Creator · kangarooking
Last updated · Sep 1, 2026
当用户纠结交朋友/选伴侣/换圈子、感觉被周围人拖累、问「该不该疏远某人」时调用。 核心理念: 五只黑猩猩理论(你的行为由最常接触的5人预测); 同伴是主动选择而非巧合; 只与价值观一致者深交, 远离愤世嫉俗者/愤怒者。 不适用于: 职场必须共事的同事关系(可先设边界)。 Triggers: 朋友/圈子/伴侣/该不该疏远/被拖累/五只黑猩猩/peer/friends/circle/values
Creator · kangarooking
Last updated · Sep 1, 2026
当用户纠结交朋友/选伴侣/换圈子、感觉被周围人拖累、问「该不该疏远某人」时调用。 核心理念: 五只黑猩猩理论(你的行为由最常接触的5人预测); 同伴是主动选择而非巧合; 只与价值观一致者深交, 远离愤世嫉俗者/愤怒者。 不适用于: 职场必须共事的同事关系(可先设边界)。 Triggers: 朋友/圈子/伴侣/该不该疏远/被拖累/五只黑猩猩/peer/friends/circle/values
Creator · kangarooking
Last updated · Sep 1, 2026
当用户纠结交朋友/选伴侣/换圈子、感觉被周围人拖累、问「该不该疏远某人」时调用。 核心理念: 五只黑猩猩理论(你的行为由最常接触的5人预测); 同伴是主动选择而非巧合; 只与价值观一致者深交, 远离愤世嫉俗者/愤怒者。 不适用于: 职场必须共事的同事关系(可先设边界)。 Triggers: 朋友/圈子/伴侣/该不该疏远/被拖累/五只黑猩猩/peer/friends/circle/values
Creator · kangarooking
Last updated · Sep 1, 2026
当用户纠结交朋友/选伴侣/换圈子、感觉被周围人拖累、问「该不该疏远某人」时调用。 核心理念: 五只黑猩猩理论(你的行为由最常接触的5人预测); 同伴是主动选择而非巧合; 只与价值观一致者深交, 远离愤世嫉俗者/愤怒者。 不适用于: 职场必须共事的同事关系(可先设边界)。 Triggers: 朋友/圈子/伴侣/该不该疏远/被拖累/五只黑猩猩/peer/friends/circle/values
Review then install
Install targets
Codex install prompt
Install the "peer-selection" agent skill from https://github.com/kangarooking/cangjie-skill/tree/main/books/naval-almanack-skill/peer-selection. 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: 当用户纠结交朋友/选伴侣/换圈子、感觉被周围人拖累、问「该不该疏远某人」时调用。 核心理念: 五只黑猩猩理论(你的行为由最常接触的5人预测); 同伴是主动选择而非巧合; 只与价值观一致者深交, 远离愤世嫉俗者/愤怒者。 不适用于: 职场必须共事的同事关系(可先设边界)。 Triggers: 朋友/圈子/伴侣/该不该疏远/被拖累/五只黑猩猩/peer/friends/circle/values 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-peer-selection","task":"Install peer-selection","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 peer-selection
Maintenance
fresh
7d 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
7d since push
License
MIT
Install
npx skills add kangarooking/cangjie-skill --skill peer-selection
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 peer-selectionDo 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%20peer-selection%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve text
/api/agent/resolve?task=Use%20peer-selection%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Install handoff
/api/skills/kangarooking-peer-selection/install
Agent should check
Copy prompt
Task: Use peer-selection in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20peer-selection%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/kangarooking-peer-selection/install
Install command: npx skills add kangarooking/cangjie-skill --skill peer-selection
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-peer-selection/install
LLM text format
/api/skills/kangarooking-peer-selection/install?format=text
Find alternatives
/api/skills/search?q=peer-selection&limit=3
Agent prompt
Use peer-selection for this task. Review https://www.openagentskill.com/api/skills/kangarooking-peer-selection/install, then install with: npx skills add kangarooking/cangjie-skill --skill peer-selectionRegistry 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-peer-selection
LLM text
/api/registry/manifest/kangarooking-peer-selection?format=text
Install alias
/api/registry/install/kangarooking-peer-selection
Recommend
/api/registry/recommend?task=Use%20peer-selection%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
PASS7d 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.
Verify behavior
I need my agent to test a web app, reproduce bugs, and verify fixes.
Operate local tools
I need my agent to operate local files and desktop apps in a repeatable workflow.
