finance-core-analysis
- Repo stars 8,497
- Author updated Live
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- Domain
- Writing
- Compatible agents
-
- Claude Code
- Cursor
- Cline
- Codex
- Windsurf
- Gemini CLI
- +20
- Trust score
- 88 / 100 · community maintained
- Author / version / license
- @digoal · no license declared
- Token usage
- Lean
- Setup complexity
- Guided setup
- External API key
- Not required
- Operating systems
- Unspecified (assume cross-platform)
- Runtime requirements
- No special requirements
- Permissions
-
- Read-only
- Write / modify
- Shell exec
- Network behavior
- Local-only
- Install commands
- 26 variants
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。
---
name: finance-core-analysis
description: Use when multiple plausible dates exist and "latest" is not implied. Generate a deep mechanism a…
category: writing
runtime: no special runtime
---
# finance-core-analysis output preview
## PART A: Task fit
- Use case: Use when multiple plausible dates exist and "latest" is not implied. Generate a deep mechanism analysis from the stage-1 daily finance brief. This is stage 2 of the daily finance pipeline: runs entirely locally. Works with Claude Code, Cursor, Cline and 23 more..
- Inputs: target material, constraints, expected output, and acceptance criteria.
- Evidence boundary: follow “Overview / Input / External data step” and do not present inference as author intent.
## PART B: Execution result
- **01** The card summarizes the use case; runtime output centers on “Use when multiple plausible dates exist and "latest" is not implied. Generate a deep mechanism analysis from the stage-1 daily finance brief. This is stage 2 of the daily finance pipeline: runs entirely locally. Works with Claude Code, Cursor, Cline and 23 more.”.
- **02** When the source has headings, the agent prioritizes “Overview / Input / External data step” so the result follows the author’s structure.
- **03** Typical output includes task judgment, concrete steps, required commands or file edits, validation, and follow-up options.
- **04** Risk context follows the fingerprint: read files, write/modify files, run shell commands; mostly runs locally; usually needs no extra API key.
## Running Rules
- read files, write/modify files, run shell commands; mostly runs locally; usually needs no extra API key.
- Validate with a small sample before expanding scope.
- Return the result, validation criteria, and next iteration options. The source does not require a stable slash command. After installation, invoke the skill by name and describe the task.
Name target files or source material, expected output, forbidden changes, and whether network or shell access is allowed. Permission fingerprint: read files, write/modify files, run shell commands.
Start with a small task and check whether the result follows “Overview / Input / External data step”. Inspect diffs, logs, previews, or tests before expanding scope.
Confirm the final output includes a concrete result, evidence, and next action. If it stays generic, tighten inputs, boundaries, and acceptance criteria.
---
name: finance-core-analysis
description: Use when multiple plausible dates exist and "latest" is not implied. Generate a deep mechanism a…
category: writing
source: digoal/blog
---
# finance-core-analysis
## When to use
- Use when multiple plausible dates exist and "latest" is not implied. Generate a deep mechanism analysis from the stage…
- Use it when the task has clear inputs, repeatable steps, and validation criteria.
## What to provide
- Target material, scope, expected result, and forbidden changes.
- Whether network, commands, file writes, or external services are allowed.
## Execution rules
- Organize steps around “Overview / Input / External data step” and keep inference separate from source facts.
- read files, write/modify files, run shell commands; mostly runs locally; usually needs no extra API key.
- Validate with a small sample before expanding the task.
## Output requirements
- Return the deliverable, key evidence, validation method, and next action.
- Mark missing information as unknown; do not invent commands, platforms, or dependencies. The author source anchors workflow facts; repository files anchor sources and commands; Fluxly only adds fit, limitations, and quality judgment.
skill "finance-core-analysis" {
input -> user goal + target files + boundaries + acceptance criteria
context -> Overview / Input / External data step
rules -> SKILL.md triggers / order / output contract
runtime -> no special runtime | read files, write/modify files, run shell commands | mostly runs locally
guardrails -> usually needs no extra API key + small-sample validation + diff/log review
output -> copyable result + checklist + next iteration
} 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
Decide Fit First
Design Intent
How To Use It
Boundaries And Review