Creator · kangarooking
Last updated · Sep 1, 2026
当用户在选择合作者/生意模式/人生策略、问「要不要长期投入这段关系/这个项目」「如何积累声誉」时调用。 核心理念: 财富、知识、声誉、关系都遵循复利; 只玩长期正和游戏, 与能想象共事一辈子的人合作, 拒绝短期思维交易。 不适用于: 紧急止损、短期现金周转等必须立即决策的场景。 Triggers: 长期/复利/声誉/合作/信任/compounding/long-term/trust
Review then install
Install targets
Codex install prompt
Install the "long-term-compounding" agent skill from https://github.com/kangarooking/cangjie-skill/tree/main/books/naval-almanack-skill/long-term-compounding. Read its SKILL.md or equivalent instructions first, install only the files needed for this workspace, and summarize any required setup before using it. Skill purpose: 当用户在选择合作者/生意模式/人生策略、问「要不要长期投入这段关系/这个项目」「如何积累声誉」时调用。 核心理念: 财富、知识、声誉、关系都遵循复利; 只玩长期正和游戏, 与能想象共事一辈子的人合作, 拒绝短期思维交易。 不适用于: 紧急止损、短期现金周转等必须立即决策的场景。 Triggers: 长期/复利/声誉/合作/信任/compounding/long-term/trust After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {"event_id":"install_<unique-id>","skill_slug":"kangarooking-long-term-compounding","task":"Install long-term-compounding","agent":"codex","outcome":"success","install_used":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes.Supply asset profile
Code review, repo analysis, testing, CI, GitHub, DevOps, and developer workflow skills.
Scenario
Testing and QA
I need my agent to test a web app, reproduce bugs, and verify fixes.
Agent fit
Claude Code + CLI + Codex
Codex, Claude Code, Cursor, CLI, or custom agents.
Install
Ready
npx skills add kangarooking/cangjie-skill --skill long-term-compounding
Maintenance
fresh
9d since push
Risk
Safe to try
Quality score needs review
GitHub quality
9.3K
91/100 Quality · 88/100 Trust
Coverage tags
Review notes
Quality score needs review
Agent adoption scorecard
These scores combine public repository metadata, OpenAgentSkill review signals, maintenance freshness, and install readiness. They are a shortlist signal, not a replacement for human review.
Quality
ExcellentHigh-confidence pick with strong adoption and healthy maintenance signals.
Trust
Review then installGood shortlist signal, but the agent should review audit notes, install policy, and outcome evidence before running it.
Audit
Safe to tryA machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
OpenAgentSkill Trust Score v5
Use as the primary candidate after human or sandbox review.
Stars
9.3K GitHub stars
Repo activity
9.3K stars, 1.1K forks
Maintenance
9d since push
License
MIT
Install
npx skills add kangarooking/cangjie-skill --skill long-term-compounding
Install safety
Agent-readable metadata
Use this block or the embedded JSON to decide whether an agent should install this skill, choose an alternative, or ask for human review first.
Suited tasks
Suited agents
Install decision
Trust and risk
Outcome loop
Install command
npx skills add kangarooking/cangjie-skill --skill long-term-compoundingDo not use when
Agent safety v2
Good audit and safety signals with no high-risk permission hints in public metadata.
Review the audit page, then allow agent install in a sandboxed workflow.
medium
Skill likely fetches remote pages, APIs, repositories, or external services.
Agent resolve plan
The Resolve API returns the selected skill, alternatives, safety policy, audit notes, install target, and copy-paste prompt an agent can follow without scraping this page.
Open JSON
/api/agent/resolve?task=Use%20long-term-compounding%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve text
/api/agent/resolve?task=Use%20long-term-compounding%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Install handoff
/api/skills/kangarooking-long-term-compounding/install
Agent should check
Copy prompt
Task: Use long-term-compounding in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20long-term-compounding%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/kangarooking-long-term-compounding/install
Install command: npx skills add kangarooking/cangjie-skill --skill long-term-compounding
Before running it, summarize audit warnings, required permissions, and the fallback skill if install is risky.Agent handoff
Use the public install endpoint to fetch the command, safety checklist, target prompts, and canonical links for this skill.
Install handoff
/api/skills/kangarooking-long-term-compounding/install
LLM text format
/api/skills/kangarooking-long-term-compounding/install?format=text
Find alternatives
/api/skills/search?q=long-term-compounding&limit=3
Agent prompt
Use long-term-compounding for this task. Review https://www.openagentskill.com/api/skills/kangarooking-long-term-compounding/install, then install with: npx skills add kangarooking/cangjie-skill --skill long-term-compoundingRegistry metadata
This page exposes the same decision, trust, audit, use-case, and install signals through the Registry API, so agents can rank this skill without scraping the UI.