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: peer-selection description: | 当用户纠结交朋友/选伴侣/换圈子、感觉被周围人拖累、问「该不该疏远某人」时调用。 核心理念: 五只黑猩猩理论(你的行为由最常接触的5人预测); 同伴是主动选择而非巧合; 只与价值观一致者深交, 远离愤世嫉俗者/愤怒者。 不适用于: 职场必须共事的同事关系(可先设边界)。 Triggers: 朋友/圈子/伴侣/该不该疏远/被拖累/五只黑猩猩/peer/friends/circle/values source_book: 《纳瓦尔宝典:财富与幸福指南》 纳瓦尔·拉维坎特 source_chapter: 第二章·幸福 / 第一节 学习幸福 / 习惯造就幸福 tags: [relationship, happiness, values, community] related_skills: - slug: happiness-skill relation: composes-with - slug: long-term-compounding relation: composes-with - slug: honesty-communication relation: composes-with ---
# 同伴选择:五只黑猩猩
## R — 原文 (Reading)
> 有个“五只黑猩猩的理论”,你可以通过它最常接触的五个黑猩猩来预测一个黑猩猩的行为。……你不应该随意地选择你的朋友,仅仅是因为你们住的比较近或者碰巧在一起工作。选择了正确的五只黑猩猩的人,是最快乐和最乐观的人。 > > — 纳瓦尔·拉维坎特, 《纳瓦尔宝典》 第二章·幸福
## I — 方法论骨架 (Interpretation)
你的行为、情绪和成就由**最常接触的五个人**预测——所以同伴选择是人生最重要的主动决策之一。 三个原则: ① **主动选择**——朋友不是地理/巧合的产物,而是价值观筛选的结果; ② **按场景配置**——「工作时,身边要有比你更成功的人;玩乐时,身边要有比你更快乐的人」; ③ **远离负向者**——愤世嫉俗者/悲观主义者会传染负面预期;处理冲突的第一规则是「不要和那些经常发生冲突的人在一起」;「如果你不能看到你与某人一起工作一辈子,那么连一天也不要和他共事」。 判断信号:总说自己诚实的人多半不诚实;花很多时间谈论价值观的人可能在掩盖什么; 价值观一致时小事不重要,价值观冲突才是争吵的根源。
## A1 — 书中的应用 (Past Application)
### 案例 1: 贝赫扎德的「哇」 - **问题**: 如何保持对生活的感恩与乐观 - **方法论的使用**: 学习热爱生活、不浪费时间在不快乐的人身上 - **结论**: 他的诀窍是「停止询问为什么,开始说哇」 - **结果**: 成为作者心中选择正确同伴的样板
### 案例 2: 从生活中剔除负面者 - **问题**: 有人做损害他人的事 - **方法论的使用**: 第一次提醒,不改就保持距离、从生活中切割 - **结论**: 「越想靠近我的,你的价值观必须要更好」 - **结果**: 圈子成为价值观过滤后的结果
## A2 — 触发场景 (Future Trigger) ★
### 用户会在什么情境下需要这个 skill?
1. 换城市/换工作后的交友 2. 被朋友拖累:「朋友总在抱怨,我也变消极了」 3. 择偶/亲密关系选择 4. 想改变圈子:「我想认识更优秀/更快乐的人」
### 语言信号
- "我该交什么样的朋友" - "要不要疏远某人" - "怎么认识优秀的人/换圈子" - "who should I surround myself with / toxic friends"
### 与相邻 skill 的区分
- 与 `long-term-compounding` 的区别: 本 skill 选「和谁生活」;复利 skill 选「和谁做生意」 - 与 `honesty-communication` 的区别: 诚实是自我标准,本 skill 是外部筛选标准
## E — 可执行步骤 (Execution)
1. **盘点你的五只黑猩猩** - 完成标准: 列出最常接触的 5 人,逐个标「积极/消极/中性」,评估他们预测了你的什么行为
2. **按场景调整配置** - 完成标准: 明确工作圈和玩乐圈分别缺什么(更成功/更快乐),列出 1 个具体加入动作(活动/社群/项目)
3. **处理负向关系** - 完成标准: 对每个消极关系选一:改造(明确沟通)、边界(减少接触频次)、或切割(退出) - 判停条件: 若对方是亲属/同事无法切割,改为设置接触边界并补齐正向外圈
4. **建立价值观检查** - 完成标准: 写下一份 3–5 条核心价值观清单,用来判断新朋友是否「小事不重要、大事一致」
## B — 边界 (Boundary) ★
### 不要在以下情况使用此 skill
- 必须共事的同事/家人(先边界,再切割) - 用户自身处于低谷、把责任全推给环境(先自我负责再选圈)
### 作者在书中警告的失败模式
- 随意选友: 「仅仅是因为你们住的比较近或者碰巧在一起工作」 - 与经常冲突的人在一起: 冲突是低质量关系的信号,不是性格磨合
### 作者的盲点 / 时代局限
- 「远离不快乐的人」在家庭/社群文化中的执行成本高,且可能滑向同温层 - 五只黑猩猩是预测性比喻,非严谨心理学结论
### 容易混淆的邻近方法论
- `long-term-compounding`: 生意伙伴选「能共事一辈子」;生活同伴选「价值观一致+积极」
---
## 相关 skills (阶段 3 定稿)
- composes-with: `happiness-skill`、`long-term-compounding`、`honesty-communication`
---
## 审计信息
- **验证通过**: V1 ✓ / V2 ✓ / V3 ✓ (v15) - **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 peer-selection, ready for a manual X post.
