finance-core-analysis
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Core Financial Analysis
Overview
Generate a deep mechanism analysis from the stage-1 daily finance brief.
This is stage 2 of the daily finance pipeline:
daily-finance → finance-core-analysis → finance-explosive-article
Use the stage-1 file as the factual base, verify/update key data from current external sources, then produce a standalone publishable markdown analysis that can also feed the final 德哥风格爆款文章.
Input
Prefer reading:
markdown/daily-finance-YYYY-MM-DD.md
If the file is not provided:
- Use the newest matching file by filename/date only when the user clearly asks for the latest report; state this assumption in the output metadata
- Ask which report date or file to use when multiple plausible dates exist and "latest" is not implied
- If the user gives raw daily-finance content in chat, use that content
- Do not invent missing facts
Extract a reusable fact table before analysis:
| Field | What to capture |
|---|---|
| Report date | Date used for file naming and source alignment |
| Key facts | 3-5 source-backed facts from daily-finance |
| Numbers | Actual, expected/previous, unit, direction, close/intraday status |
| Sources | Inherited source names/links and any reliability limits |
| Open questions | Facts that require current re-check or must be excluded |
External data step
Always access current external data when producing a current analysis.
Use web search, browser, finance tools, or available MCP tools to:
- Re-check major market prices, yields, exchange rates, commodities, and volatility indicators
- Verify policy statements, macro data, earnings data, and geopolitical facts
- Update stale numbers from the stage-1 brief when newer reliable data exists
- Add only source-verifiable data
Use source hierarchy:
- Primary: official releases, central banks, exchanges, regulators, company filings, Reuters, Bloomberg, FT, WSJ
- Chinese reliable sources: 财新, 第一财经, 财经, 21世纪经济报道, 经济观察报
- Secondary sources require backtracking to original data
Current-data pull should be narrow and decision-relevant. Prioritize:
- Rates: US 10Y/2Y, China 10Y, major central-bank signal
- Liquidity: DXY, CNH, SHIBOR/DR007 or equivalent local liquidity indicator when relevant
- Risk appetite: major equity index, VIX or local volatility/breadth proxy
- Commodities: oil, gold, copper only when linked to the day's thesis
If a value cannot be verified, remove it or mark it as 【待】; never build the core judgment on 【待】.
Core model
Explain market behavior through these variables:
- Liquidity
- Interest rates
- Risk appetite
- Capital flows
- Policy direction
- Balance-sheet pressure
- Incentive constraints
Use first-principles reasoning:
事件 → 约束变化 → 资金行为 → 定价结果 → 风险信号
Analysis rules
- Separate confirmed facts from interpretation
- Reuse source-backed numbers from daily-finance
- Add new data only when it is necessary and source-verifiable
- Mark uncertainty clearly
- Write as a serious publishable 公众号 deep-analysis article; save the strongest viral packaging for finance-explosive-article
- Do not give explicit buy/sell recommendations
- For every major conclusion, name the constraint that changed and the observable signal that would prove it wrong
- Avoid analyzing every lens mechanically; select the 3-5 lenses that actually explain the fact base
Validation checklist
Before final output, check:
- Data correctness: dates, units, directions, actual vs expected, intraday vs close
- Source consistency: important claims have reliable sources
- Logic integrity: each conclusion follows from a mechanism, not from mood words
- Causal chain: event, constraint, capital behavior, pricing result, risk signal
- Counter-case: include what would make the judgment wrong
- Publication readiness: title, subheadings, short paragraphs, clear conclusion
Required structure
1. Title
- Use a clear 公众号-style title
- Prefer tension and mechanism over clickbait
2. Executive judgment
- State the single most important market judgment
- Explain what changed today
- Include one "what would change my mind" sentence
3. Fact base
- Summarize the 3-5 key facts inherited from daily-finance
- Preserve important numbers and source labels
- Add newly verified external data when necessary
- Use a compact table with columns:
标签,事实,数值,来源,状态
4. Mechanism analysis
Analyze through 3-5 lenses as relevant:
- Liquidity
- Interest rates
- Risk appetite
- Capital flows
- Policy
- Balance sheets
For each lens, explain:
- What changed
- Why it matters
- How it transmits into asset prices
- What data would confirm or falsify this lens
5. Core contradiction
Identify the main tension, for example:
- Growth vs inflation
- Policy easing vs currency pressure
- Risk appetite vs earnings pressure
- Liquidity repair vs balance-sheet contraction
6. Scenario deduction
Provide:
- Base case
- Alternative case
- Falsification signal
Each scenario must specify:
- Trigger condition
- Asset-pricing implication
- Observable confirmation signal
7. Key variables to watch
List 3-6 observable indicators for the next update.
8. Non-advisory implication
Explain directional exposure and risk, not ticker calls.
9. Sources
List inherited sources and any new verified sources.
