{"slug":"kangarooking-peer-selection","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。\n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。\n不适用于: 职场必须共事的同事关系(可先设边界)。\nTriggers: 朋友/圈子/伴侣/该不该疏远/被拖累/五只黑猩猩/peer/friends/circle/values","long_description":"---\nname: peer-selection\ndescription: |\n  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。\n  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。\n  不适用于: 职场必须共事的同事关系(可先设边界)。\n  Triggers: 朋友/圈子/伴侣/该不该疏远/被拖累/五只黑猩猩/peer/friends/circle/values\nsource_book: 《纳瓦尔宝典：财富与幸福指南》 纳瓦尔·拉维坎特\nsource_chapter: 第二章·幸福 / 第一节 学习幸福 / 习惯造就幸福\ntags: [relationship, happiness, values, community]\nrelated_skills:\n  - slug: happiness-skill\n    relation: composes-with\n  - slug: long-term-compounding\n    relation: composes-with\n  - slug: honesty-communication\n    relation: composes-with\n---\n\n# 同伴选择：五只黑猩猩\n\n## R — 原文 (Reading)\n\n> 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。\n>\n> — 纳瓦尔·拉维坎特, 《纳瓦尔宝典》 第二章·幸福\n\n## I — 方法论骨架 (Interpretation)\n\n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。\n三个原则：\n① **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；\n② **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」；\n③ **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」。\n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；\n价值观一致时小事不重要，价值观冲突才是争吵的根源。\n\n## A1 — 书中的应用 (Past Application)\n\n### 案例 1: 贝赫扎德的「哇」\n- **问题**: 如何保持对生活的感恩与乐观\n- **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\n- **结论**: 他的诀窍是「停止询问为什么，开始说哇」\n- **结果**: 成为作者心中选择正确同伴的样板\n\n### 案例 2: 从生活中剔除负面者\n- **问题**: 有人做损害他人的事\n- **方法论的使用**: 第一次提醒，不改就保持距离、从生活中切割\n- **结论**: 「越想靠近我的，你的价值观必须要更好」\n- **结果**: 圈子成为价值观过滤后的结果\n\n## A2 — 触发场景 (Future Trigger) ★\n\n### 用户会在什么情境下需要这个 skill?\n\n1. 换城市/换工作后的交友\n2. 被朋友拖累：「朋友总在抱怨，我也变消极了」\n3. 择偶/亲密关系选择\n4. 想改变圈子：「我想认识更优秀/更快乐的人」\n\n### 语言信号\n\n- \"我该交什么样的朋友\"\n- \"要不要疏远某人\"\n- \"怎么认识优秀的人/换圈子\"\n- \"who should I surround myself with / toxic friends\"\n\n### 与相邻 skill 的区分\n\n- 与 `long-term-compounding` 的区别: 本 skill 选「和谁生活」；复利 skill 选「和谁做生意」\n- 与 `honesty-communication` 的区别: 诚实是自我标准，本 skill 是外部筛选标准\n\n## E — 可执行步骤 (Execution)\n\n1. **盘点你的五只黑猩猩**\n   - 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\n\n2. **按场景调整配置**\n   - 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）\n\n3. **处理负向关系**\n   - 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）\n   - 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\n\n4. **建立价值观检查**\n   - 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」\n\n## B — 边界 (Boundary) ★\n\n### 不要在以下情况使用此 skill\n\n- 必须共事的同事/家人（先边界，再切割）\n- 用户自身处于低谷、把责任全推给环境（先自我负责再选圈）\n\n### 作者在书中警告的失败模式\n\n- 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」\n- 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\n\n### 作者的盲点 / 时代局限\n\n- 「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\n- 五只黑猩猩是预测性比喻，非严谨心理学结论\n\n### 容易混淆的邻近方法论\n\n- `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」\n\n---\n\n## 相关 skills (阶段 3 定稿)\n\n- composes-with: `happiness-skill`、`long-term-compounding`、`honesty-communication`\n\n---\n\n## 审计信息\n\n- **验证通过**: V1 ✓ / V2 ✓ / V3 ✓ (v15)\n- **测试通过率**: 见 test-results.md\n- **蒸馏时间**: 2026-08-01\n","tagline":"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。\n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。\n不适用于: 职场必须共事的同事关系(可先设边界)。\nTriggers: 朋友/圈子/伴侣/该不该疏远/被拖累/五只黑猩猩/peer/friends/circle/values","category":"automation","tags":["relationship","happiness","values","community","agent-skill"],"author":"kangarooking","verified":false,"attribution":{"status":"registry_indexed","statusLabel":"Registry indexed","shortLabel":"REGISTRY INDEXED","sourceLabel":"github fast track","sourceDetail":"kangarooking/cangjie-skill","creatorName":"kangarooking","creatorUrl":"https://github.com/kangarooking","sourceUrl":"https://github.com/kangarooking/cangjie-skill/tree/main/books/naval-almanack-skill/peer-selection","indexedBy":"OpenAgentSkill community index","claimUrl":"https://www.openagentskill.com/skills/kangarooking-peer-selection#claim-this-skill","claimCta":"Claim this skill","trustNote":"This listing was indexed from public sources and is not marked official until a maintainer claim is approved.","publicNote":"Attribution links to the public repository or creator profile. 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rollout."]