A practical pick for a repeatable workflow: peer-selection: 当用户纠结交朋友/选伴侣/换圈子、感觉被周围人拖累、问「该不该疏远某人」时调用。 核心理念: 五只黑猩猩理论(你的行为由最常接触的5人预测); 同伴是主动选择而非巧合; 只与价值观一致者深交, 远离愤世嫉俗者/愤怒者。 不适用于: 职场必须共事的... 9.3K stars https://www.openagentskill.com/skills/kangarooking-peer-selection?ref=x
Listing + install path for peer-selection: https://www.openagentskill.com/skills/kangarooking-peer-selection?ref=x Install: npx skills add kangarooking/cangjie-skill --skill peer-selection
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
Show the canonical listing, current trust and audit signals, and real Agent-Proven evidence where developers evaluate the repository.
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@kangarooking
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Review then install
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Install targets
Codex install prompt
Install the "peer-selection" agent skill from https://github.com/kangarooking/cangjie-skill/tree/main/books/naval-almanack-skill/peer-selection. 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: 当用户纠结交朋友/选伴侣/换圈子、感觉被周围人拖累、问「该不该疏远某人」时调用。 核心理念: 五只黑猩猩理论(你的行为由最常接触的5人预测); 同伴是主动选择而非巧合; 只与价值观一致者深交, 远离愤世嫉俗者/愤怒者。 不适用于: 职场必须共事的同事关系(可先设边界)。 Triggers: 朋友/圈子/伴侣/该不该疏远/被拖累/五只黑猩猩/peer/friends/circle/values 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-peer-selection","task":"Install peer-selection","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 peer-selection
Maintenance
fresh
7d 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
7d since push
License
MIT
Install
npx skills add kangarooking/cangjie-skill --skill peer-selection
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 peer-selectionDo 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%20peer-selection%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve text
/api/agent/resolve?task=Use%20peer-selection%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Install handoff
/api/skills/kangarooking-peer-selection/install
Agent should check
Copy prompt
Task: Use peer-selection in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20peer-selection%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/kangarooking-peer-selection/install
Install command: npx skills add kangarooking/cangjie-skill --skill peer-selection
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-peer-selection/install
LLM text format
/api/skills/kangarooking-peer-selection/install?format=text
Find alternatives
/api/skills/search?q=peer-selection&limit=3
Agent prompt
Use peer-selection for this task. Review https://www.openagentskill.com/api/skills/kangarooking-peer-selection/install, then install with: npx skills add kangarooking/cangjie-skill --skill peer-selectionRegistry 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-peer-selection
LLM text
/api/registry/manifest/kangarooking-peer-selection?format=text
Install alias
/api/registry/install/kangarooking-peer-selection
Recommend
/api/registry/recommend?task=Use%20peer-selection%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
PASS7d 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.
Verify behavior
I need my agent to test a web app, reproduce bugs, and verify fixes.
Operate local tools
I need my agent to operate local files and desktop apps in a repeatable workflow.
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.
Run multimodal agents that operate desktop interfaces
