--- name: finance-explosive-article description: Generate stage-3 high-impact 德哥风格 公众号 financial articles from daily-finance and finance-core-analysis outputs plus current web verification. Use this skill whenever the user wants a 公众号爆款文章, final financial commentary, "帮我写成文章"、"整理成爆款"、"德哥风格"、"公众号推文"、"写一篇深度文章"、"把分析写成文章发布", or the third and final step of the pipeline. Even if the user only says "帮我把今天的分析整理一下发出去", use this skill. This is stage 3 of: daily-finance → finance-core-analysis → finance-explosive-article. --- # 德哥风格金融爆款文章 ## Overview Generate a **high-impact, publishable financial article** in 德哥风格 for 公众号. Pipeline position: ``` daily-finance → finance-core-analysis → finance-explosive-article ``` - **Stage 1** supplies facts and verified sources - **Stage 2** supplies mechanisms, scenarios, and key variables - **Stage 3 (this skill)** transforms them into a sharp, viral-ready article The goal is NOT to summarize news. The goal is to: - Explain what is **really** happening beneath the surface - Identify the underlying drivers - Deliver sharp, data-backed insight - Make readers say: **"原来是这样"** --- ## Step 1: Read Inputs **Preferred:** Read both upstream files: - `markdown/daily-finance-YYYY-MM-DD.md` - `markdown/finance-core-analysis-YYYY-MM-DD.md` **Fallback order:** | Situation | Action | |---|---| | Only `daily-finance` exists | Build mechanism yourself; mark uncertainty explicitly | | Only `finance-core-analysis` exists | Use its facts/sources; avoid unsupported news details | | Date ambiguous | Ask the user which date to use | | User pasted content in chat | Use that content directly | --- ## Step 2: Verify Key Data Always access current external data before writing. Use web search / browser / MCP tools to: - Confirm upstream facts are still accurate - Re-check any number used in the **title, opening, or core judgment** - Update stale data when a reliable newer source exists **Do not** add fresh claims only for dramatic effect. Every number must be source-traceable. **Source hierarchy:** - Primary: Reuters, Bloomberg, FT, WSJ; 财新, 第一财经 - Secondary (require backtracking): FT中文, WSJ中文, 新浪财经 - Forbidden: 自媒体, 公众号, 未经核实社交媒体 --- ## Step 3: Apply 德哥风格 Three mandatory elements: ### 3a. First-Principles Mechanism Never explain surface events. Explain the bottom-layer driver. Every conclusion must trace to at least one: - 流动性 Liquidity - 利率 Interest rates - 风险偏好 Risk appetite - 资本流动 Capital flows - 政策方向 Policy direction - 资产负债表压力 Balance-sheet pressure - 激励约束 Incentive constraints ### 3b. Counterintuitive Reversal(必须有) The article **must** contain a clear "不是A,是B" cognitive reversal that exposes a real mechanism mismatch — not wordplay. **Strong 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。" **Banned phrases (replace with mechanisms):** - ❌ "因为利好所以涨" - ❌ "市场情绪推动" - ❌ "资金炒作" - ❌ "政策刺激" ### 3c. Reusable Systemic Model(必须有) Every article must leave the reader with one model they can reuse. **Standard causal chain:** ``` 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: - "流动性-风险偏好模型" - "美元利率-全球资金流模型" - "政策预期-资产负债表模型" --- ## Step 4: Validate Before Writing | Check | Requirement | |---|---| | **Data** | Dates, units, directions correct? Actual vs expected labeled? Intraday vs close distinguished? | | **Sources** | Every key number traceable to upstream files or reliable external source? | | **Reversal logic** | "不是A,是B" supported by mechanism, not rhetoric? | | **Causal chain** | Trigger → mechanism → capital behavior → asset pricing → risk constraint → next signal? | | **Publication** | Title, opening, section rhythm, conclusion, sources, disclaimer all present? | | **Risk boundary** | No explicit buy/sell recommendation? | > If a powerful sentence overstates the evidence, weaken the sentence — never weaken the facts. --- ## Output Format(MANDATORY STRUCTURE) ### 1. 爆点标题 - Must create tension or contradiction - Must trigger curiosity - Prefer "不是A,是B" or "真正的X,不是Y" - ✅ "市场根本不是在涨,而是在赌一件事" - ✅ "所有人都在看政策,真正的变量却在资金价格" - ❌ Generic headlines without tension ### 2. 破题(Opening) - Start with a **fact or anomaly** - Immediately raise the core question - State the mistaken mainstream interpretation - Foreshadow the counterintuitive answer ### 3. 一句话反转(Core Judgment) One direct sentence defining the article's central reversal: > `这件事表面上是A,本质上是B。` Then explain why A is incomplete and B is the real pricing variable. ### 4. 核心逻辑(Core Analysis) 2–4 sections, each containing: - Mechanism explanation - Data or observable signals - Causal reasoning - Link back to the systemic model Typical angles: Liquidity / Policy / Global capital flows / Sector rotation ### 5. 可复用模型(System Model) Summarize the reusable model explicitly: ``` 第一层:触发变量 — ... 第二层:传导机制 — ... 第三层:资产定价 — ... 第四层:验证信号 — ... ``` ### 6. 关键判断(Key Insight) Clearly state: - What the market is actually pricing - What most people misunderstand - Which variable matters most next ### 7. 推演(Scenario Analysis) | 情景 | 触发条件 | 资产含义 | |---|---|---| | 基准情景 | ... | ... | | 备选情景 | ... | ... | | 证伪信号 | ... | ... | ### 8. 方向性参考(Non-Advisory Implication) Directional thinking only. No ticker calls, no buy/sell. ### 9. 收束(Closing) - Strong summary sentence - End with mechanism, not slogan ### 10. 数据来源 Short source list, one per line. ### 11. 免责声明 > 本文仅供参考,不构成投资建议。 --- ## File Output Save to: ``` markdown/finance-explosive-article-YYYY-MM-DD.md ``` - Use the **same report date** as upstream files - Create `markdown/` directory if missing - UTF-8 encoding - Final article only — no process notes - **Fallback:** If write fails, output full markdown in chat --- ## Writing Style - Short paragraphs, clear rhythm - Sharp and direct — no fluff, no academic tone - Use contrast: "不是A,而是B" - Declarative sentences preferred - Use "说白了", "真正的问题是", "底层逻辑是" sparingly but decisively - Do not stack metaphors - Start with tension → land on mechanism → close with model --- ## Goal Produce an article that: 1. Makes the reader say **"原来是这样"** 2. Leaves behind **one reusable model** 3. Can spread on social platforms 4. Builds authority and trust through factual precision