What does this skill do, and when should you use it?
Value Investing Agent by danielchu97 ships as a SKILL.md methodology plus a standalone MCP server (the npm package value-investing-agent). The skill file directs a model to analyze stocks following Graham and Buffett: estimate intrinsic value via DCF and the Graham Number, require at least a 25% margin of safety, and evaluate five types of economic moats. The MCP server adds ten tools for real-time quotes, financials, news, a personal watchlist, and report generation, with pluggable data providers (Yahoo Finance by default, Finnhub, Alpha Vantage). It is MIT-licensed and explicitly educational — not investment advice.
The SKILL.md defines a step-by-step analysis workflow: understand the business, evaluate the moat (brand, cost advantage, network effect, switching costs, scale), check financial health against concrete thresholds (ROE >15%, current ratio >1.5, interest coverage >5x), estimate intrinsic value with DCF and Graham formulas, compute the margin of safety, and produce a structured report with mandatory disclaimer. The MCP server exposes tools — get_stock_quote, get_financials, calculate_intrinsic_value, analyze_moat, manage_watchlist, generate_stock_report, and more — that fetch market data, run valuation math, maintain watchlists, and generate daily and deep-dive reports.
- A value investor wanting a quick read on whether a US stock (e.g. AAPL, MSFT) trades with a 25%+ margin of safety
- A multi-position investor generating daily summary reports for a watchlist instead of checking quotes manually
- A student of Graham/Buffett methods using the structured framework to practice valuation and moat analysis
- A conservative investor comparing DCF, Graham Number, and growth-formula outputs and adopting the most conservative figure
- A developer plugging in a custom data provider via the plugin architecture to build a personalized analysis pipeline
How do you install this skill?
- This is a static source review; no code or tests were executed.
- The default data provider (Yahoo Finance) is rate-limit prone; finnhub/alpha-vantage require API keys and are overseas services with unverified mainland-China reachability.
- No Chinese-language support; output language must be arranged separately.
- Output is for educational/research purposes only, not investment advice; valuations depend heavily on assumptions and must be independently verified.
- No version number or changelog at skill level; upgrade behavior may be unstable.
- Network access
- MCP Server
Node.js >= 18 (for the bundled MCP server)MCP-compatible client (e.g. Claude Desktop)
The SKILL.md methodology can be used on its own without installation. For the MCP tools, the recommended path is adding {"mcpServers":{"value-investing-agent":{"command":"npx","args":["-y","value-investing-agent"]}}} to your MCP client config (e.g. Claude Desktop). Requires Node.js >= 18. Alternatives: global install (npm install -g value-investing-agent) or building from source (git clone, then npm install && npm run build). For reliable data, register a free API key at finnhub.io and set the FINNHUB_API_KEY environment variable. The skill file lives at skills/value-investing/SKILL.md in the repository.
tmp="$(mktemp -d)"
git clone --depth 1 https://github.com/danielchu97/Value-Investing-Agent.git "$tmp"
mkdir -p ~/.claude/skills
cp -R "$tmp/skills/value-investing" ~/.claude/skills/
rm -rf "$tmp"Generated from the source repository and skill path; it copies only this skill's folder. If the author's install steps above differ, follow those first. To scope it to one project, replace ~/.claude/skills with that project's .claude/skills.
How do you use this skill?
Once installed, send your agent any of these to trigger it:
- Get me the current quote for Apple
- Calculate the intrinsic value of AAPL
- Analyze the competitive moat of Coca-Cola
- Add GOOGL to my watchlist in the Technology group
Once configured, trigger tools with natural language in your MCP client: "Get me the current quote for Apple", "Calculate the intrinsic value of AAPL", "Analyze the competitive moat of Coca-Cola", "Add GOOGL to my watchlist in the Technology group", "Generate a daily report for my watchlist", or "Create a detailed analysis report for Berkshire Hathaway". Switch data providers with "Switch to finnhub provider" or the set_provider tool. Used standalone, the SKILL.md serves as analysis guidance, asking the model to follow the prescribed report structure and data-quality standards.
What are this skill's strengths and limitations?