Connect agents to hundreds of workflow automations
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--- name: peer-selection description: | 当用户纠结交朋友/选伴侣/换圈子、感觉被周围人拖累、问「该不该疏远某人」时调用。 核心理念: 五只黑猩猩理论(你的行为由最常接触的5人预测); 同伴是主动选择而非巧合; 只与价值观一致者深交, 远离愤世嫉俗者/愤怒者。 不适用于: 职场必须共事的同事关系(可先设边界)。 Triggers: 朋友/圈子/伴侣/该不该疏远/被拖累/五只黑猩猩/peer/friends/circle/values source_book: 《纳瓦尔宝典:财富与幸福指南》 纳瓦尔·拉维坎特 source_chapter: 第二章·幸福 / 第一节 学习幸福 / 习惯造就幸福 tags: [relationship, happiness, values, community] related_skills: - slug: happiness-skill relation: composes-with - slug: long-term-compounding relation: composes-with - slug: honesty-communication relation: composes-with ---
# 同伴选择:五只黑猩猩
## R — 原文 (Reading)
> 有个“五只黑猩猩的理论”,你可以通过它最常接触的五个黑猩猩来预测一个黑猩猩的行为。……你不应该随意地选择你的朋友,仅仅是因为你们住的比较近或者碰巧在一起工作。选择了正确的五只黑猩猩的人,是最快乐和最乐观的人。 > > — 纳瓦尔·拉维坎特, 《纳瓦尔宝典》 第二章·幸福
## I — 方法论骨架 (Interpretation)
你的行为、情绪和成就由**最常接触的五个人**预测——所以同伴选择是人生最重要的主动决策之一。 三个原则: ① **主动选择**——朋友不是地理/巧合的产物,而是价值观筛选的结果; ② **按场景配置**——「工作时,身边要有比你更成功的人;玩乐时,身边要有比你更快乐的人」; ③ **远离负向者**——愤世嫉俗者/悲观主义者会传染负面预期;处理冲突的第一规则是「不要和那些经常发生冲突的人在一起」;「如果你不能看到你与某人一起工作一辈子,那么连一天也不要和他共事」。 判断信号:总说自己诚实的人多半不诚实;花很多时间谈论价值观的人可能在掩盖什么; 价值观一致时小事不重要,价值观冲突才是争吵的根源。
## A1 — 书中的应用 (Past Application)
### 案例 1: 贝赫扎德的「哇」 - **问题**: 如何保持对生活的感恩与乐观 - **方法论的使用**: 学习热爱生活、不浪费时间在不快乐的人身上 - **结论**: 他的诀窍是「停止询问为什么,开始说哇」 - **结果**: 成为作者心中选择正确同伴的样板
### 案例 2: 从生活中剔除负面者 - **问题**: 有人做损害他人的事 - **方法论的使用**: 第一次提醒,不改就保持距离、从生活中切割 - **结论**: 「越想靠近我的,你的价值观必须要更好」 - **结果**: 圈子成为价值观过滤后的结果
## A2 — 触发场景 (Future Trigger) ★
### 用户会在什么情境下需要这个 skill?
1. 换城市/换工作后的交友 2. 被朋友拖累:「朋友总在抱怨,我也变消极了」 3. 择偶/亲密关系选择 4. 想改变圈子:「我想认识更优秀/更快乐的人」
### 语言信号
- "我该交什么样的朋友" - "要不要疏远某人" - "怎么认识优秀的人/换圈子" - "who should I surround myself with / toxic friends"
### 与相邻 skill 的区分
- 与 `long-term-compounding` 的区别: 本 skill 选「和谁生活」;复利 skill 选「和谁做生意」 - 与 `honesty-communication` 的区别: 诚实是自我标准,本 skill 是外部筛选标准
## E — 可执行步骤 (Execution)
1. **盘点你的五只黑猩猩** - 完成标准: 列出最常接触的 5 人,逐个标「积极/消极/中性」,评估他们预测了你的什么行为
2. **按场景调整配置** - 完成标准: 明确工作圈和玩乐圈分别缺什么(更成功/更快乐),列出 1 个具体加入动作(活动/社群/项目)
3. **处理负向关系** - 完成标准: 对每个消极关系选一:改造(明确沟通)、边界(减少接触频次)、或切割(退出) - 判停条件: 若对方是亲属/同事无法切割,改为设置接触边界并补齐正向外圈
4. **建立价值观检查** - 完成标准: 写下一份 3–5 条核心价值观清单,用来判断新朋友是否「小事不重要、大事一致」
## B — 边界 (Boundary) ★
### 不要在以下情况使用此 skill
- 必须共事的同事/家人(先边界,再切割) - 用户自身处于低谷、把责任全推给环境(先自我负责再选圈)
### 作者在书中警告的失败模式
- 随意选友: 「仅仅是因为你们住的比较近或者碰巧在一起工作」 - 与经常冲突的人在一起: 冲突是低质量关系的信号,不是性格磨合
### 作者的盲点 / 时代局限
- 「远离不快乐的人」在家庭/社群文化中的执行成本高,且可能滑向同温层 - 五只黑猩猩是预测性比喻,非严谨心理学结论
### 容易混淆的邻近方法论
- `long-term-compounding`: 生意伙伴选「能共事一辈子」;生活同伴选「价值观一致+积极」
---
## 相关 skills (阶段 3 定稿)
- composes-with: `happiness-skill`、`long-term-compounding`、`honesty-communication`
---
## 审计信息
- **验证通过**: V1 ✓ / V2 ✓ / V3 ✓ (v15) - **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 peer-selection, ready for a manual X post.
A practical pick for a repeatable workflow: peer-selection: 当用户纠结交朋友/选伴侣/换圈子、感觉被周围人拖累、问「该不该疏远某人」时调用。 核心理念: 五只黑猩猩理论(你的行为由最常接触的5人预测); 同伴是主动选择而非巧合; 只与价值观一致者深交, 远离愤世嫉俗者/愤怒者。 不适用于: 职场必须共事的... 9.3K stars https://www.openagentskill.com/skills/kangarooking-peer-selection?ref=x
Listing + install path for peer-selection: https://www.openagentskill.com/skills/kangarooking-peer-selection?ref=x Install: npx skills add kangarooking/cangjie-skill --skill peer-selection
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
Show the canonical listing, current trust and audit signals, and real Agent-Proven evidence where developers evaluate the repository.
