[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6DSHEZ9KP261D508PDJD0YM":3,"skill-same:01M6DSHEZ9KP261D508PDJD0YM":99},{"skillNo":4,"name":5,"nameZh":6,"description":7,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":16,"categories":17,"keywords":31,"publishedAt":42,"linkOnly":43,"markdownContent":44,"markdownBody":45,"frontMatter":46,"refName":47,"commitSha":48,"skillDirectory":49,"forksCount":50,"repositoryHtmlUrl":51,"repositoryHomepageUrl":6,"ownerHtmlUrl":52,"ownerBlogUrl":6,"ownerDescription":6,"updatedAt":53,"install":54,"resources":67},"01M6DSHEZ9KP261D508PDJD0YM","product-analytics",null,"Use when defining product KPIs, building metric dashboards, running cohort or retention analysis, or interpreting feature adoption trends across product stages.","zhangzhang-111-i\u002Fclaude-skills111","zhangzhang-111-i","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F251344927?v=4","01M6DRBP4NCM1ZCHTT0FW0SQHD","lixiying","01M6DRBPAMFDJSGQ69XPK9KM9J",4,"MIT","https:\u002F\u002Fgithub.com\u002Fzhangzhang-111-i\u002Fclaude-skills111\u002Fblob\u002Fmain\u002Fproduct-team\u002Fproduct-analytics\u002FSKILL.md",[18,23,28],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000013","分析与可视化","SCENARIO","使用场景",{"categoryNo":24,"categoryName":25,"taxonomyType":26,"taxonomyTypeDesc":27},"01JBSEEDCAT000000000000031","产品经理","PROFESSION","适用职业",{"categoryNo":29,"categoryName":30,"taxonomyType":26,"taxonomyTypeDesc":27},"01JBSEEDCAT000000000000033","数据分析师",[32,33,34,35,36,37,38,39,40,41],"analytics","product","product analytics","adoption","analysis","dashboards","cohort","use","across","feature","2026-11-10 10:12:30",false,"---\nname: product-analytics\ndescription: Use when defining product KPIs, building metric dashboards, running cohort or retention analysis, or interpreting feature adoption trends across product stages.\n---\n\n# Product Analytics\n\nDefine, track, and interpret product metrics across discovery, growth, and mature product stages.\n\n## When To Use\n\nUse this skill for:\n- Metric framework selection (AARRR, North Star, HEART)\n- KPI definition by product stage (pre-PMF, growth, mature)\n- Dashboard design and metric hierarchy\n- Cohort and retention analysis\n- Feature adoption and funnel interpretation\n\n## Workflow\n\n1. Select metric framework\n- AARRR for growth loops and funnel visibility\n- North Star for cross-functional strategic alignment\n- HEART for UX quality and user experience measurement\n\n2. Define stage-appropriate KPIs\n- Pre-PMF: activation, early retention, qualitative success\n- Growth: acquisition efficiency, expansion, conversion velocity\n- Mature: retention depth, revenue quality, operational efficiency\n\n3. Design dashboard layers\n- Executive layer: 5-7 directional metrics\n- Product health layer: acquisition, activation, retention, engagement\n- Feature layer: adoption, depth, repeat usage, outcome correlation\n\n4. Run cohort + retention analysis\n- Segment by signup cohort or feature exposure cohort\n- Compare retention curves, not single-point snapshots\n- Identify inflection points around onboarding and first value moment\n\n5. Interpret and act\n- Connect metric movement to product changes and release timeline\n- Distinguish signal from noise using period-over-period context\n- Propose one clear product action per major metric risk\u002Fopportunity\n\n## KPI Guidance By Stage\n\n### Pre-PMF\n- Activation rate\n- Week-1 retention\n- Time-to-first-value\n- Problem-solution fit interview score\n\n### Growth\n- Funnel conversion by stage\n- Monthly retained users\n- Feature adoption among new cohorts\n- Expansion \u002F upsell proxy metrics\n\n### Mature\n- Net revenue retention aligned product metrics\n- Power-user share and depth of use\n- Churn risk indicators by segment\n- Reliability and support-deflection product metrics\n\n## Dashboard Design Principles\n\n- Show trends, not isolated point estimates.\n- Keep one owner per KPI.\n- Pair each KPI with target, threshold, and decision rule.