li-jialu/investor-panel-skill — explained in plain English
Analysis updated 2026-05-18
Ask the panel to analyze whether a stock is a great business, an overpriced one, or both.
Have several investor lenses debate a specific company and show where they disagree.
Rank a list of stocks by how worth further research they are.
Run a hold or sell review that lists the facts that would change your mind.
| li-jialu/investor-panel-skill | 0xazanul/fuzz-skill | 0xsero/tailscale-mullvad-toggle | |
|---|---|---|---|
| Stars | 31 | 31 | 31 |
| Language | — | C | Python |
| Setup difficulty | easy | moderate | easy |
| Complexity | 2/5 | 3/5 | 2/5 |
| Audience | pm founder | researcher | developer |
Figures from each repo's GitHub metadata at analysis time.
Meant to be installed as a Codex skill by pointing it at the GitHub repository.
Investor Panel Skill is an AI agent skill that lets you hand over a company, a stock, a position, or an investment thesis and have several well known investor styles review it together. Buffett looks at business quality and moat, Graham and Klarman look for margin of safety, Damodaran turns the story into numbers, Taleb hunts for tail risk, Druckenmiller and Soros focus on macro conditions and liquidity, Simons asks for statistical evidence, and a Serenity style lens digs into supply chain bottlenecks. Each investor is more than a name tag: it is a distilled profile covering where their information comes from, how they make decisions, how they judge business quality, management, financials, valuation, and when they would sell. The real value is not one more opinion, it is seeing where these experts disagree. Is a good company too expensive? Is its growth overestimated? Is a cheap stock actually a trap? Is the story missing real evidence? Is there a risk big enough to override everything else? A full analysis produces investor votes with a signal, a confidence level, and the core reason behind each one, plus a summary of where the panel agrees and where it genuinely splits. It also includes challenges to the thesis from angles like valuation, business cycle, financial health, governance, technology, and tail risk, along with the specific facts that would prove the thesis wrong, and a list of next things worth checking such as filings, metrics, news, or supply chain clues. The default panel spans around 26 lenses grouped by style: quality and long term compounding investors such as Buffett, Munger, and Fisher, value investors focused on safety margins such as Graham and Klarman, valuation focused thinkers such as Damodaran, macro and cycle watchers such as Druckenmiller, Soros, and Taleb, contrarian and special situation investors such as Simons, Burry, and Ackman, and a supply chain research lens in the Serenity style. To install it with Codex, you point Codex at the GitHub repository and ask it to install the entire skills folder, not just the main skill file. The project is explicit about its limits. It is research help, not investment advice. It does not promise returns or place trades, and it will not invent current prices, financials, filings, or holdings, so any claim about what is happening right now must be checked with real tools first.
An AI skill that runs a company or investment thesis past a panel of famous investor styles, from Buffett to Taleb, and surfaces where they agree and disagree.
The README does not state a license.
Setup difficulty is rated easy, with roughly 5min to a first successful run.
Mainly pm founder.
This repo across BitVibe Labs
Don't trust strangers blindly. Verify against the repo.