[](https://www.openagentskill.com/skills/kangarooking-peer-selection?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[](https://www.openagentskill.com/skills/kangarooking-peer-selection?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[](https://www.openagentskill.com/skills/kangarooking-peer-selection/audit)
[](https://www.openagentskill.com/skills/kangarooking-peer-selection?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)kangarooking
@kangarooking
Share whether this skill looks useful for your agent workflow. Aggregated feedback improves rankings over time.
Review then install
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Install targets
Codex install prompt
Install the "peer-selection" agent skill from https://github.com/kangarooking/cangjie-skill/tree/main/books/naval-almanack-skill/peer-selection. 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: 当用户纠结交朋友/选伴侣/换圈子、感觉被周围人拖累、问「该不该疏远某人」时调用。 核心理念: 五只黑猩猩理论(你的行为由最常接触的5人预测); 同伴是主动选择而非巧合; 只与价值观一致者深交, 远离愤世嫉俗者/愤怒者。 不适用于: 职场必须共事的同事关系(可先设边界)。 Triggers: 朋友/圈子/伴侣/该不该疏远/被拖累/五只黑猩猩/peer/friends/circle/values 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-peer-selection","task":"Install peer-selection","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 peer-selection
Maintenance
fresh
7d 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
7d since push
License
MIT
Install
npx skills add kangarooking/cangjie-skill --skill peer-selection
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 peer-selectionDo 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%20peer-selection%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve text
/api/agent/resolve?task=Use%20peer-selection%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Install handoff
/api/skills/kangarooking-peer-selection/install
Agent should check
Copy prompt
Task: Use peer-selection in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20peer-selection%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/kangarooking-peer-selection/install
Install command: npx skills add kangarooking/cangjie-skill --skill peer-selection
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-peer-selection/install
LLM text format
/api/skills/kangarooking-peer-selection/install?format=text
Find alternatives
/api/skills/search?q=peer-selection&limit=3
Agent prompt
Use peer-selection for this task. Review https://www.openagentskill.com/api/skills/kangarooking-peer-selection/install, then install with: npx skills add kangarooking/cangjie-skill --skill peer-selectionRegistry 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-peer-selection
LLM text
/api/registry/manifest/kangarooking-peer-selection?format=text
Install alias
/api/registry/install/kangarooking-peer-selection
Recommend
/api/registry/recommend?task=Use%20peer-selection%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
PASS7d 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.
Verify behavior
I need my agent to test a web app, reproduce bugs, and verify fixes.
Operate local tools
I need my agent to operate local files and desktop apps in a repeatable workflow.
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.
Run multimodal agents that operate desktop interfaces
Connect agents to hundreds of workflow automations
利用AI大模型,一键生成高清短视频 Generate short videos with one click using AI LLM.
Alternative firmware for ESP8266 and ESP32 based devices with easy configuration using webUI, OTA updates, automation using timers or rules, expandability and entirely local control over MQTT, HTTP, Serial or KNX. Full documentation at
--- name: peer-selection description: | 当用户纠结交朋友/选伴侣/换圈子、感觉被周围人拖累、问「该不该疏远某人」时调用。 核心理念: 五只黑猩猩理论(你的行为由最常接触的5人预测); 同伴是主动选择而非巧合; 只与价值观一致者深交, 远离愤世嫉俗者/愤怒者。 不适用于: 职场必须共事的同事关系(可先设边界)。 Triggers: 朋友/圈子/伴侣/该不该疏远/被拖累/五只黑猩猩/peer/friends/circle/values source_book: 《纳瓦尔宝典:财富与幸福指南》 纳瓦尔·拉维坎特 source_chapter: 第二章·幸福 / 第一节 学习幸福 / 习惯造就幸福 tags: [relationship, happiness, values, community] related_skills: - slug: happiness-skill relation: composes-with - slug: long-term-compounding relation: composes-with - slug: honesty-communication relation: composes-with ---
# 同伴选择:五只黑猩猩
## R — 原文 (Reading)
> 有个“五只黑猩猩的理论”,你可以通过它最常接触的五个黑猩猩来预测一个黑猩猩的行为。……你不应该随意地选择你的朋友,仅仅是因为你们住的比较近或者碰巧在一起工作。选择了正确的五只黑猩猩的人,是最快乐和最乐观的人。 > > — 纳瓦尔·拉维坎特, 《纳瓦尔宝典》 第二章·幸福
## I — 方法论骨架 (Interpretation)
你的行为、情绪和成就由**最常接触的五个人**预测——所以同伴选择是人生最重要的主动决策之一。 三个原则: ① **主动选择**——朋友不是地理/巧合的产物,而是价值观筛选的结果; ② **按场景配置**——「工作时,身边要有比你更成功的人;玩乐时,身边要有比你更快乐的人」; ③ **远离负向者**——愤世嫉俗者/悲观主义者会传染负面预期;处理冲突的第一规则是「不要和那些经常发生冲突的人在一起」;「如果你不能看到你与某人一起工作一辈子,那么连一天也不要和他共事」。 判断信号:总说自己诚实的人多半不诚实;花很多时间谈论价值观的人可能在掩盖什么; 价值观一致时小事不重要,价值观冲突才是争吵的根源。
## A1 — 书中的应用 (Past Application)
### 案例 1: 贝赫扎德的「哇」 - **问题**: 如何保持对生活的感恩与乐观 - **方法论的使用**: 学习热爱生活、不浪费时间在不快乐的人身上 - **结论**: 他的诀窍是「停止询问为什么,开始说哇」 - **结果**: 成为作者心中选择正确同伴的样板
### 案例 2: 从生活中剔除负面者 - **问题**: 有人做损害他人的事 - **方法论的使用**: 第一次提醒,不改就保持距离、从生活中切割 - **结论**: 「越想靠近我的,你的价值观必须要更好」 - **结果**: 圈子成为价值观过滤后的结果