\n- Use cohort and segment filters by default.\n- Prefer comparable time windows (weekly vs weekly, monthly vs monthly).\n\nSee:\n- `references\u002Fmetrics-frameworks.md`\n- `references\u002Fdashboard-templates.md`\n\n## Cohort Analysis Method\n\n1. Define cohort anchor event (signup, activation, first purchase).\n2. Define retained behavior (active day, key action, repeat session).\n3. Build retention matrix by cohort week\u002Fmonth and age period.\n4. Compare curve shape across cohorts.\n5. Flag early drop points and investigate journey friction.\n\n## Retention Curve Interpretation\n\n- Sharp early drop, low plateau: onboarding mismatch or weak initial value.\n- Moderate drop, stable plateau: healthy core audience with predictable churn.\n- Flattening at low level: product used occasionally, revisit value metric.\n- Improving newer cohorts: onboarding or positioning improvements are working.\n\n## Tooling\n\n### `scripts\u002Fmetrics_calculator.py`\n\nCLI utility for:\n- Retention rate calculations by cohort age\n- Cohort table generation\n- Basic funnel conversion analysis\n\nExamples:\n```bash\npython3 scripts\u002Fmetrics_calculator.py retention events.csv\npython3 scripts\u002Fmetrics_calculator.py cohort events.csv --cohort-grain month\npython3 scripts\u002Fmetrics_calculator.py funnel funnel.csv --stages visit,signup,activate,pay\n```\n","# Product Analytics\n\nDefine, track, and interpret product metrics across discovery, growth, and mature product stages.\n\n## When To Use\n\nUse this skill for:\n- Metric framework selection (AARRR, North Star, HEART)\n- KPI definition by product stage (pre-PMF, growth, mature)\n- Dashboard design and metric hierarchy\n- Cohort and retention analysis\n- Feature adoption and funnel interpretation\n\n## Workflow\n\n1. Select metric framework\n- AARRR for growth loops and funnel visibility\n- North Star for cross-functional strategic alignment\n- HEART for UX quality and user experience measurement\n\n2. Define stage-appropriate KPIs\n- Pre-PMF: activation, early retention, qualitative success\n- Growth: acquisition efficiency, expansion, conversion velocity\n- Mature: retention depth, revenue quality, operational efficiency\n\n3. Design dashboard layers\n- Executive layer: 5-7 directional metrics\n- Product health layer: acquisition, activation, retention, engagement\n- Feature layer: adoption, depth, repeat usage, outcome correlation\n\n4. Run cohort + retention analysis\n- Segment by signup cohort or feature exposure cohort\n- Compare retention curves, not single-point snapshots\n- Identify inflection points around onboarding and first value moment\n\n5. Interpret and act\n- Connect metric movement to product changes and release timeline\n- Distinguish signal from noise using period-over-period context\n- Propose one clear product action per major metric risk\u002Fopportunity\n\n## KPI Guidance By Stage\n\n### Pre-PMF\n- Activation rate\n- Week-1 retention\n- Time-to-first-value\n- Problem-solution fit interview score\n\n### Growth\n- Funnel conversion by stage\n- Monthly retained users\n- Feature adoption among new cohorts\n- Expansion \u002F upsell proxy metrics\n\n### Mature\n- Net revenue retention aligned product metrics\n- Power-user share and depth of use\n- Churn risk indicators by segment\n- Reliability and support-deflection product metrics\n\n## Dashboard Design Principles\n\n- Show trends, not isolated point estimates.\n- Keep one owner per KPI.\n- Pair each KPI with target, threshold, and decision rule.\n- Use cohort and segment filters by default.\n- Prefer comparable time windows (weekly vs weekly, monthly vs monthly).\n\nSee:\n- `references\u002Fmetrics-frameworks.md`\n- `references\u002Fdashboard-templates.md`\n\n## Cohort Analysis Method\n\n1. Define cohort anchor event (signup, activation, first purchase).\n2. Define retained behavior (active day, key action, repeat session).\n3. Build retention matrix by cohort week\u002Fmonth and age period.