},"bestFor":["automation","relationship","happiness","values","community","agent-skill"],"doNotUseFor":["Production credentials, payments, or irreversible account changes without explicit human review","Sensitive private data before reviewing repository code, license, and permission surface"],"knownRisks":["Quality score needs review"],"backward_compatible":{"trust_score_v4":{"version":"trust-score-v4","score":88,"tier":"production","label":"Production candidate","summary":"Strong OpenAgentSkill Trust Score across adoption, recent maintenance, license clarity, documentation, dependency/runtime risk, install safety, permission surface, and install availability."}}},"trust_score_v4":{"version":"trust-score-v4","score":88,"tier":"production","label":"Production candidate","summary":"Strong OpenAgentSkill Trust Score across adoption, recent maintenance, license clarity, documentation, dependency/runtime risk, install safety, permission surface, and install availability.","recommendedAction":"Shortlist for production use, then run a normal repository and dependency review.","dimensions":[{"id":"github_adoption","label":"GitHub adoption","score":94,"weight":0.13,"status":"pass","detail":"9.3K GitHub stars"},{"id":"repo_activity","label":"Stars/forks activity","score":93,"weight":0.08,"status":"pass","detail":"9.3K stars, 1.1K forks; issue activity unavailable in current metadata"},{"id":"maintenance","label":"Recent maintenance","score":100,"weight":0.14,"status":"pass","detail":"7d since push"},{"id":"license","label":"License clarity","score":86,"weight":0.09,"status":"pass","detail":"MIT"},{"id":"documentation","label":"README/SKILL.md completeness","score":84,"weight":0.14,"status":"pass","detail":"Metadata includes enough usage and workflow context"},{"id":"dependency_risk","label":"Dependency/runtime risk","score":90,"weight":0.12,"status":"pass","detail":"no major dependency risk hints in public 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evidence","detail":"https://github.com/kangarooking/cangjie-skill/tree/main/books/naval-almanack-skill/peer-selection"},{"status":"pass","label":"Review status","detail":"AI review data available"},{"status":"info","label":"Agent Proven outcomes","detail":"No agent outcome data yet"},{"status":"warn","label":"Ownership","detail":"No approved owner claim yet"},{"status":"info","label":"OpenAgentSkill usage","detail":"No local usage activity yet"},{"status":"info","label":"Agent outcomes","detail":"No agent outcome data yet"}],"strengths":["AI review approved","Install path is available","Repository evidence is available","Recently maintained repository","Large GitHub adoption signal","Install command has no obvious high-risk pattern"],"warnings":["Quality score needs review"],"evidence":{"stars":"9.3K GitHub stars","repoActivity":"9.3K stars, 1.1K forks","lastPushed":"7d since push","license":"MIT","repository":"https://github.com/kangarooking/cangjie-skill/tree/main/books/naval-almanack-skill/peer-selection","install":"npx skills add kangarooking/cangjie-skill --skill peer-selection","installSafety":"standard package or runtime install path","permissionSurface":"no high-risk permission surface in public metadata","documentation":"Strong README/SKILL.md context","agentOutcomes":"No agent outcome data yet"},"installReadiness":{"ready":true,"command":"npx skills add kangarooking/cangjie-skill --skill peer-selection","policy":"agent_install_candidate","label":"Agent install candidate","notes":["Install path is available","Repository evidence is available","License is declared","No Agent Proven outcome evidence yet","7d since push"]},"agentCompatibility":["Codex","Claude Code","Cursor","OpenAgentSkill CLI"],"riskSummary":{"level":"low","label":"Low metadata risk","notes":["Quality score needs 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review"]},"agent_proven":{"version":"agent-proven-v1","score":0,"tier":"unproven","label":"Needs first agent run","summary":"No agent outcome reports yet. Use Resolve, run one narrow sandbox task, then report the result.","metrics":{"totalOutcomes":0,"successfulOutcomes":0,"failedOutcomes":0,"installAttempts":0,"installSuccessRate":null,"successRate":null,"recentSuccessRate":null,"recentFailureRate":null,"riskBlocked":0,"setupRequired":0,"notRelevant":0,"avgOutputQuality":null,"avgTimeToUsefulMs":null,"productionOutcomes":0,"humanReviewRequired":0,"uniqueAgents":0,"lastOutcomeAt":null},"signals":[],"penalties":["No