earnings_reaction_interpreter_skill

Earnings Reaction Interpreter Skill

Data dependencies and execution prerequisites

It is recommended to use Wind wind-mcp-skill to obtain underlying data. Before execution, first check whether wind-mcp-skillalready exists 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 after earnings are released to quickly answer "why did the stock move this way, where was the real beat, what exactly is the market trading, and what should be watched next." The output focus is not to copy the earnings figures again, but to clearly break down the results, reaction, and follow-up judgment.

Execution workflow

Step 1: Confirm earnings facts and the price reaction window

First confirm the corresponding earnings period, release time, after-hours or pre-market reaction, and the current observation window. Prioritize sorting out:

• Whether the earnings and guidance have been fully disclosed
• Whether the main stock price reaction occurred after hours, pre-market, or during the next day's session
• Whether the reaction magnitude clearly exceeds historical norms
• Whether comparable companies in the same sector showed related moves

If the price reaction is still changing rapidly, make clear that the current interpretation represents only the judgment at that point in time.

Step 2: Separate "results" from "performance"

Break the earnings results into multiple layers instead of looking only at a single headline:

• Whether core results such as revenue, profit, and margins beat expectations
• Whether key operating metrics support the headline's surface-level strength
• Whether guidance was simultaneously raised, maintained, or weakened
• Whether earnings quality comes from core business improvement, structural optimization, or one-off items
• Whether the price reaction is amplifying the earnings conclusion or diverging from the earnings content

The goal of this step is to avoid the mechanical judgment that "a number beat expectations, therefore it is bullish."

Step 3: Identify the core disagreement the market is actually trading

Extract the main line the market cares about most from the earnings results; common ones include:

• Whether growth is sustainable
• Whether margins have peaked or begun to recover
• Whether a certain business line has entered an inflection point
• Whether management guidance reflects deeper problems
• Whether the story originally priced into the valuation has been reinforced or weakened

If the stock price moves opposite to the headline, focus on explaining "why the market ignored the surface-level positive" or "why it amplified the marginal change."

Step 4: Judge post-earnings durability and secondary verification points

Not all earnings reactions can continue. Further judge:

• Whether this reaction looks more like a one-time emotional release or the starting point of a trend-level re-rating
• Which details may continue to be traded the next day or the following week
• Which issues still need to wait for the earnings call, supplementary filings, or management clarification
• If the short-term market interpretation is excessive, how it may swing back later

Step 5: Form an updated research judgment

Combining the earnings results, guidance, market reaction, and follow-up verification points, clarify:

• Whether the original investment logic has been reinforced, weakened, or is basically unchanged
• Whether the priority of focus needs to be adjusted
• If tracking continues, what is most worth verifying next
• If no conclusion is reached immediately, what information is truly missing

Step 6: Integrate into a finished post-earnings review

The final output should directly serve post-earnings-night review and next-day judgment, without showing the intermediate collection process or internal reasoning. The content should prioritize explanation and judgment rather than piling up materials.

Output Structure

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{Stock Name} Post-Earnings Reaction Interpretation ({YYYY-MM-DD})

I. 30-Second Conclusion

• Result level: {clearly better than expected / broadly in line / below expectations}
• Reaction level: {price change and core reason}
• The variable actually being traded: {one sentence}
• Current judgment: {thesis strengthened / thesis unchanged / thesis weakened}

II. Breakdown of Earnings Results

Item	Market expectation	Actual result	Preliminary interpretation
Revenue	{value}	{value}	{explanation}
Profit/EPS	{value}	{value}	{explanation}
Key operating metrics	{value}	{value}	{explanation}
Guidance	{expectation}	{actual}	{explanation}

III. Why the Market Reacted This Way

• Positive drivers: {content}
• Suppressing factors: {content}
• Difference between surface and substance: {content}

IV. The Real Points of Disagreement After Earnings

• {disagreement point 1}
• {disagreement point 2}
• {disagreement point 3}

V. What Else to Watch Going Forward

• Short-term verification point: {content}
• Medium-term verification point: {content}
• Signals that could change the judgment: {content}

VI. Current Action Recommendation

• Recommendation: {continue tracking / raise priority / temper optimism / wait for additional information}
• Reason: {explanation}

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Quality Requirements

1. It must explain both the "earnings content" and the "market reaction"; it cannot cover only one half.
2. If the stock price performance is inconsistent with the headline, the reason for the mismatch should be explained first.
3. It cannot attribute all changes to a single metric; it needs to highlight the main variable that truly determines the reaction.
4. Post-earnings judgment should carry an awareness of the time window, avoiding writing after-hours sentiment as a long-term conclusion.
5. The output should help users decide "how to understand this earnings report now," rather than stopping at restating the results.