description: Use this skill when the user requests to generate, create, or write professional research reports including but not limited to market analysis, consumer insights, brand analysis, financial analysis, industry research, competitive intelligence, investment due diligence, or any consulting-grade analytical report. This skill operates in two phases — (1) generating a structured analysis framework with chapter skeleton, data query requirements, and analysis logic, and (2) after data collection by other skills, producing the final consulting-grade report with structured narratives, embedded charts, and strategic insights.
---
# Professional Research Report Skill
## Overview
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:
1.**Phase 1 — Analysis Framework Generation**: Given a research subject, produce a rigorous analysis framework including chapter skeleton, per-chapter data requirements, analysis logic, and visualization plan.
2.**Phase 2 — Report Generation**: After data has been collected by other skills, synthesize all inputs into a final polished report.
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**.
- **NO Hallucinations**: Do not invent, estimate, or simulate data. If data is missing, state "Data not available" rather than fabricating numbers.
- **Traceable Sources**: Every major claim and chart must be traceable back to the input data package.
- **Design analysis frameworks** from scratch given only a research subject and scope
- Transform raw data into structured, high-depth research reports
- Follow the **"Visual Anchor → Data Contrast → Integrated Analysis"** flow per sub-chapter
- Produce insights following the **"Data → User Psychology → Strategy Implication"** chain
- Embed pre-generated charts and construct comparison tables
- Generate inline citations formatted per **GB/T 7714-2015** standards
- Output reports in the language specified by `output_locale` with professional consulting tone
- Adapt analytical depth and structure to domain (marketing, finance, industry, etc.)
## When to Use This Skill
**Always load this skill when:**
- User asks for a market analysis, consumer insight report, financial analysis, industry research, or any consulting-grade analytical report
- User provides a research subject and needs a structured analysis framework before data collection
- User provides data summaries, analysis frameworks, or chart files to be synthesized into a report
- User needs a professional consulting-style research report
- The task involves transforming research findings into structured strategic narratives
---
# Phase 1: Analysis Framework Generation
## Purpose
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.
## Phase 1 Inputs
| 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 |
## Phase 1 Workflow
### Step 1.1: Understand the Research Subject
- Parse the research subject to identify the **core entity** (market, brand, product, industry, consumer segment, financial instrument, etc.)
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).
| **EVA (Economic Value Added)** | After-tax operating profit - Cost of capital | Value creation capability assessment |
#### Competitive & Strategic Positioning
| 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 |
#### Industry & Supply Chain Analysis
| 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 |
#### Selection Principles
1.**Domain-First**: Based on the domain identified in Step 1.1, select **2-4** most relevant frameworks from the toolkit above
2.**Complementary**: Choose complementary rather than overlapping frameworks (e.g., macro-level with PESTEL + micro-level with Porter's Five Forces)
3.**Depth over Breadth**: Better to deeply apply 2 frameworks than superficially stack 6
4.**Data-Feasible**: Selected frameworks must be supportable by downstream data collection skills — if the data required by a framework cannot be reasonably obtained, downgrade or substitute
5.**Explicit Mapping**: In the chapter skeleton, explicitly annotate which framework each chapter uses and how it is applied
#### Framework Selection Output Format
```markdown
## 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 |
[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]
```
## Phase 1 Quality Checklist
- [ ] Analysis framework covers all natural dimensions for the identified domain
- [ ] 2-4 professional analysis frameworks are selected and explicitly mapped to chapters
- [ ] Selected frameworks are complementary (not overlapping) and data-feasible
- [ ] Each chapter has clear Analysis Objective, Analysis Logic (referencing chosen framework), and Core Hypothesis
- [ ] Data requirements are specific, measurable, and include search keywords
- [ ] Every chapter has at least one visualization plan
- [ ] Data priorities (P0/P1/P2) are assigned realistically
- [ ] The framework is actionable — a data collection agent can execute on the Search Keywords directly
- [ ] Data Collection Task List is comprehensive and deduplicated
---
# Phase 1→2 Handoff: Data Collection & Chart Generation
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:
1. Execute the **Search Keywords** from each chapter's data requirements
2. Collect quantitative data, qualitative insights, and source URLs
3. Generate charts based on the **Visualization & Content Plan**
4. Return a **Data Package** containing:
- **Data Summary**: Raw numbers, metrics, and qualitative findings per chapter
- **Chart Files**: Generated chart images with local file paths
- **External Search Findings**: Source URLs and summaries for citations
> **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.