10. Disclaimer
本文仅供参考,不构成投资建议。
File output
If environment allows:
Save to:
markdown/finance-core-analysis-YYYY-MM-DD.md
Rules:
- Use the same report date as the input
daily-financefile - Create directory if missing
- Use UTF-8 encoding
- Output a complete publishable markdown article, not notes
- If write fails → fallback to chat output
Writing style
- Use 公众号-readable structure: strong title, short paragraphs, numbered sections
- Keep the tone sharp but rational
- Explain mechanisms in plain Chinese
- Use contrast where helpful: "不是A,而是B"
- Avoid empty emotional phrases and unexplained jargon
Goal
Produce a reusable deep-analysis document that answers:
- What changed
- Why it changed
- What mechanism connects facts to asset pricing
- What would prove the analysis wrong
- Fluxly category
- Writing
- Author-declared agents
- No explicit declaration found; this is not inferred or tested compatibility
- Static check
- 88 / 100 · heuristic scan, not runtime safety proof
- Author / version / license
- @digoal · no license declared
- Fluxly token estimate
- Lean
- Fluxly setup estimate
- Guided setup
- External API key
- No requirement detected
- Detected OS requirements
- Unspecified
- Runtime requirements
- Unspecified
- Detected file/system behavior
-
- Read-only
- Write / modify
- Shell exec
- Detected network behavior
- Local-only
- Install commands
- None (reference only)
Profile is derived at build time from SKILL.md and install vectors. Subject to drift from author intent.
Heads up: 未限定 allowed-tools,默认拥有全部工具权限。
# File output
- Use the same report date as the input `daily-finance` file
- Create directory if missing
- Use UTF-8 encoding
- Output a complete publishable markdown article, not notes
- If write fails → fallback to chat output Generate a deep mechanism analysis from the stage-1 daily finance brief. This is stage 2 of the daily finance pipeline: daily-finance → finance-core-analysis → finance-explosive-article
Prefer reading: markdown/daily-finance-YYYY-MM-DD.md If the file is not provided:
Always access current external data when producing a current analysis. Use web search, browser, finance tools, or available MCP tools to: Re-check major market prices, yields, exchange rates, commodities, and volatility indicators
Explain market behavior through these variables: Liquidity Interest rates
Separate confirmed facts from interpretation Reuse source-backed numbers from daily-finance Add new data only when it is necessary and source-verifiable
Before final output, check: Data correctness: dates, units, directions, actual vs expected, intraday vs close Source consistency: important claims have reliable sources
# Core Financial Analysis
## Overview
Generate a **deep mechanism analysis** from the stage-1 daily finance brief.
This is stage 2 of the daily finance pipeline:
`daily-finance → finance-core-analysis → finance-explosive-article`
Use the stage-1 file as the factual base, verify/update key data from current external sources, then produce a standalone publishable markdown analysis that can also feed the final 德哥风格爆款文章.
---
## Input
Prefer reading:
`markdown/daily-finance-YYYY-MM-DD.md`
If the file is not provided:
- Use the newest matching file by filename/date only when the user clearly asks for the latest report; state this assumption in the output metadata
- Ask which report date or file to use when multiple plausible dates exist and "latest" is not implied
- If the user gives raw daily-finance content in chat, use that content
- Do not invent missing facts
Extract a reusable fact table before analysis:
| Field | What to capture |
|---|---|
| Report date | Date used for file naming and source alignment |
| Key facts | 3-5 source-backed facts from daily-finance |
| Numbers | Actual, expected/previous, unit, direction, close/intraday status |
| Sources | Inherited source names/links and any reliability limits |
| Open questions | Facts that require current re-check or must be excluded |
---
## External data step
Always access current external data when producing a current analysis.
Use web search, browser, finance tools, or available MCP tools to:
- Re-check major market prices, yields, exchange rates, commodities, and volatility indicators
- Verify policy statements, macro data, earnings data, and geopolitical facts
- Update stale numbers from the stage-1 brief when newer reliable data exists
- Add only source-verifiable data
Use source hierarchy:
… Author text anchors workflow facts; Fluxly only indexes current sections, terms, files, and commands.
sections -> Overview → Input → External data step → Core model → Analysis rules → Validation checklist
terms -> deep mechanism analysis · Generate a deep mechanism analysis from the stage-1 daily finance brief. · Always access current external data when producing a current analysis. · Current-data pull should be narrow and decision-relevant. · If a value cannot be verified, remove it or mark it as 【待】; never build the core judgment on 【待】. · List 3-6 observable indicators for the next update. · Explain directional exposure and risk, not ticker calls. · List inherited sources and any new verified sources.
files/cmd -> daily-finance → finance-core-analysis → finance-explosive-article · markdown/daily-finance-YYYY-MM-DD.md · 【待】 · 事件 → 约束变化 → 资金行为 → 定价结果 → 风险信号 · markdown/finance-core-analysis-YYYY-MM-DD.md · daily-finance
body sha256 -> 70c43c22f18e
Decide Fit First
Design Intent
How To Use It
Boundaries And Review