Research Discipline
A short self-bias checklist to run at the START of any investment research task (stock...
Install
npx skills add HKUDS/Vibe-Trading --skill research-discipline -g -a claude-code -y- Repository
- HKUDS/Vibe-Trading37.4k
- Category
- Writing
- Updated
- 3d ago
- License
- MIT
- Context cost
- Lightabout 575 tokens
- Runs scripts
- No, instructions only
What it does
A short self-bias checklist to run at the START of any investment research task (stock screen / sector study / company deep-dive). Four biases that systematically warp AI research, leader-bias (only big caps), English-bias (miss JP/KR/TW players), narrative-bias (chase concept labels), confirmation-bias (only bullish evidence), plus recency-bias. Load this first, then research with the corrections in mind. Not a workflow, just a 60-second attitude reset that materially improves coverage and honesty.
AI Research Bias Self-Check
Run this at the start of any research task (screening, sector study, company deep-dive). These biases systematically warp AI-generated research, 60 seconds here materially improves coverage and intellectual honesty.
The biases and their corrections
| Bias | How it shows | Correction |
|---|---|---|
| Leader-bias | Search results are dominated by large-caps; you end up analyzing only the obvious names. | Deliberately search small/mid-caps and suppliers; add small cap / mid cap / supply chain to queries. Ask: "who is NOT in the top-10 that should be here?" |
| English-bias | You miss Japanese / Korean / Taiwanese / European players because English sources under-cover them. | For any hardware/supply-chain thesis, explicitly search JP/KR/TW markets in their own languages, they are often the actual choke-point owners. |
| Narrative-bias | You get pulled in by a concept label ("AI stock", "new energy") and analyze the marketing instead of the business. | Ignore the label; look at the actual product, unit economics, and financial statements. A company tagged "AI" may have no AI revenue. |
| Confirmation-bias | Once a thesis forms, you only search for evidence that supports it. | Force a Munger inversion: for every bull point, deliberately search the bear case ("X risks / problems / bear case"). Cite at least one disconfirming data point per conclusion. |
| Recency-bias | You rely on a cached/outdated figure because it ranks high in search. | For any material number, check its date. Prefer the last 30 days; mark anything older than a year as "possibly stale". |