real agent outcome evidence yet"]},"outcome_stats":null,"safety":{"score":79,"level":"review_before_install","label":"Review before install","safety_tier":{"tier":"reviewed","label":"Reviewed","badge":"REVIEWED","summary":"Good audit and safety signals with no high-risk permission hints in public metadata.","recommended_action":"Review the audit page, then allow agent install in a sandboxed workflow.","auto_install_policy":"review","reasons":["Safe-to-try audit","79/100 agent safety score"]},"auto_install_allowed":false,"human_review_required":true,"blocked":false,"audit_risk":"safe_to_try","permission_hints":[{"id":"network","label":"Network access","reason":"Skill likely fetches remote pages, APIs, repositories, or external services.","severity":"medium"}],"policy_warnings":["Quality score needs review"],"constraints_applied":{"max_risk":"medium","needs_install_command":true,"min_stars":0}},"safety_gate":{"tier":"reviewed","label":"Reviewed","badge":"REVIEWED","auto_install_policy":"review","auto_install_allowed":false,"blocked":false,"human_review_required":true,"recommended_action":"Review the audit page, then allow agent install in a sandboxed workflow.","reasons":["Safe-to-try audit","79/100 agent safety score"]},"eval":{"version":"openagentskill-skill-eval-v1","status":"review","score":85,"risk_level":"medium","decision":{"recommendation":"manual_review","reason":"Review the audit page, then allow agent install in a sandboxed workflow.","auto_install_allowed":false,"policy":"review","human_review_required":true},"blockers":[],"warnings":["Task fit: Task fit is weak; compare alternatives before selecting.","Agent safety gate: Good audit and safety signals with no high-risk permission hints in public metadata.","Quality score needs review"],"validation_plan":["Inspect repository, README/SKILL.md, license, and recent commits before production use.","Install in an isolated workspace or sandbox with no production secrets available.","Run the smallest representative task and record files touched, commands run, network access, and outputs.","Compare the selected skill against at least one alternative when the eval status is review or failed.","Promote only after the agent reports a successful verification result and unresolved warnings are accepted."],"checks":[{"id":"task_fit","label":"Task fit","status":"warn","score":70,"required_for_auto_install":true,"detail":"Task fit is weak; compare alternatives before selecting.","evidence":["Evaluate peer-selection before installing it in an agent workflow","automation","Browser automation workflows; Claude Code teams; teams that value GitHub adoption signals"]},{"id":"install_path","label":"Install path","status":"pass","score":92,"required_for_auto_install":true,"detail":"Install handoff is available.","evidence":["npx skills add kangarooking/cangjie-skill --skill peer-selection"]},{"id":"install_safety","label":"Install command safety","status":"pass","score":92,"required_for_auto_install":true,"detail":"standard package or runtime install path","evidence":["npx skills add kangarooking/cangjie-skill --skill peer-selection"]},{"id":"trust_score","label":"Trust score","status":"pass","score":88,"required_for_auto_install":true,"detail":"Strong OpenAgentSkill Trust Score across adoption, recent maintenance, license clarity, documentation, dependency/runtime risk, install safety, permission surface, and install availability.","evidence":["Production candidate","9.3K GitHub stars","MIT"]},{"id":"audit_score","label":"Audit score","status":"pass","score":91,"required_for_auto_install":true,"detail":"Safe to try","evidence":["Quality score needs review"]},{"id":"agent_safety_gate","label":"Agent safety gate","status":"warn","score":79,"required_for_auto_install":true,"detail":"Good audit and safety signals with no high-risk permission hints in public metadata.","evidence":["Review the audit page, then allow agent install in a sandboxed workflow.","Safe-to-try audit"]},{"id":"readme_skillmd_completeness","label":"README/SKILL.md completeness","status":"pass","score":84,"required_for_auto_install":false,"detail":"Metadata includes enough usage and workflow context","evidence":["Strong README/SKILL.md context"]},{"id":"license_clarity","label":"License