Financial Analyzing
huangjia2019/claude-code-engineering
Analyze financial data, calculate financial ratios, and generate analysis reports.
Generate stage-2 publishable deep financial analysis markdown from a daily-finance brief plus current web verification, using liquidity, interest rates, risk appetite, capital flows, policy, and…
Install Finance Core Analysis
$ npx skills add digoal/blog --skill finance-core-analysis -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install digoal/blog finance-core-analysis --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/digoal/blog.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/finance-core-analysis .claude/skills/finance-core-analysis && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "finance-core-analysis" agent skill from https://github.com/digoal/blog/tree/master/skills/finance-core-analysis into .claude/skills/finance-core-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "finance-core-analysis", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/digoal/blog/tree/master/skills/finance-core-analysisType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add digoal/blog --skill finance-core-analysis -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install digoal/blog finance-core-analysis --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/digoal/blog.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/finance-core-analysis .agents/skills/finance-core-analysis && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "finance-core-analysis" agent skill from https://github.com/digoal/blog/tree/master/skills/finance-core-analysis into .agents/skills/finance-core-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "finance-core-analysis", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add digoal/blog --skill finance-core-analysis -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install digoal/blog finance-core-analysis --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/digoal/blog.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/finance-core-analysis .cursor/skills/finance-core-analysis && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "finance-core-analysis" agent skill from https://github.com/digoal/blog/tree/master/skills/finance-core-analysis into .cursor/skills/finance-core-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "finance-core-analysis", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/digoal/blog.git --path skills/finance-core-analysis--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add digoal/blog --skill finance-core-analysis -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install digoal/blog finance-core-analysis --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/digoal/blog.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/finance-core-analysis .gemini/skills/finance-core-analysis && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "finance-core-analysis" agent skill from https://github.com/digoal/blog/tree/master/skills/finance-core-analysis into .gemini/skills/finance-core-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "finance-core-analysis", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install digoal/blog finance-core-analysisInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add digoal/blog --skill finance-core-analysis -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/digoal/blog.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/finance-core-analysis .github/skills/finance-core-analysis && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "finance-core-analysis" agent skill from https://github.com/digoal/blog/tree/master/skills/finance-core-analysis into .github/skills/finance-core-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "finance-core-analysis", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add digoal/blog --skill finance-core-analysis -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install digoal/blog finance-core-analysis --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/digoal/blog.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/finance-core-analysis .opencode/skills/finance-core-analysis && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "finance-core-analysis" agent skill from https://github.com/digoal/blog/tree/master/skills/finance-core-analysis into .opencode/skills/finance-core-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "finance-core-analysis", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
finance-core-analysis- GitHub stars
- 8.6k
- Token cost
- ~1.7k tokens
- SKILL.md length
- 809 words
- Files
- 3
- Skills in repo
- 98
- Repo updated
- First seen
- Licence
- GPL-2.0
At a glance
Generate stage-2 publishable deep financial analysis markdown from a daily-finance brief plus current web verification, using liquidity, interest rates, risk appetite, capital flows, policy, and…
- Works in 10 steps: Title → Executive judgment → Fact base → …
- User wants a deeper 公众号-style markdown analysis based on daily-finance output
- SKILL.md covers Overview, Input, External data step and Core model, plus 6 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Finance Core Analysis is an agent skill from digoal/blog. Generate stage-2 publishable deep financial analysis markdown from a daily-finance brief plus current web verification, using liquidity, interest rates, risk appetite, capital flows, policy, and balance-sheet constraints. Use when user wants a deeper 公众号-style markdown analysis based on daily-finance output, core macro/market mechanism analysis, or the second step of the daily finance pipeline before finance-explosive-article.
Its SKILL.md is about 1.7k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files (for example `test-prompts.json`).
It sits in Business, Finance & HR, covering Financial analysis. The repository describes itself as: AI,Opensource,Database,Business,Finance,Minds. git clone --depth 1 https://github.com/digoal/blog. The licence is GPL-2.0.
When your agent uses it
- User wants a deeper 公众号-style markdown analysis based on daily-finance output
- Core macro/market mechanism analysis
- The second step of the daily finance pipeline before finance-explosive-article
Example prompts
- “/finance-core-analysis”
Workflow steps
10 steps, taken from the step headings in SKILL.md.
What it can do on your machine
Read from SKILL.md and the folder at commit 69fb793. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md.
