available visualization skills | Optional |
| External Search Findings | URLs and summaries for inline citations | Optional |
Verify that all required inputs are present:
If any P0 data is missing, note it in the report and flag for the user.
Map the final report structure from the Analysis Framework:
Before writing the report, generate all planned charts from the Analysis Framework's Visualization & Content Plan. This step ensures every sub-chapter has its "Visual Anchor" ready before narrative writing begins.
Visualization & Content Plan entries from the Analysis Framework to build a chart generation task list:---|---|---|---|---|---
1 | 2.1 | Line chart | Market Size Trend 2020-2025 | X: Year, Y: Market Size (billion CNY) | Data Requirement #1, #2
2 | 3.1 | Pie chart | Consumer Age Distribution | Segments: Age groups, Values: Share % | Data Requirement #5
... | ... | ... | ... | ... | ...
CRITICAL : Use ONLY the numbers provided in the Data Summary. Do NOT invent or "smooth" data to make charts look better. If data points are missing, the chart must reflect that reality (e.g., broken line or missing bar), or the chart type must be adjusted.
Delegate to Visualization Skill : Invoke the available visualization/charting skill (e.g., data-analysis) for each chart task with:
charts/chapter_{N}_{chart_index}.pngCollect Chart File Paths : Record all generated chart file paths for embedding in Step 2.4:
## Generated Charts
| # | Chapter | Chart Title | File Path |
|---|---------|-------------|-----------|
| 1 | 2.1 | Market Size Trend 2020-2025 | charts/chapter_2_1.png |
| 2 | 3.1 | Consumer Age Distribution | charts/chapter_3_1.png |
5. Validate : Confirm all P0-priority charts have been generated. If any chart generation fails, note it and fall back to comparison tables for that sub-chapter.
Principle : Complete ALL chart generation before starting report writing. This ensures a consistent visual narrative and avoids interleaving generation with writing.
For each sub-chapter, follow the "Visual Anchor → Data Contrast → Integrated Analysis" flow:
 — use the file paths collected in Step 2.3Source Rule : Every number in the table must come from the Data Summary. No hallucinations.
Narrative Rule : Narrative must explain the provided data. Do not make claims unsupported by the inputs.
Each sub-chapter must end with a robust analytical paragraph (min. 200 words) that:
>)Before outputting, confirm the report contains all sections in order :
Abstract → 1. Introduction → 2...N. Body Chapters → N+1. Conclusion → N+2. References
Additionally verify:
 references are validThe report MUST NOT stop after the Conclusion — it MUST include References as the final section.
output_locale1,000 not 1,000)1., 1.1) directly followed by the title>) to anchor the section.Every insight must connect Data → User Psychology → Strategy Implication :
❌ Bad: "Females are 60%. Strategy: Target females."
✅ Good: "Females constitute 60% with a high TGI of 180. **This suggests**
the purchase decision is driven by aesthetic and social validation
rather than pure utility. **Consequently**, media spend should pivot
towards visual-heavy platforms (e.g., RED/Instagram) to maximize CTR,
treating male audiences only as a secondary gift-giving segment."
[Source Title](URL)) when using External Search Findings# Report Title — no introductory text---)# [Report Title]
## Abstract
[Executive summary with key takeaways]
## 1. Introduction
[Background, objectives, methodology]
## 2. [Body Chapter Title]
### 2.1 [Sub-chapter Title]

| Metric | Brand A | Brand B |
|--------|---------|--------|
| ... | ... | ... |
[Integrated narrative analysis: What → Why → So What, min. 200 words]
> [Optional: One-liner strategic truth]
### 2.2 [Sub-chapter Title]
...
## N+1. Conclusion
[Pure objective synthesis, NO bullet points, neutral tone]
[Para 1: The fundamental nature of the group/market]
[Para 2: Core tension or behavior pattern]
[Final: One or two sentences stating the objective truth]
## N+2. References
[1] Author. Title[EB/OL]. URL, Date.
[2] ...
User provides: Research subject "Gen-Z Skincare Market Analysis"
Phase 1 output (Analysis Framework):
# Gen-Z Skincare Market Analysis Framework
## Research Overview
- **Research Subject**: Gen-Z Skincare Market Deep Analysis
- **Scope**: China market, 2020-2025, consumers aged 18-27
- **Analysis Domain**: Market Analysis + Consumer Insights
- **Core Research Questions**:
1. What is the size and growth momentum of the Gen-Z skincare market?
2. What is unique about Gen-Z consumer skincare behavior patterns?
3. How can brands effectively reach and convert Gen-Z consumers?
## Chapter Skeleton
### 1. Market Size & Growth Trends
- **Analysis Objective**: Quantify Gen-Z skincare market size and identify growth drivers
- **Analysis Logic**: Total market → Segmentation → Growth rate → Driver decomposition
- **Core Hypothesis**: Gen-Z is becoming the core engine of skincare consumption growth
#### Data Requirements
| # | Data Metric | Data Type | Suggested Sources | Search Keywords | Priority | Time Range |
|---|-------------|-----------|-------------------|-----------------|----------|------------|
| 1 | China skincare market total size | Quantitative | Industry reports | "China skincare market size 2024 2025" | P0 | 2020-2025 |
| 2 | Gen-Z skincare spending share | Quantitative | Industry reports, e-commerce platforms | "Gen-Z skincare spending share youth" | P0 | Latest |
#### Visualization & Content Plan
**Chart 1**: Line chart — China Skincare Market Size Trend 2020-2025
**Argument Structure**:
1. What: Quantified status of market size and Gen-Z share
2. Why: Consumption upgrade, ingredient-conscious consumers, social media driven
3. So What: Brands should prioritize building youth-oriented product lines
### 2. Consumer Profiling & Behavioral Insights
...
## Data Collection Task List
[Consolidated P0/P1 tasks]
After data collection, user provides: Analysis Framework + Data Summary with brand metrics + chart file paths.
Phase 2 output (Final Report) follows this flow:
# Gen-Z Skincare Market Deep Analysis Report 1. Introduction — Market context, research scope, data sources
2. Market Size & Growth Trend Analysis — Embed trend charts, comparison tables, strategic narrative
3. Consumer Profiling & Behavioral Insights — Demographics, purchase drivers, "So What" analysis
4. Brand Competitive Landscape Assessment — Brand positioning, share analysis, competitive dynamics
5. Marketing Strategy & Channel Insights — Channel effectiveness, content strategy implications
6. Conclusion — Objective synthesis in flowing prose (no bullets)
 syntax---) in the document# title — no preambleoutput_locale = zh_CN # configurable per user request
reasoning_locale = en
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Repository
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First Seen
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Installed on
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7. References — GB/T 7714-2015 formatted list