## A2 — 触发场景 (Future Trigger) ★
### 用户会在什么情境下需要这个 skill?
1. 换城市/换工作后的交友 2. 被朋友拖累:「朋友总在抱怨,我也变消极了」 3. 择偶/亲密关系选择 4. 想改变圈子:「我想认识更优秀/更快乐的人」
### 语言信号
- "我该交什么样的朋友" - "要不要疏远某人" - "怎么认识优秀的人/换圈子" - "who should I surround myself with / toxic friends"
### 与相邻 skill 的区分
- 与 `long-term-compounding` 的区别: 本 skill 选「和谁生活」;复利 skill 选「和谁做生意」 - 与 `honesty-communication` 的区别: 诚实是自我标准,本 skill 是外部筛选标准
## E — 可执行步骤 (Execution)
1. **盘点你的五只黑猩猩** - 完成标准: 列出最常接触的 5 人,逐个标「积极/消极/中性」,评估他们预测了你的什么行为
2. **按场景调整配置** - 完成标准: 明确工作圈和玩乐圈分别缺什么(更成功/更快乐),列出 1 个具体加入动作(活动/社群/项目)
3. **处理负向关系** - 完成标准: 对每个消极关系选一:改造(明确沟通)、边界(减少接触频次)、或切割(退出) - 判停条件: 若对方是亲属/同事无法切割,改为设置接触边界并补齐正向外圈
4. **建立价值观检查** - 完成标准: 写下一份 3–5 条核心价值观清单,用来判断新朋友是否「小事不重要、大事一致」
## B — 边界 (Boundary) ★
### 不要在以下情况使用此 skill
- 必须共事的同事/家人(先边界,再切割) - 用户自身处于低谷、把责任全推给环境(先自我负责再选圈)
### 作者在书中警告的失败模式
- 随意选友: 「仅仅是因为你们住的比较近或者碰巧在一起工作」 - 与经常冲突的人在一起: 冲突是低质量关系的信号,不是性格磨合
### 作者的盲点 / 时代局限
- 「远离不快乐的人」在家庭/社群文化中的执行成本高,且可能滑向同温层 - 五只黑猩猩是预测性比喻,非严谨心理学结论
### 容易混淆的邻近方法论
- `long-term-compounding`: 生意伙伴选「能共事一辈子」;生活同伴选「价值观一致+积极」
---
## 相关 skills (阶段 3 定稿)
- composes-with: `happiness-skill`、`long-term-compounding`、`honesty-communication`
---
## 审计信息
- **验证通过**: V1 ✓ / V2 ✓ / V3 ✓ (v15) - **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 peer-selection, ready for a manual X post.
A practical pick for a repeatable workflow: peer-selection: 当用户纠结交朋友/选伴侣/换圈子、感觉被周围人拖累、问「该不该疏远某人」时调用。 核心理念: 五只黑猩猩理论(你的行为由最常接触的5人预测); 同伴是主动选择而非巧合; 只与价值观一致者深交, 远离愤世嫉俗者/愤怒者。 不适用于: 职场必须共事的... 9.3K stars https://www.openagentskill.com/skills/kangarooking-peer-selection?ref=x
Listing + install path for peer-selection: https://www.openagentskill.com/skills/kangarooking-peer-selection?ref=x Install: npx skills add kangarooking/cangjie-skill --skill peer-selection
Listing source
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Attribution links to the public repository or creator profile. Creators can claim the listing to update ownership signals.