clarity","status":"pass","score":86,"required_for_auto_install":true,"detail":"MIT","evidence":["MIT"]},{"id":"recent_maintenance","label":"Recent maintenance","status":"pass","score":100,"required_for_auto_install":false,"detail":"7d since push","evidence":["7d since push"]},{"id":"permission_surface","label":"Permission surface","status":"pass","score":100,"required_for_auto_install":true,"detail":"no high-risk permission surface in public metadata","evidence":["Network access: medium"]},{"id":"alternatives","label":"Alternatives available","status":"info","score":55,"required_for_auto_install":false,"detail":"No close alternatives were found in the current shortlist.","evidence":[]}],"endpoints":{"web":"https://www.openagentskill.com/skills/kangarooking-peer-selection/evals","api":"/api/agent/evals?slug=kangarooking-peer-selection","text":"/api/agent/evals?slug=kangarooking-peer-selection&format=text"}},"agent_readable_metadata":{"version":"openagentskill-agent-metadata-v2","skill":{"slug":"kangarooking-peer-selection","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。\n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。\n不适用于: 职场必须共事的同事关系(可先设边界)。\nTriggers: 朋友/圈子/伴侣/该不该疏远/被拖累/五只黑猩猩/peer/friends/circle/values","category":"automation","url":"https://www.openagentskill.com/skills/kangarooking-peer-selection","repository":"https://github.com/kangarooking/cangjie-skill/tree/main/books/naval-almanack-skill/peer-selection","github_repo":"kangarooking/cangjie-skill"},"suited_tasks":["Browser automation workflows","Claude Code teams","teams that value GitHub adoption signals","Navigate pages","Click and type safely","Check visual and DOM state","Run test suites","Capture failures"],"suited_agents":["Codex","Claude Code","Cursor","OpenAgentSkill CLI","CLI"],"install":{"command":"npx skills add kangarooking/cangjie-skill --skill peer-selection","ready":true,"targets":[{"id":"openagentskill-cli","label":"CLI","kind":"command","value":"npx --yes https://github.com/Leon-Drq/openagentskill/releases/download/cli-v0.3.0/openagentskill-0.3.0.tgz add kangarooking-peer-selection"},{"id":"codex","label":"Codex","kind":"agent-prompt","value":"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."},{"id":"claude-code","label":"Claude Code","kind":"agent-prompt","value":"Add \"peer-selection\" as a Claude Code skill from https://github.com/kangarooking/cangjie-skill/tree/main/books/naval-almanack-skill/peer-selection. Inspect the skill instructions, place the reusable skill files in the appropriate local skills location for this project, and report the activation steps. 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\":\"claude-code\",\"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."},{"id":"cursor","label":"Cursor","kind":"agent-prompt","value":"Turn \"peer-selection\" from https://github.com/kangarooking/cangjie-skill/tree/main/books/naval-almanack-skill/peer-selection into a reusable Cursor project rule or agent instruction. Preserve the core workflow, adapt paths to this repo, and keep the rule scoped to tasks where it is relevant. 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\":\"cursor\",\"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."}],"handoff_url":"https://www.openagentskill.com/api/skills/kangarooking-peer-selection/install","manifest_url":"https://www.openagentskill.com/api/registry/manifest/kangarooking-peer-selection"},"trust":{"score":88,"label":"Production candidate","version":"trust-score-v4","install_policy":"agent_install_candidate","evidence":{"stars":"9.3K GitHub stars","repoActivity":"9.3K stars, 1.1K forks","lastPushed":"7d since push","license":"MIT","repository":"https://github.com/kangarooking/cangjie-skill/tree/main/books/naval-almanack-skill/peer-selection","install":"npx skills add kangarooking/cangjie-skill --skill peer-selection","installSafety":"standard package or runtime install path","permissionSurface":"no high-risk permission surface in public metadata","documentation":"Strong README/SKILL.md context","agentOutcomes":"No agent outcome data yet"},"outcome_evidence":{"total":0,"successes":0,"failures":0,"not_relevant":0,"success_rate":null,"recent_success_rate":null,"recent_failure_rate":null,"install_attempts":0,"install_success_rate":null,"risk_blocked":0,"setup_required":0,"avg_output_quality":null,"production_outcomes":0,"last_outcome_at":null,"label":"No agent outcome data yet"},"auto_install":{"allowed":true,"sandbox_required":true,"reason":"Trust Score v4 allows sandbox-first agent installation after normal workspace review."