Manifest
/api/registry/manifest/kangarooking-long-term-compounding
LLM text
/api/registry/manifest/kangarooking-long-term-compounding?format=text
Install alias
/api/registry/install/kangarooking-long-term-compounding
Recommend
/api/registry/recommend?task=Use%20long-term-compounding%20in%20an%20agent%20workflow&limit=3
Agent fit
Browser automation
Use-case tags
Platforms
Claude Code
Audit report
A machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
Agent decision cockpit
Use this as a leading candidate, then validate the README and install path in your own agent stack.
Role in stack
Primary pick
Primary fit
Browser automation
Trust label
Production-ready
Install path
Command ready
Use when
Evidence
review first
Implementation path
Trust profile
Good shortlist signal, but the agent should review audit notes, install policy, and outcome evidence before running it.
GitHub adoption
PASS9.3K GitHub stars
Stars/forks activity
PASS9.3K stars, 1.1K forks; issue activity unavailable in current metadata
Recent maintenance
PASS9d since push
License clarity
PASSMIT
Good signals
Review before install
Recommended action
Use as the primary candidate after human or sandbox review.
Quality profile
High-confidence pick with strong adoption and healthy maintenance signals.
Workflow fit
Operate web apps
I need my agent to control a browser, fill forms, and verify web app workflows.
Operate local tools
I need my agent to operate local files and desktop apps in a repeatable workflow.
Investigate faster
I need my agent to research a topic, compare sources, and produce a concise report.
Workflow fit
Operate and verify web apps
A workflow for agents that navigate products, fill forms, take screenshots, and verify real user flows across web applications.
Turn skills into distribution
A workflow for turning newly indexed skills into SEO briefs, social drafts, comparison pages, and reusable publishing workflows.
Find, compare, and synthesize
A workflow for agents that gather sources, compare claims, summarize long material, and draft useful research briefs.
Alternative shortlist
Similar skills that may fit this task.
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--- name: long-term-compounding description: | 当用户在选择合作者/生意模式/人生策略、问「要不要长期投入这段关系/这个项目」「如何积累声誉」时调用。 核心理念: 财富、知识、声誉、关系都遵循复利; 只玩长期正和游戏, 与能想象共事一辈子的人合作, 拒绝短期思维交易。 不适用于: 紧急止损、短期现金周转等必须立即决策的场景。 Triggers: 长期/复利/声誉/合作/信任/compounding/long-term/trust source_book: 《纳瓦尔宝典:财富与幸福指南》 纳瓦尔·拉维坎特 source_chapter: 第一章·财富 / 第一节 创造财富 / 认识如何创造财富 tags: [long-term, compounding, relationship, trust, reputation] related_skills: - slug: wealth-structure relation: composes-with - slug: peer-selection relation: composes-with - slug: game-selection relation: contrasts-with ---
# 长期复利游戏
## R — 原文 (Reading)
> 玩复利游戏。无论是财富,人际关系或是知识,所有你人生里获得的回报,都来自于复利。……我的联合创始人Nivi说,“在一个长期游戏里,好像每个人都在让彼此发财,而在一个短期游戏里,好像每个人都在让自己发财。” > > — 纳瓦尔·拉维坎特, 《纳瓦尔宝典》 第一章·财富
## I — 方法论骨架 (Interpretation)
把复利从金融概念升级为通用人生规律:财富、知识、声誉、关系都以指数方式积累, 所以选择的判据不是「现在能拿多少」,而是「这件事在十年尺度上是否复利」。 两个推论:① 只与「能想象共事一辈子」的长期伙伴合作——信任让谈判成本趋近于零; ② 只玩长期正和游戏——长期游戏里人人把饼做大,短期游戏里人人抢饼。 声誉是最典型的复利资产:持续几十年维护诚信,最终价值远超有才华但无声誉积累的人。 反面筛选信号:愤世嫉俗者、悲观主义者、短期思维者——他们会破坏复利结构。
## A1 — 书中的应用 (Past Application)
### 案例 1: 与 Elad Gil 的交易 - **问题**: 商业谈判成本高、信任难建立 - **方法论的使用**: 与 Elad Gil 长期交易,对方主动多给好处、差额自掏腰包 - **结论**: 信任让常规谈判极简,彼此愿意让利 - **结果**: 作者几乎每笔交易都优先拉对方入局,关系进入复利循环
### 案例 2: 声誉换来别人做不了的交易 - **问题**: 为什么巴菲特能买到别人买不到的公司 - **方法论的使用**: 长期诚信+可靠+长期思维建立的声誉品牌 - **结论**: 「你的性格和你的声誉是可以建立的……你知道这不是运气」 - **结果**: 别人把「运气」当机会时,声誉者把机会变成确定收益
