# Research Discipline

A short self-bias checklist to run at the START of any investment research task (stock...

- Repository: https://github.com/HKUDS/Vibe-Trading (37375 stars)
- Category: Writing
- License: MIT
- Last updated: 2026-11-01
- Runs scripts: no, instructions only

## Install

Claude Code: `npx skills add HKUDS/Vibe-Trading --skill research-discipline -g -a claude-code -y`
Codex: `npx skills add HKUDS/Vibe-Trading --skill research-discipline -g -a codex -y`
Cursor: `npx skills add HKUDS/Vibe-Trading --skill research-discipline -g -a cursor -y`
Gemini CLI: `npx skills add HKUDS/Vibe-Trading --skill research-discipline -g -a gemini-cli -y`

## Description

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.

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

# 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". |

## How to apply

The rest: https://github.com/HKUDS/Vibe-Trading/blob/HEAD/agent/src/skills/research-discipline/SKILL.md