},"best_for":["automation","relationship","happiness","values","community","agent-skill"],"known_risks":["Quality score needs review"]},"agent_proven":{"version":"agent-proven-v1","score":0,"tier":"unproven","label":"Needs first agent run","summary":"No agent outcome reports yet. Use Resolve, run one narrow sandbox task, then report the result.","metrics":{"totalOutcomes":0,"successfulOutcomes":0,"failedOutcomes":0,"installAttempts":0,"installSuccessRate":null,"successRate":null,"recentSuccessRate":null,"recentFailureRate":null,"riskBlocked":0,"setupRequired":0,"notRelevant":0,"avgOutputQuality":null,"avgTimeToUsefulMs":null,"productionOutcomes":0,"humanReviewRequired":0,"uniqueAgents":0,"lastOutcomeAt":null},"signals":[],"penalties":["No real agent outcome evidence yet"]},"audit":{"score":91,"risk_level":"safe_to_try","risk_label":"Safe to try","warnings":["Quality score needs review"]},"safety_gate":{"tier":"reviewed","label":"Reviewed","auto_install_policy":"review","auto_install_allowed":false,"human_review_required":true,"blocked":false,"recommended_action":"Review the audit page, then allow agent install in a sandboxed workflow."},"quality":{"score":91,"label":"Excellent"},"supply":{"track":"Coding and developer agents","scenario":"Testing and QA","maintenance":"7d since push","risk":"Safe to try"},"alternative_skills":[],"do_not_use_when":["teams that need a vendor-supported SLA","high-compliance environments without internal security review","No OpenAgentSkill engagement data yet","Quality score needs review","Production credentials, payments, or irreversible account changes without explicit human review","Sensitive private data before reviewing repository code, license, and permission surface"],"agent_contract":{"task_input":"Use peer-selection in an agent workflow","recommended_action":"Review the audit page, then allow agent install in a sandboxed workflow.","install_policy":"review","minimum_review_before_use":["Trust: 88/100 Production candidate","Audit: 91/100 Safe to try","Safety: 79/100 Review before install","Review repository, license, install command, and permission surface before production use."],"expected_agent_output":{"selected_skill":"kangarooking-peer-selection (peer-selection)","install_command":"npx skills add kangarooking/cangjie-skill --skill peer-selection","risk_summary":"Safe to try; Reviewed; Low metadata risk","verification_result":"Report the smallest successful task, files touched, warnings, and any missing setup."}},"outcome_feedback":{"endpoint":"https://www.openagentskill.com/api/agent/outcome","method":"POST","requires_resolve_event_id":true,"event_id_source":"Use install_receipt.outcome_feedback.event_id or feedback.event_id returned by /api/agent/resolve for the current task.","expected_outcomes":["success","failed","not_relevant","blocked_by_risk","setup_required"],"payload_template":{"event_id":"<install_receipt.outcome_feedback.event_id or feedback.event_id from /api/agent/resolve>","skill_slug":"kangarooking-peer-selection","task":"Use peer-selection in an agent workflow","agent":"codex","outcome":"success","install_used":true,"risk_blocked":false,"setup_required":false,"task_success":true,"output_quality":4,"error_type":null,"human_review_required":false,"workspace":"sandbox","time_to_useful_ms":120000,"notes":"Report the smallest successful task, setup friction, files touched, and risk notes."}},"endpoints":{"web":"https://www.openagentskill.com/skills/kangarooking-peer-selection","api":"https://www.openagentskill.com/api/agent/skills/kangarooking-peer-selection","audit":"https://www.openagentskill.com/skills/kangarooking-peer-selection/audit","eval":"https://www.openagentskill.com/api/agent/evals?slug=kangarooking-peer-selection&task=Use%20peer-selection%20in%20an%20agent%20workflow&max_risk=medium","resolve":"https://www.openagentskill.com/api/agent/resolve?task=Use%20peer-selection%20in%20an%20agent%20workflow&agent=codex&max_risk=medium","receipt":"https://www.openagentskill.com/api/agent/receipt?task=Use%20peer-selection%20in%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text","install":"https://www.openagentskill.com/api/skills/kangarooking-peer-selection/install","manifest":"https://www.openagentskill.com/api/registry/manifest/kangarooking-peer-selection"}},"machine_metadata":{"version":"openagentskill-agent-metadata-v2","skill":{"slug":"kangarooking-peer-selection","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。