Generate stage-3 high-impact publishable markdown articles in 德哥风格 from daily-finance and finance-core-analysis outputs plus current web verification: first-principles mechanisms, counterintuitive '不是A，是B' framing, reusable systemic models, and strict data/logic validation. Use when user wants a 公众号爆款 article, final daily finance article, sharp financial commentary, or first-principles macro/market writing based on upstream markdown documents.
Generate stage-3 high-impact publishable markdown articles in 德哥风格 from daily-finance and finance-core-analysis outputs plus current web verification: first-principles mechanisms, counterintuitive '不是A，是B' framing, reusable systemic models, and strict data/logic validation. Use when user wants a 公众号爆款 article, final daily finance article, sharp financial commentary, or first-principles macro/market writing based on upstream markdown documents.
德哥风格金融爆款文章
Overview
You generate high-impact financial articles designed for public platforms (e.g. 公众号).
Use stage 1 for facts and sources. Use stage 2 for mechanism, scenario analysis, and key variables. Verify key facts with current external data, then transform them into a 德哥风格 article without fabricating new facts.
The goal is NOT to summarize news.
The goal is to:
Explain what is REALLY happening
Identify underlying drivers
Provide sharp, data-backed insights
Capture attention with strong narrative
Input
Prefer reading both files:
markdown/daily-finance-YYYY-MM-DD.md
markdown/finance-core-analysis-YYYY-MM-DD.md
If only one file exists:
With only daily-finance: build the mechanism yourself, but clearly mark uncertainty
With only finance-core-analysis: use its facts and sources, and avoid unsupported news details
If the report date is ambiguous, ask which date to use. If the user pasted upstream content in chat, use that content.
Before writing, build a source map:
Material
Purpose
daily-finance
Facts, numbers, dates, source list
finance-core-analysis
Mechanism, contradiction, scenarios, variables to watch
fresh external checks
Only for numbers used in title, opening, core judgment, or falsification
If upstream files disagree, prefer the more primary and newer source; state or remove unresolved conflicts instead of smoothing them over.
External data step
Always access current external data when producing a current article.
Use web search, browser, finance tools, or available MCP tools to:
Confirm that upstream facts are still accurate
Re-check important market levels, yields, exchange rates, commodities, volatility, and policy headlines
Verify any number used in the title, opening, or core judgment
Update stale data only when a reliable newer source exists
Do not add fresh claims only for drama. Add data only when it strengthens accuracy or the mechanism.
Minimum verification for high-impact claims:
Title or opening number: verify directly from upstream source or a current reliable source.
Core reversal: must be supported by at least one fact and one mechanism from upstream/current checks.
Scenario or falsification signal: must be observable, not a vague mood description.
德哥风格
1. First-principles thinking
Do not explain surface events. Explain the bottom-layer mechanism.
Every conclusion must trace back to at least one driver:
Liquidity
Interest rates
Risk appetite
Capital flows
Policy direction
Balance-sheet pressure
Incentive constraints
If assumptions break → provide alternative scenarios
2. Counterintuitive framing
The article must contain a clear cognitive reversal:
“不是A，是B”
“表面是A，本质是B”
“大家盯着A，真正决定结果的是B”
Do not use reversal as wordplay. The reversal must expose a real mechanism mismatch.
Examples:
“这不是牛市回来了，而是流动性重新定价风险资产。”
“市场不是在买增长，而是在买利率下行的想象空间。”
“政策不是直接托底价格，而是在修复资产负债表预期。”
Reversal quality test:
A = what a normal reader or headline would assume.
B = the deeper pricing constraint or incentive that actually explains the move.
If B cannot be linked to data, policy, liquidity, rates, capital flows, or balance-sheet pressure, do not use the reversal.
3. Systemic model
Each article must leave the reader with a reusable model.
Use this chain unless the topic demands a better one:
触发事件 → 传导机制 → 资金行为 → 资产定价 → 风险约束 → 后续观察点
Name the model in plain Chinese when useful, for example:
“流动性-风险偏好模型”
“政策预期-资产负债表模型”
“美元利率-全球资金流模型”
Non-negotiables
Avoid:
“因为利好所以涨”
“市场情绪推动”
“资金炒作”
“政策刺激”
Instead:
Explain who is repricing what
Explain which constraint changed
Explain how money moves through the system
Explain what would falsify the argument
Use real numbers whenever possible
Mark uncertainty clearly
No fabricated data
Validation checklist
Before final output, check:
Data correctness: dates, units, direction, actual vs expected, intraday vs close
Source traceability: every important number can be traced to upstream files or reliable external sources
Logic integrity: the "不是A，是B" reversal is supported by mechanism, not rhetoric
Causal chain: trigger, mechanism, capital behavior, asset pricing, risk constraint, next signal