Claim this skillOwner claim
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Creator backlink kit
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[](https://www.openagentskill.com/skills/kangarooking-peer-selection?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[](https://www.openagentskill.com/skills/kangarooking-peer-selection?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[](https://www.openagentskill.com/skills/kangarooking-peer-selection/audit)
[](https://www.openagentskill.com/skills/kangarooking-peer-selection?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)kangarooking
@kangarooking
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Install targets
Codex install prompt
Install the "peer-selection" agent skill from https://github.com/kangarooking/cangjie-skill/tree/main/books/naval-almanack-skill/peer-selection. 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: 当用户纠结交朋友/选伴侣/换圈子、感觉被周围人拖累、问「该不该疏远某人」时调用。 核心理念: 五只黑猩猩理论(你的行为由最常接触的5人预测); 同伴是主动选择而非巧合; 只与价值观一致者深交, 远离愤世嫉俗者/愤怒者。 不适用于: 职场必须共事的同事关系(可先设边界)。 Triggers: 朋友/圈子/伴侣/该不该疏远/被拖累/五只黑猩猩/peer/friends/circle/values 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-peer-selection","task":"Install peer-selection","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 peer-selection
Maintenance
fresh
7d 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
7d since push
License
MIT
Install
npx skills add kangarooking/cangjie-skill --skill peer-selection
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 peer-selectionDo 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%20peer-selection%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve text
/api/agent/resolve?task=Use%20peer-selection%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Install handoff
/api/skills/kangarooking-peer-selection/install
Agent should check
Copy prompt
Task: Use peer-selection in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20peer-selection%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/kangarooking-peer-selection/install
Install command: npx skills add kangarooking/cangjie-skill --skill peer-selection
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-peer-selection/install
LLM text format
/api/skills/kangarooking-peer-selection/install?format=text
Find alternatives
/api/skills/search?q=peer-selection&limit=3
Agent prompt
Use peer-selection for this task. Review https://www.openagentskill.com/api/skills/kangarooking-peer-selection/install, then install with: npx skills add kangarooking/cangjie-skill --skill peer-selectionRegistry 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-peer-selection
LLM text
/api/registry/manifest/kangarooking-peer-selection?format=text
Install alias
/api/registry/install/kangarooking-peer-selection
Recommend
/api/registry/recommend?task=Use%20peer-selection%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
PASS7d 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.
Verify behavior
I need my agent to test a web app, reproduce bugs, and verify fixes.
Operate local tools
I need my agent to operate local files and desktop apps in a repeatable workflow.
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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利用AI大模型,一键生成高清短视频 Generate short videos with one click using AI LLM.
Alternative firmware for ESP8266 and ESP32 based devices with easy configuration using webUI, OTA updates, automation using timers or rules, expandability and entirely local control over MQTT, HTTP, Serial or KNX. Full documentation at
--- name: peer-selection description: | 当用户纠结交朋友/选伴侣/换圈子、感觉被周围人拖累、问「该不该疏远某人」时调用。 核心理念: 五只黑猩猩理论(你的行为由最常接触的5人预测); 同伴是主动选择而非巧合; 只与价值观一致者深交, 远离愤世嫉俗者/愤怒者。 不适用于: 职场必须共事的同事关系(可先设边界)。 Triggers: 朋友/圈子/伴侣/该不该疏远/被拖累/五只黑猩猩/peer/friends/circle/values source_book: 《纳瓦尔宝典:财富与幸福指南》 纳瓦尔·拉维坎特 source_chapter: 第二章·幸福 / 第一节 学习幸福 / 习惯造就幸福 tags: [relationship, happiness, values, community] related_skills: - slug: happiness-skill relation: composes-with - slug: long-term-compounding relation: composes-with - slug: honesty-communication relation: composes-with ---
# 同伴选择:五只黑猩猩
## R — 原文 (Reading)
> 有个“五只黑猩猩的理论”,你可以通过它最常接触的五个黑猩猩来预测一个黑猩猩的行为。……你不应该随意地选择你的朋友,仅仅是因为你们住的比较近或者碰巧在一起工作。选择了正确的五只黑猩猩的人,是最快乐和最乐观的人。 > > — 纳瓦尔·拉维坎特, 《纳瓦尔宝典》 第二章·幸福
## I — 方法论骨架 (Interpretation)
你的行为、情绪和成就由**最常接触的五个人**预测——所以同伴选择是人生最重要的主动决策之一。 三个原则: ① **主动选择**——朋友不是地理/巧合的产物,而是价值观筛选的结果; ② **按场景配置**——「工作时,身边要有比你更成功的人;玩乐时,身边要有比你更快乐的人」; ③ **远离负向者**——愤世嫉俗者/悲观主义者会传染负面预期;处理冲突的第一规则是「不要和那些经常发生冲突的人在一起」;「如果你不能看到你与某人一起工作一辈子,那么连一天也不要和他共事」。 判断信号:总说自己诚实的人多半不诚实;花很多时间谈论价值观的人可能在掩盖什么; 价值观一致时小事不重要,价值观冲突才是争吵的根源。
## A1 — 书中的应用 (Past Application)
### 案例 1: 贝赫扎德的「哇」 - **问题**: 如何保持对生活的感恩与乐观 - **方法论的使用**: 学习热爱生活、不浪费时间在不快乐的人身上 - **结论**: 他的诀窍是「停止询问为什么,开始说哇」 - **结果**: 成为作者心中选择正确同伴的样板
### 案例 2: 从生活中剔除负面者 - **问题**: 有人做损害他人的事 - **方法论的使用**: 第一次提醒,不改就保持距离、从生活中切割 - **结论**: 「越想靠近我的,你的价值观必须要更好」 - **结果**: 圈子成为价值观过滤后的结果
