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Research Bias Self-Check

Makes the agent check itself for common research biases before investment research.

Source Download skill
Repository
HKUDS/Vibe-Trading
Stars
37,433
Licence
MIT
Files
1 file

What it does

This skill is a short checklist the AI agent reads before starting an investment research task such as a stock screen, sector study, or company deep-dive. It names five thinking traps that often distort AI-written research: only looking at large companies, missing non-English players, chasing hype labels instead of the actual business, searching only for supporting evidence, and relying on outdated figures. Once read, the agent is asked to broaden its search and cite at least one piece of contrary evidence before concluding. It is a mindset reset rather than a full workflow, and it points to two companion skills for checking numbers and final reports.

Great for

  • Analysts or students who want more balanced AI-assisted stock or sector research
  • Anyone who wants an agent to surface bear cases and smaller companies, not just the obvious large caps
  • Teams using the companion financial_rigor and report_audit skills as part of a layered review

Skip it if

  • People expecting a step-by-step research process or data retrieval; the file says it is only an attitude checklist, so it does not fetch or verify data itself
  • Using its output as investment advice; the checklist improves reasoning but does not make research correct or guarantee returns

Try asking

  • “Research the solar equipment supply chain and include smaller suppliers and non-English sources.”
  • “Do a deep-dive on this company and make sure you look for the bear case before concluding.”
  • “Screen the semiconductor sector, and tell me which important players are missing from the obvious leaders.”
  • “Check whether the AI revenue claims for this stock are real or just a marketing label.”
Step-by-step guide: how to use Research Bias Self-CheckInstall, first run, examples, tips and FAQs

Install in 3 steps

  1. 1

    Download the skill

    The ZIP contains the 1 original files, the MIT licence and an attribution note.

    research-discipline.zip
  2. 2

    Add it to your agent

    Claude Code (all projects)

    mkdir -p ~/.claude/skills && unzip research-discipline.zip -d ~/.claude/skills/

    Claude Code / Agent SDK (this project only)

    mkdir -p .claude/skills && unzip research-discipline.zip -d .claude/skills/

    Claude apps (web/desktop): Settings → Capabilities → Skills → Upload skill, and choose the ZIP.

  3. 3

    Ask for the task

    No special command needed — the agent reads the skill's description and loads it when your request matches. Try one of the prompts above.

Get better results

  • Pair it with the financial_rigor cross_validate and report_audit skills, since this file only covers reasoning, not numbers or report quality.
  • Ask the agent explicitly for small-cap, non-English, and bear-case searches so the broadened query plan actually happens.
  • Request dates on key figures so you can see which numbers the agent flagged as possibly stale.

What's inside

  • SKILL.md

Redistributed unmodified from HKUDS/Vibe-Trading under the MIT licence. The assessment was drafted with AI from the skill's files on 2026-10-29. Skills can instruct your agent to run code — read SKILL.md and any scripts before installing.