Data dependencies and execution prerequisites
It is recommended to use Wind wind-mcp-skill to obtain the underlying data. Before execution, first check whether wind-mcp-skillexists locally; if not, prompt the user to install:
# GitHub
npx skills add Wind-Information-Co-Ltd/wind-skills --skill wind-mcp-skill -g -y
# Gitee 镜像（国内）
npx skills add https://gitee.com/wind_info/wind-skills.git --skill wind-mcp-skill -g -y
Skill positioning
This skill is used to conduct a horizontal comparison of 2-5 candidate companies within the same industry or same theme, and output an actionable relative ranking and rationale for selection. The focus is not to rewrite each company, but to help users answer "if research or holdings can only prioritize a few of them, who should be chosen first, and why."
Execution process
Step 1: Confirm the comparable scope and comparison objective
First clarify whether the comparison targets are truly comparable, focusing on confirming:
- Whether the track is the same
- Whether the business models are similar
- Whether they are at a similar development stage or clearly misaligned
- Whether the user wants to compare short-term trading opportunities or medium- to long-term allocation value
If the targets are not suitable for direct comparison, first explain the boundaries of comparability, then decide whether to continue forcing a side-by-side comparison.
Step 2: Establish a unified comparison framework
Standardize the comparison dimensions around the user's actual decision. Commonly used dimensions include:
- Business quality and competitive position
- Growth speed and growth certainty
- Profitability and cash generation capability
- Valuation level and expectation requirements
- Near-term catalysts and risk exposure
All candidate companies should be unfolded under the same framework, avoiding writing only stories for one company and looking only at numbers for another.
Step 3: Complete alignment of basic data and facts
Collect key facts for each company, unify the calibers, and place them into a comparison table, paying special attention to:
- Consistent time calibers
- Consistent currencies and units
- Consistent valuation method calibers
- Explain outliers and one-off factors
The goal of this stage is to base subsequent judgments on the same coordinate system.
Step 4: Compare "business quality" rather than only comparing "data levels"
In addition to key financial indicators, also compare:
- Core products and customer structure
- Market share and competitive advantages
- The business model's resilience to volatility
- Management execution and capital allocation style
If a company's short-term data is more impressive but its business stability is clearly weaker, this should be clearly pointed out, and one must not be misled by surface-level growth rates.
Step 5: Compare "odds" and "catalyst sequence"
A true comparison often involves not only looking at who is better, but also at who is more worth buying now or prioritizing for tracking. Key judgments include:
- Which company is good but already fully priced in
- Which company is average but has a larger expectation gap
- Which company has short-term catalysts, and which company needs time to deliver
- Which company is more suitable for observation, and which company is more suitable for action
Step 6: Output ranking and decision recommendations
After completing the horizontal comparison, provide a clear ranking and explain:
- The core reasons for the higher-ranked companies
- The main shortcomings of the lower-ranked companies
- If only one can be researched, only one held, or only one traded short-term, how should each choice be made
If the conclusion depends on differences in user style, also clearly break out and explain "growth-oriented preference," "value-oriented preference," and "trading-oriented preference."
Output structure
{Industry/Theme} peer comparison ({YYYY-MM-DD})
I. Conclusion summary
- Best overall choice: {Company}
- Best expectation gap choice: {Company}
- Most suitable for continued observation: {Company}
II. Unified comparison table
| Company | Business positioning | Growth | Profitability | Valuation | Recent catalysts | Main risks |
|---|---|---|---|---|---|---|
| {Company A} | {Description} | {Description} | {Description} | {Description} | {Description} | {Description} |
| {Company B} | {Description} | {Description} | {Description} | {Description} | {Description} | {Description} |
III. Relative strength analysis
Business quality
- {Who is stronger, and in what way}
Growth quality
- {Who is stronger, and in what way}
Valuation odds
- {Who is more attractive, and for what reason}
Catalysts and timing
- {Who is more suitable right now, and for what reason}
IV. Final ranking
| Rank | Company | Conclusion |
|---|---|---|
| 1 | {Company} | {Reason} |
| 2 | {Company} | {Reason} |
| 3 | {Company} | {Reason} |
V. Decision recommendations
- If you can only study one first: {Company}, because {Reason}
- If you can only track one first: {Company}, because {Reason}
- If you can only avoid one first: {Company}, because {Reason}
Quality requirements
- Only compare truly comparable targets; when necessary, first state clearly what is not comparable.
- Use the same comparison standard throughout to avoid data and narrative each saying something different.
- The output should focus on "relative strength and ranking," not a patchwork of multiple individual stock introductions.
- Quality, valuation, and timing must be compared at the same time; do not rank using only a single indicator.
- If the conclusion clearly depends on investment style, the applicable audience should be stated clearly.