---
# Phase 2: Report Generation
## Purpose
Receive the completed **Analysis Framework** and **Data Package** from upstream, and synthesize them into a final consulting-grade report.
## Phase 2 Inputs
| 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 |
## Phase 2 Workflow
### Step 2.1: Receive and Validate Inputs
Verify that all required inputs are present:
1.**Analysis Framework** — Confirm it contains chapter skeleton, data requirements, and visualization plans
2.**Data Summary** — Confirm it contains data organized per chapter, cross-reference against P0 requirements
3.**Chart Files** — Confirm file paths are valid local paths
If any P0 data is missing, note it in the report and flag for the user.
### Step 2.2: Map Report Structure
Map the final report structure from the Analysis Framework:
1.**Abstract** — Executive summary with key takeaways
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.
#### When to Execute This Step
- **Chart Files already provided**: Skip this step — proceed directly to Step 2.4.
- **Chart Files NOT provided but a visualization skill is available**: Execute this step to generate all charts first.
- **No Chart Files and no visualization skill available**: Skip this step — use comparison tables as the primary visual anchor in Step 2.4, and note the absence of charts.
#### Chart Generation Workflow
1.**Extract Chart Tasks**: Parse all `Visualization & Content Plan` entries from the Analysis Framework to build a chart generation task list:
| # | Chapter | Chart Type | Chart Title | Data Mapping | Data Source |
2.**Prepare Chart Data**: For each chart task, extract the corresponding data points from the **Data Summary**.
> **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.
| 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.
### Step 2.4: Write the Report
For each sub-chapter, follow the **"Visual Anchor → Data Contrast → Integrated Analysis"** flow:
1.**Visual Evidence Block**: Embed charts using `` — use the file paths collected in Step 2.3
2.**Data Contrast Table**: Create a Markdown comparison table for key metrics
- **Requirement**: End each sub-chapter with a robust analytical paragraph (min. 200 words).
- **Narrative Flow**: This paragraph must look like a natural continuation of the text. It must synthesize the section's findings into a strategic judgment.
- **Content Logic**:
1. Synthesize the conflicting or reinforcing data points above.
2. Reveal the *underlying* user tension or opportunity.
3. Key Insight: **Optional**: Only if you have a concise, punchy "One-Liner Truth", place it at the very end using a **Blockquote** (`>`) to anchor the section.
### Insight Depth (The "So What" Chain)
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."
```
### References
- **Inline**: Use markdown links for sources (e.g. `[Source Title](URL)`) when using External Search Findings
- **References section**: Formatted strictly per **GB/T 7714-2015**
### Markdown Rules
- **Immediate Start**: Begin directly with `# Report Title` — no introductory text
- **No Separators**: Do NOT use horizontal rules (`---`)
## Report Structure Template
```markdown
# [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] ...
```
## Complete Example
### Phase 1 Example: Framework Generation
User provides: Research subject "Gen-Z Skincare Market Analysis"
**Phase 1 output (Analysis Framework):**
```markdown
# 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
- **ZERO HALLUCINATION POLICY**: Each statement, chart, and number in the report must be supported by data points from the input Data Summary. If data is missing, admit it.
- **Traceability**: If requested, you must be able to point to the specific line in the Data Summary or External Search Findings that supports a claim.
- The framework should adapt its analytical dimensions and depth to the specific domain (financial analysis uses different frameworks than consumer insights)
- When the research subject is ambiguous, default to the broadest reasonable scope and note assumptions
