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Long-Term Compounding Advisor

Helps the agent weigh long-term vs short-term choices in partnerships, deals and reputation-building

Source Download skill
Repository
kangarooking/cangjie-skill
Stars
11,998
Licence
MIT
Files
3 files

What it does

This is a thinking framework based on ideas from Naval Ravikant's book, written in Chinese. When you ask whether to commit to a partner, project or relationship long-term, or how to build trust and reputation, the agent applies a 'compounding' lens: it asks whether the decision will grow in value over about ten years, whether you could imagine working with the person for a lifetime, and whether the other party shows cynical or short-term habits. It is advice-style reasoning, not a tool that takes actions.

Great for

  • People deciding whether to take on a long-term business partner, client or hire
  • Founders or freelancers weighing a quick, lucrative deal against their reputation
  • Anyone wanting a structured way to think about trust and long-term relationships

Skip it if

  • Emergencies or urgent cash-flow problems, which the skill itself says should be decided immediately rather than through long-term reasoning
  • Situations involving fraud or illegal activity, where the skill says to stop losses first rather than rely on long-term patience
  • Fast-changing or heavily regulated industries, where the book's assumption of stable, predictable environments may not hold

Try asking

  • “Should I commit to a three-year partnership with this co-founder? Run the lifetime test on them.”
  • “This client pays well fast but the work will hurt my reputation. Is it worth it?”
  • “How can I build a reputation so good opportunities come to me?”
  • “Is this person trustworthy enough for a long-term collaboration?”
Step-by-step guide: how to use Long-Term Compounding AdvisorInstall, first run, examples, tips and FAQs

Install in 3 steps

  1. 1

    Download the skill

    The ZIP contains the 3 original files, the MIT licence and an attribution note.

    long-term-compounding.zip
  2. 2

    Add it to your agent

    Claude Code (all projects)

    mkdir -p ~/.claude/skills && unzip long-term-compounding.zip -d ~/.claude/skills/

    Claude Code / Agent SDK (this project only)

    mkdir -p .claude/skills && unzip long-term-compounding.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

  • Give the agent concrete context about the person or opportunity, such as timeline, money at stake and past interactions, so the reasoning is specific.
  • Treat the output as a prompt for your own judgement; the skill itself notes that long-term thinking has blind spots and does not cover necessary stop-losses.
  • The skill is written in Chinese; asking in Chinese may produce the most natural results, though English triggers are listed.

What's inside

  • SKILL.md
  • test-prompts.json
  • test-results.md

Redistributed unmodified from kangarooking/cangjie-skill 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.