\n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。\n不适用于: 职场必须共事的同事关系(可先设边界)。\nTriggers: 朋友/圈子/伴侣/该不该疏远/被拖累/五只黑猩猩/peer/friends/circle/values","category":"automation","url":"https://www.openagentskill.com/skills/kangarooking-peer-selection","repository":"https://github.com/kangarooking/cangjie-skill/tree/main/books/naval-almanack-skill/peer-selection","github_repo":"kangarooking/cangjie-skill"},"suited_tasks":["Browser automation workflows","Claude Code teams","teams that value GitHub adoption signals","Navigate pages","Click and type safely","Check visual and DOM state","Run test suites","Capture failures"],"suited_agents":["Codex","Claude Code","Cursor","OpenAgentSkill CLI","CLI"],"install":{"command":"npx skills add kangarooking/cangjie-skill --skill peer-selection","ready":true,"targets":[{"id":"openagentskill-cli","label":"CLI","kind":"command","value":"npx --yes https://github.com/Leon-Drq/openagentskill/releases/download/cli-v0.3.0/openagentskill-0.3.0.tgz add kangarooking-peer-selection"},{"id":"codex","label":"Codex","kind":"agent-prompt","value":"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."},{"id":"claude-code","label":"Claude Code","kind":"agent-prompt","value":"Add \"peer-selection\" as a Claude Code skill from https://github.com/kangarooking/cangjie-skill/tree/main/books/naval-almanack-skill/peer-selection. Inspect the skill instructions, place the reusable skill files in the appropriate local skills location for this project, and report the activation steps. 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\":\"claude-code\",\"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."},{"id":"cursor","label":"Cursor","kind":"agent-prompt","value":"Turn \"peer-selection\" from https://github.com/kangarooking/cangjie-skill/tree/main/books/naval-almanack-skill/peer-selection into a reusable Cursor project rule or agent instruction. Preserve the core workflow, adapt paths to this repo, and keep the rule scoped to tasks where it is relevant. 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\":\"cursor\",\"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."}],"handoff_url":"https://www.openagentskill.com/api/skills/kangarooking-peer-selection/install","manifest_url":"https://www.openagentskill.com/api/registry/manifest/kangarooking-peer-selection"},"trust":{"score":88,"label":"Production candidate","version":"trust-score-v4","install_policy":"agent_install_candidate","evidence":{"stars":"9.3K GitHub stars","repoActivity":"9.3K stars, 1.1K forks","lastPushed":"7d since push","license":"MIT","repository":"https://github.com/kangarooking/cangjie-skill/tree/main/books/naval-almanack-skill/peer-selection","install":"npx skills add kangarooking/cangjie-skill --skill peer-selection","installSafety":"standard package or runtime install path","permissionSurface":"no high-risk permission surface in public metadata","documentation":"Strong README/SKILL.md context","agentOutcomes":"No agent outcome data yet"},"outcome_evidence":{"total":0,"successes":0,"failures":0,"not_relevant":0,"success_rate":null,"recent_success_rate":null,"recent_failure_rate":null,"install_attempts":0,"install_success_rate":null,"risk_blocked":0,"setup_required":0,"avg_output_quality":null,"production_outcomes":0,"last_outcome_at":null,"label":"No agent outcome data yet"},"auto_install":{"allowed":true,"sandbox_required":true,"reason":"Trust Score v4 allows sandbox-first agent installation after normal workspace review."},"best_for":["automation","relationship","happiness","values","community","agent-skill"],"known_risks":["Quality score needs review"]},"agent_proven":{"version":"agent-proven-v1","score":0,"tier":"unproven","label":"Needs first agent run","summary":"No agent outcome reports yet. Use Resolve, run one narrow sandbox task, then report the result.","metrics":{"totalOutcomes":0,"successfulOutcomes":0,"failedOutcomes":0,"installAttempts":0,"installSuccessRate":null,"successRate":null,"recentSuccessRate":null,"recentFailureRate":null,"riskBlocked":0,"setupRequired":0,"notRelevant":0,"avgOutputQuality":null,"avgTimeToUsefulMs":null,"productionOutcomes":0,"humanReviewRequired":0,"uniqueAgents":0,"lastOutcomeAt":null},"signals":[],"penalties":["No real agent outcome evidence yet"]},"audit":{"score":91,"risk_level":"safe_to_try","risk_label":"Safe to try","warnings":["Quality score needs review"]},"safety_gate":{"tier":"reviewed","label":"Reviewed","auto_install_policy":"review","auto_install_allowed":false,"human_review_required":true,"blocked":false,"recommended_action":"Review the audit page, then allow agent install in a sandboxed workflow."