- Concrete, complete methodology: explicit valuation formulas, metric thresholds (ROE >15%, gross margin >40%), and report structure rather than vague advice
- Standalone MCP server that starts with a single npx command and works with any MCP-compatible client, not just Claude products
- Pluggable data sources — Yahoo Finance (no key), Finnhub, Alpha Vantage built in, plus a custom provider guide
- Solid engineering: MIT license, test and lint scripts, bilingual README
- Built-in risk discipline: conservative-estimate rule, mandatory disclaimer, and documented pitfalls like value traps
- The default Yahoo Finance provider is rate-limited and can hit 429 errors; stable use requires obtaining Finnhub or Alpha Vantage keys yourself
- DCF outputs are assumption-driven estimates; the skill itself admits they are not precise and cannot serve as actionable investment advice
- Coverage is focused on US stocks (all documented examples are US-listed); non-US market support is not documented
- No published backtesting or accuracy evidence; output quality depends on model reasoning and data quality
- The SKILL.md and MCP server are two distinct parts — installing only the skill file gives no real-time data tools
How does this skill compare with similar options?
Side by side with related skills; every score comes from the same FSRS standard.
| Skill | FS score | Stars | Last updated | License |
|---|---|---|---|---|
| Value Investing Agent this page | 55 · Use with care | ★ 23 | 8mo ago | MIT |
| Buffett Investment Thinking System | 53 · Use with care | ★ 823 | 6mo ago | — |
| Income Investment: Durable & Opportunistic Distribution Analysis | 59 · Recommended | ★ 17k | 13d ago | MIT |
| US Value Investing 4-Dimension Analysis Skill | 52 · Use with care | ★ 1.1k | 6mo ago | MIT |
| StockValuation.io Local Valuation Workflow | 58 · Recommended | ★ 33 | 1mo ago | Apache-2.0 |
Positioned as "every value investor deserves their own AI agent," it differs from simply asking a general-purpose AI assistant for a valuation by bundling live market data tools, explicit formulas, and watchlist management; compared to using the SKILL.md alone, the MCP server adds data fetching and report generation at the cost of requiring Node.js and an MCP client setup.
How did FollowSkills review this skill?
The SKILL.md is a pure methodology prompt: no permissions, no scripts, no credentials or sensitive-data handling; it mandates source citation and a disclaimer, giving transparent data flow. Deducted for: it instructs the model to pull from external data providers without disclosing external call scope, failure recovery or rollback; publisher identity is unverified.
Self-consistent formulas (DCF, Graham Number, growth formula) with a clear conservative-estimate rule, and repo vitest suites (dcf/graham/margin-of-safety) cover key calculation paths including negative FCF and zero-value edge cases. However, this is a static review with no executed tests, and the skill's failure feedback for missing/unavailable data is only principled guidance, so it is capped at 10.
Clear audience and five-step framework, with declared boundaries (circle of competence, non-advice disclaimer). Deducted for: no Chinese-language support, core function depends on overseas APIs (yahoo-finance, finnhub, alpha-vantage) with the default provider explicitly prone to 429 rate limiting, questionable mainland-China reachability, and no systematic non-fit/trigger conditions.
Well-layered (principles → framework → report spec → pitfalls) with disclaimer template, data-quality standards and known limitations (over-precision, value traps). Deducted for: no version/changelog within the skill, install/dependency notes live only in the README, and maintenance responsibility/update path is not stated at skill level.
Can produce structured valuation and margin-of-safety reports with reproducible formulas and thresholds. Deducted for: the value claim is essentially a generic investing-methodology prompt with limited evidence of marginal gain over directly asking Claude, and outputs still require user verification of data and assumptions; capped at 7 for static review.
Three test files target the core calculations, formula sources (Graham's works) are traceable, and fact/opinion separation is explicitly required. Deducted for: no executed tests, no CI or third-party execution evidence, and the skill file itself carries thin verifiable claims; conservatively 4 under the static cap of 5.
Open a dimension to read why it scored that way
Evidence confidence：Low — Mostly static review, author material or a limited demo; useful for discovery, not high-risk decisions.
See the full review method →