## A2 — 触发场景 (Future Trigger) ★
### 用户会在什么情境下需要这个 skill?
1. 换城市/换工作后的交友 2. 被朋友拖累:「朋友总在抱怨,我也变消极了」 3. 择偶/亲密关系选择 4. 想改变圈子:「我想认识更优秀/更快乐的人」
### 语言信号
- "我该交什么样的朋友" - "要不要疏远某人" - "怎么认识优秀的人/换圈子" - "who should I surround myself with / toxic friends"
### 与相邻 skill 的区分
- 与 `long-term-compounding` 的区别: 本 skill 选「和谁生活」;复利 skill 选「和谁做生意」 - 与 `honesty-communication` 的区别: 诚实是自我标准,本 skill 是外部筛选标准
## E — 可执行步骤 (Execution)
1. **盘点你的五只黑猩猩** - 完成标准: 列出最常接触的 5 人,逐个标「积极/消极/中性」,评估他们预测了你的什么行为
2. **按场景调整配置** - 完成标准: 明确工作圈和玩乐圈分别缺什么(更成功/更快乐),列出 1 个具体加入动作(活动/社群/项目)
3. **处理负向关系** - 完成标准: 对每个消极关系选一:改造(明确沟通)、边界(减少接触频次)、或切割(退出) - 判停条件: 若对方是亲属/同事无法切割,改为设置接触边界并补齐正向外圈
4. **建立价值观检查** - 完成标准: 写下一份 3–5 条核心价值观清单,用来判断新朋友是否「小事不重要、大事一致」
## B — 边界 (Boundary) ★
### 不要在以下情况使用此 skill
- 必须共事的同事/家人(先边界,再切割) - 用户自身处于低谷、把责任全推给环境(先自我负责再选圈)
### 作者在书中警告的失败模式
- 随意选友: 「仅仅是因为你们住的比较近或者碰巧在一起工作」 - 与经常冲突的人在一起: 冲突是低质量关系的信号,不是性格磨合
### 作者的盲点 / 时代局限
- 「远离不快乐的人」在家庭/社群文化中的执行成本高,且可能滑向同温层 - 五只黑猩猩是预测性比喻,非严谨心理学结论
### 容易混淆的邻近方法论
- `long-term-compounding`: 生意伙伴选「能共事一辈子」;生活同伴选「价值观一致+积极」
---
## 相关 skills (阶段 3 定稿)
- composes-with: `happiness-skill`、`long-term-compounding`、`honesty-communication`
---
## 审计信息
- **验证通过**: V1 ✓ / V2 ✓ / V3 ✓ (v15) - **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 peer-selection, ready for a manual X post.
A practical pick for a repeatable workflow: peer-selection: 当用户纠结交朋友/选伴侣/换圈子、感觉被周围人拖累、问「该不该疏远某人」时调用。 核心理念: 五只黑猩猩理论(你的行为由最常接触的5人预测); 同伴是主动选择而非巧合; 只与价值观一致者深交, 远离愤世嫉俗者/愤怒者。 不适用于: 职场必须共事的... 9.3K stars https://www.openagentskill.com/skills/kangarooking-peer-selection?ref=x
Listing + install path for peer-selection: https://www.openagentskill.com/skills/kangarooking-peer-selection?ref=x Install: npx skills add kangarooking/cangjie-skill --skill peer-selection
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
Show the canonical listing, current trust and audit signals, and real Agent-Proven evidence where developers evaluate the repository.
[](https://www.openagentskill.com/skills/kangarooking-peer-selection?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[](https://www.openagentskill.com/skills/kangarooking-peer-selection?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[](https://www.openagentskill.com/skills/kangarooking-peer-selection/audit)
[](https://www.openagentskill.com/skills/kangarooking-peer-selection?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)kangarooking
@kangarooking
Share whether this skill looks useful for your agent workflow. Aggregated feedback improves rankings over time.
Review then install
UI-TARS Desktop
Run multimodal agents that operate desktop interfaces
37.0K Starsn8n
Connect agents to hundreds of workflow automations
194.1K StarsMoneyPrinterTurbo
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88.5K StarsTasmota
Alternative firmware for ESP8266 and ESP32 based devices with easy configuration using webUI, OTA updates, automation using timers or rules, expandability and entirely local control over MQTT, HTTP, Serial or KNX. Full documentation at
24.7K StarsPermission surface
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
Permission surface
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
Permission surface
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
Permission surface
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