},"quality":{"score":91,"label":"Excellent"},"supply":{"track":"Coding and developer agents","scenario":"Testing and QA","maintenance":"7d since push","risk":"Safe to try"},"alternative_skills":[],"do_not_use_when":["teams that need a vendor-supported SLA","high-compliance environments without internal security review","No OpenAgentSkill engagement data yet","Quality score needs review","Production credentials, payments, or irreversible account changes without explicit human review","Sensitive private data before reviewing repository code, license, and permission surface"],"agent_contract":{"task_input":"Use peer-selection in an agent workflow","recommended_action":"Review the audit page, then allow agent install in a sandboxed workflow.","install_policy":"review","minimum_review_before_use":["Trust: 88/100 Production candidate","Audit: 91/100 Safe to try","Safety: 79/100 Review before install","Review repository, license, install command, and permission surface before production use."],"expected_agent_output":{"selected_skill":"kangarooking-peer-selection (peer-selection)","install_command":"npx skills add kangarooking/cangjie-skill --skill peer-selection","risk_summary":"Safe to try; Reviewed; Low metadata risk","verification_result":"Report the smallest successful task, files touched, warnings, and any missing setup."}},"outcome_feedback":{"endpoint":"https://www.openagentskill.com/api/agent/outcome","method":"POST","requires_resolve_event_id":true,"event_id_source":"Use install_receipt.outcome_feedback.event_id or feedback.event_id returned by /api/agent/resolve for the current task.","expected_outcomes":["success","failed","not_relevant","blocked_by_risk","setup_required"],"payload_template":{"event_id":"<install_receipt.outcome_feedback.event_id or feedback.event_id from /api/agent/resolve>","skill_slug":"kangarooking-peer-selection","task":"Use peer-selection in an agent workflow","agent":"codex","outcome":"success","install_used":true,"risk_blocked":false,"setup_required":false,"task_success":true,"output_quality":4,"error_type":null,"human_review_required":false,"workspace":"sandbox","time_to_useful_ms":120000,"notes":"Report the smallest successful task, setup friction, files touched, and risk notes."}},"endpoints":{"web":"https://www.openagentskill.com/skills/kangarooking-peer-selection","api":"https://www.openagentskill.com/api/agent/skills/kangarooking-peer-selection","audit":"https://www.openagentskill.com/skills/kangarooking-peer-selection/audit","eval":"https://www.openagentskill.com/api/agent/evals?slug=kangarooking-peer-selection&task=Use%20peer-selection%20in%20an%20agent%20workflow&max_risk=medium","resolve":"https://www.openagentskill.com/api/agent/resolve?task=Use%20peer-selection%20in%20an%20agent%20workflow&agent=codex&max_risk=medium","receipt":"https://www.openagentskill.com/api/agent/receipt?task=Use%20peer-selection%20in%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text","install":"https://www.openagentskill.com/api/skills/kangarooking-peer-selection/install","manifest":"https://www.openagentskill.com/api/registry/manifest/kangarooking-peer-selection"}},"supply_profile":{"track":{"slug":"coding","label":"Coding and developer agents","shortLabel":"Coding","description":"Code review, repo analysis, testing, CI, GitHub, DevOps, and developer workflow skills."