## A2 — 触发场景 (Future Trigger) ★
### 用户会在什么情境下需要这个 skill?
1. 评估合作/合伙/签约对象:「这个人能合作五年十年吗」 2. 犹豫是否接受短期高回报交易:「这单来钱快但伤口碑」 3. 想积累声誉/复利资产:「怎么让机会主动来找我」 4. 关系决策:「这段关系值得长期投入吗」
### 语言信号
- "长期 vs 短期怎么选" - "这个人靠谱吗/值得长期合作吗" - "怎么建立信任/声誉" - "compounding / long-term game / is this person trustworthy"
### 与相邻 skill 的区分
- 与 `game-selection` 的区别: 本 skill 关注时间尺度(长期/短期);game-selection 关注博弈结构(零和/正和/单人) - 与 `peer-selection` 的区别: 本 skill 的伙伴筛选服务于复利收益;peer-selection 服务于幸福与行为塑造
## E — 可执行步骤 (Execution)
1. **对候选机会跑复利测试** - 完成标准: 回答「十年后它还值多少?现在投入的信任/时间/钱会不会指数增长?」 - 判停条件: 若答案是「不可复利且只是快钱」,标记为短期游戏,慎重
2. **对合作者跑『一辈子』测试** - 完成标准: 问「我能想象和这个人共事/生活一辈子吗?」;不能,则一天也别开始
3. **检查负向信号** - 完成标准: 确认对方不是愤世嫉俗者/悲观主义者/短期思维者(他们要证明自己负面看法正确)
4. **为声誉做一笔复利存款** - 完成标准: 本周期内做一件「对方会记得的好事」,不记账、不估量
## B — 边界 (Boundary) ★
### 不要在以下情况使用此 skill
- 对方已在诈骗/违法边缘(先止损,不要用长期主义自我麻痹) - 用户急需短期现金流救急(先解决生存,再谈复利)
### 作者在书中警告的失败模式
- 与愤世嫉俗者合作: 「他们会任由坏事发生,以证明他们负面看法是正确的」 - 估量付出: 「不要去估量——一旦开始计较,你的耐性就会耗尽」
### 作者的盲点 / 时代局限
- 长期游戏假设环境稳定可预期;在剧变行业/强监管环境,长期承诺也有风险 - 「所有好处都来自复利」是强断言,未考虑不可复利的必要止损
### 容易混淆的邻近方法论
- `game-selection`: 先识别博弈结构,再决定玩长期还是短期
---
## 相关 skills (阶段 3 定稿)
- composes-with: `wealth-structure`(复利结构)、`peer-selection`(长期伙伴) - contrasts-with: `game-selection`(时间尺度 vs 博弈结构)
---
## 审计信息
- **验证通过**: V1 ✓ / V2 ✓ / V3 ✓ (v03) - **测试通过率**: 见 test-results.md - **蒸馏时间**: 2026-08-01
Source provenance
Decision snapshot
9,334 GitHub stars
Audit
Install and adoption review
Agent-proven evidence
Outcome reports after resolve, review, install, and one narrow run.
No agent outcome data yet. The first agent run can report success, setup needs, risk blocks, failure, or not-relevant through /api/agent/outcome.
Install
Free and open source. Review the report before installing into production agents.
Growth loop
Scenario-led draft for long-term-compounding, ready for a manual X post.
long-term-compounding: 当用户在选择合作者/生意模式/人生策略、问「要不要长期投入这段关系/这个项目」「如何积累声誉」时调用。 核心理念: 财富、知识、声誉、关系都遵循复利; 只玩长期正和游戏, 与能想象共事一... 9.3K stars https://www.openagentskill.com/skills/kangarooking-long-term-compounding?ref=x
Listing + install path for long-term-compounding: https://www.openagentskill.com/skills/kangarooking-long-term-compounding?ref=x Install: npx skills add kangarooking/cangjie-skill --skill long-term-compounding
Listing source
This listing was indexed from public sources and is not marked official until a maintainer claim is approved.
Attribution links to the public repository or creator profile. Creators can claim the listing to update ownership signals.
Claim this skillOwner claim
This Registry indexed listing is attributed to kangarooking but is not marked official yet. Claim it to add a verified owner signal and make future launch, install, and audit updates easier to trust.
Creator backlink kit
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Review then install
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no high-risk permission surface in public metadata
Agent outcomes
No agent outcome data yet
Docs
Strong README/SKILL.md context
Risk summary
Install readiness