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Finance Core Analysis loads about 1.7k tokens when it runs. Until then it costs about 113 tokens; SKILL.md has 809 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from digoal/blog at commit 69fb793, republished under its GPL-2.0 licence (© digoal). 809 words, ~1,663 tokens.
Download SKILL.mdSave it as
.claude/skills/finance-core-analysis/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.- name
- finance-core-analysis
- description
- Generate stage-2 publishable deep financial analysis markdown from a daily-finance brief plus current web verification, using liquidity, interest rates, risk appetite, capital flows, policy, and balance-sheet constraints. Use when user wants a deeper 公众号-style markdown analysis based on daily-finance output, core macro/market mechanism analysis, or the second step of the daily finance pipeline before finance-explosive-article.
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
Show full SKILL.md (300 more words)Show less
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
© digoal, GPL-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 2 other files in skills/finance-core-analysis of digoal/blog.
- SKILL.md
- SKILL.md.bak.20260525-091704
- test-prompts.json
Open the folder on GitHubat commit 69fb793
Compare with similar skills
Finance Core Analysis next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Finance Core Analysis this skilldigoal/blog | 8.6k | — | ~1.7k | Automated safety check: Pass | GPL-2.0 | |
| Financial Analyzinghuangjia2019/claude-code-engineering | 1.1k | 1 repos | ~474 | Automated safety check: Pass | None | |
| Longbridge Earningshelsome/folio | 269 | 1 repos | ~2.5k | Automated safety check: Pass | None | |
| Fundamentalsstaskh/trading_skills | 374 | 1 repos | ~836 | Automated safety check: Pass | MIT | |
| Earnings AnalysisWind-Alice/AliceMarket | 130 | 3 repos | ~2.2k | Automated safety check: Pass | None | |
| Buy Side Equity Research Memohaskaomni/serenity-skill | 632 | — | ~3.8k | Automated safety check: Pass | MIT |
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Questions about Finance Core Analysis
What does Finance Core Analysis do?
Generate stage-2 publishable deep financial analysis markdown from a daily-finance brief plus current web verification, using liquidity, interest rates, risk appetite, capital flows, policy, and…. Finance Core Analysis is an agent skill from digoal/blog. Generate stage-2 publishable deep financial analysis markdown from a daily-finance brief plus current web verification, using liquidity, interest rates, risk appetite, capital flows, policy, and balance-sheet constraints.
When should I use Finance Core Analysis?
Finance Core Analysis fits situations like: user wants a deeper 公众号-style markdown analysis based on daily-finance output; core macro/market mechanism analysis; the second step of the daily finance pipeline before finance-explosive-article.
How do I install Finance Core Analysis in Claude Code?
Run `npx skills add digoal/blog --skill finance-core-analysis -a claude-code`. Or copy the skill folder (skills/finance-core-analysis in digoal/blog) into .claude/skills/finance-core-analysis in your project. Claude Code loads it when a task matches its description.
How do I install Finance Core Analysis in Codex?
Run `npx skills add digoal/blog --skill finance-core-analysis -a codex`. Or copy the skill folder (skills/finance-core-analysis in digoal/blog) into .agents/skills/finance-core-analysis in your project. Codex loads it when a task matches its description.
Can I use Finance Core Analysis in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add digoal/blog --skill finance-core-analysis -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/finance-core-analysis, .gemini/skills/finance-core-analysis, .github/skills/finance-core-analysis and .opencode/skills/finance-core-analysis in your project.
What does Finance Core Analysis need to run?
SKILL.md names no scripts, command-line tools or credentials: Finance Core Analysis is instructions for the agent only.
Does Finance Core Analysis access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Finance Core Analysis safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Finance Core Analysis use?
Finance Core Analysis is published under the GPL-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Finance Core Analysis use?
About 1.7k tokens (SKILL.md is roughly 6.7k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Finance Core Analysis?
Skills that share tags, products or a category with Finance Core Analysis: Financial Analyzing (huangjia2019/claude-code-engineering, 1.1k stars), Longbridge Earnings (helsome/folio, 269 stars), Fundamentals (staskh/trading_skills, 374 stars) and Earnings Analysis (Wind-Alice/AliceMarket, 130 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Finance Core Analysis?
digoal (a GitHub user) maintains it in digoal/blog, which has 8,587 GitHub stars. The repository holds 98 skills in this directory. The repository was last updated on September 28, 2026.
Source: digoal/blog on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.