},"scenario":{"label":"Testing and QA","description":"I need my agent to test a web app, reproduce bugs, and verify fixes.","useCases":[{"slug":"browser-automation","title":"Browser automation"},{"slug":"testing-qa","title":"Testing and QA"},{"slug":"local-desktop","title":"Local desktop"}]},"applicableAgents":["Claude Code","CLI","Codex","Cursor"],"install":{"ready":true,"command":"npx skills add kangarooking/cangjie-skill --skill peer-selection","primaryTarget":"CLI","targetCount":4},"githubQuality":{"stars":9334,"starsLabel":"9.3K","forks":1079,"license":"MIT","qualityScore":91,"trustScore":88,"auditScore":91},"maintenance":{"status":"fresh","label":"7d since push","daysSincePush":7,"lastPushedAt":"2026-08-30T02:37:57+00:00"},"risk":{"level":"safe_to_try","label":"Safe to try","requiresReview":true,"notes":["Quality score needs review"]},"coverageTags":["Coding","Testing and QA","automation","relationship","happiness","values","community","agent-skill"]},"audit":{"audit_score":91,"risk_level":"safe_to_try","risk_label":"Safe to try","quality_score":91,"trust_score":88,"maintenance_score":100,"security_score":89,"install_score":92,"warnings":["Quality score needs review"]},"quality_signals":{"model":"v2","star_score":27.79,"usage_score":0,"review_score":5.1,"metadata_score":7,"freshness_score":15},"platforms":["Claude Code"],"use_cases":[{"slug":"browser-automation","title":"Browser automation","url":"https://www.openagentskill.com/use-cases/browser-automation"},{"slug":"testing-qa","title":"Testing and QA","url":"https://www.openagentskill.com/use-cases/testing-qa"},{"slug":"local-desktop","title":"Local desktop","url":"https://www.openagentskill.com/use-cases/local-desktop"},{"slug":"research-agents","title":"Research agents","url":"https://www.openagentskill.com/use-cases/research-agents"}],"stacks":[{"slug":"browser-qa-agent","title":"Browser QA agent","url":"https://www.openagentskill.com/collections/browser-qa-agent"},{"slug":"content-growth-agent","title":"Content growth agent","url":"https://www.openagentskill.com/collections/content-growth-agent"},{"slug":"research-report-agent","title":"Research report agent","url":"https://www.openagentskill.com/collections/research-report-agent"}],"install":"npx skills add kangarooking/cangjie-skill --skill peer-selection","install_targets":[{"id":"openagentskill-cli","label":"CLI","title":"OpenAgentSkill CLI","kind":"command","value":"npx --yes https://github.com/Leon-Drq/openagentskill/releases/download/cli-v0.3.0/openagentskill-0.3.0.tgz add kangarooking-peer-selection","description":"Resolve policy, run the source installer safely, and report a verified install receipt.","copyLabel":"Copy command"},{"id":"codex","label":"Codex","title":"Codex install prompt","kind":"agent-prompt","value":"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.","description":"Give Codex a repo-aware install prompt when the skill is not available through a local CLI.","copyLabel":"Copy prompt"},{"id":"claude-code","label":"Claude Code","title":"Claude Code skill prompt","kind":"agent-prompt","value":"Add \"peer-selection\" as a Claude Code skill from https://github.com/kangarooking/cangjie-skill/tree/main/books/naval-almanack-skill/peer-selection. Inspect the skill instructions, place the reusable skill files in the appropriate local skills location for this project, and report the activation steps. 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\":\"claude-code\",\"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.","description":"Use this prompt to ask Claude Code to add the skill and explain the local activation steps.","copyLabel":"Copy prompt"},{"id":"cursor","label":"Cursor","title":"Cursor rule prompt","kind":"agent-prompt","value":"Turn \"peer-selection\" from https://github.com/kangarooking/cangjie-skill/tree/main/books/naval-almanack-skill/peer-selection into a reusable Cursor project rule or agent instruction. Preserve the core workflow, adapt paths to this repo, and keep the rule scoped to tasks where it is relevant. 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\":\"cursor\",\"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.","description":"Use this when installing as Cursor project rules or reusable agent instructions.","copyLabel":"Copy prompt"}],"repository":"https://github.com/kangarooking/cangjie-skill/tree/main/books/naval-almanack-skill/peer-selection","github_repo":"kangarooking/cangjie-skill","version":"1.0.0","license":"MIT","urls":{"web":"https://www.openagentskill.com/skills/kangarooking-peer-selection","repository":"https://github.com/kangarooking/cangjie-skill/tree/main/books/naval-almanack-skill/peer-selection","api":"/api/agent/skills/kangarooking-peer-selection","install_api":"/api/skills/kangarooking-peer-selection/install"},"meta":{"created_at":"2026-09-01T19:12:29.1238+00:00","updated_at":"2026-09-01T19:12:29.177872+00:00","agent_friendly":true}}