\n4. Compare curve shape across cohorts.\n5. Flag early drop points and investigate journey friction.\n\n## Retention Curve Interpretation\n\n- Sharp early drop, low plateau: onboarding mismatch or weak initial value.\n- Moderate drop, stable plateau: healthy core audience with predictable churn.\n- Flattening at low level: product used occasionally, revisit value metric.\n- Improving newer cohorts: onboarding or positioning improvements are working.\n\n## Tooling\n\n### `scripts\u002Fmetrics_calculator.py`\n\nCLI utility for:\n- Retention rate calculations by cohort age\n- Cohort table generation\n- Basic funnel conversion analysis\n\nExamples:\n```bash\npython3 scripts\u002Fmetrics_calculator.py retention events.csv\npython3 scripts\u002Fmetrics_calculator.py cohort events.csv --cohort-grain month\npython3 scripts\u002Fmetrics_calculator.py funnel funnel.csv --stages visit,signup,activate,pay\n```\n",{"name":5,"description":7},"main","c0a12fc98d85642fa8893e31fc5cf5dfad879de6","product-team\u002Fproduct-analytics",0,"https:\u002F\u002Fgithub.com\u002Fzhangzhang-111-i\u002Fclaude-skills111","https:\u002F\u002Fgithub.com\u002Fzhangzhang-111-i","2026-03-13 21:49:18",{"source":8,"skillName":5,"commands":55,"prompt":65,"zipAvailable":66},[56,59,62],{"tool":57,"command":58},"npx","npx skills add zhangzhang-111-i\u002Fclaude-skills111 --skill product-analytics",{"tool":60,"command":61},"bunx","bunx skills add zhangzhang-111-i\u002Fclaude-skills111 --skill product-analytics",{"tool":63,"command":64},"pnpm","pnpm dlx skills add zhangzhang-111-i\u002Fclaude-skills111 --skill product-analytics","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fzhangzhang-111-i\u002Fclaude-skills111\u002Fblob\u002Fmain\u002Fproduct-team\u002Fproduct-analytics\u002FSKILL.md",true,[68,73,76,79,82,86,90,96],{"path":69,"resourceType":70,"resourceTypeDesc":71,"sizeBytes":50,"sourceHtmlUrl":72},"agent-prompt.md","REFERENCE","参考文档","https:\u002F\u002Fgithub.com\u002Fhefarica\u002Farbitragex-v2\u002Fblob\u002Fmain\u002F.claude\u002Fagents\u002Fskills\u002F05-initial-snapshot-live-update-engineer\u002Fagent-prompt.md",{"path":74,"resourceType":70,"resourceTypeDesc":71,"sizeBytes":50,"sourceHtmlUrl":75},"anti-patterns.md","https:\u002F\u002Fgithub.com\u002Fhefarica\u002Farbitragex-v2\u002Fblob\u002Fmain\u002F.claude\u002Fagents\u002Fskills\u002F05-initial-snapshot-live-update-engineer\u002Fanti-patterns.md",{"path":77,"resourceType":70,"resourceTypeDesc":71,"sizeBytes":50,"sourceHtmlUrl":78},"checklist.md","https:\u002F\u002Fgithub.com\u002Fhefarica\u002Farbitragex-v2\u002Fblob\u002Fmain\u002F.claude\u002Fagents\u002Fskills\u002F05-initial-snapshot-live-update-engineer\u002Fchecklist.md",{"path":80,"resourceType":70,"resourceTypeDesc":71,"sizeBytes":50,"sourceHtmlUrl":81},"implementation-patterns.md","https:\u002F\u002Fgithub.com\u002Fhefarica\u002Farbitragex-v2\u002Fblob\u002Fmain\u002F.claude\u002Fagents\u002Fskills\u002F05-initial-snapshot-live-update-engineer\u002Fimplementation-patterns.md",{"path":83,"resourceType":70,"resourceTypeDesc":71,"sizeBytes":84,"sourceHtmlUrl":85},"references\u002Fdashboard-templates.md",2014,"https:\u002F\u002Fgithub.com\u002Fzhangzhang-111-i\u002Fclaude-skills111\u002Fblob\u002Fmain\u002Fproduct-team\u002Fproduct-analytics\u002Freferences\u002Fdashboard-templates.md",{"path":87,"resourceType":70,"resourceTypeDesc":71,"sizeBytes":88,"sourceHtmlUrl":89},"references\u002Fmetrics-frameworks.md",2425,"https:\u002F\u002Fgithub.com\u002Fzhangzhang-111-i\u002Fclaude-skills111\u002Fblob\u002Fmain\u002Fproduct-team\u002Fproduct-analytics\u002Freferences\u002Fmetrics-frameworks.md",{"path":91,"resourceType":92,"resourceTypeDesc":93,"sizeBytes":94,"sourceHtmlUrl":95},"scripts\u002Fmetrics_calculator.py","SCRIPT","脚本",5503,"https:\u002F\u002Fgithub.com\u002Fzhangzhang-111-i\u002Fclaude-skills111\u002Fblob\u002Fmain\u002Fproduct-team\u002Fproduct-analytics\u002Fscripts\u002Fmetrics_calculator.py",{"path":97,"resourceType":70,"resourceTypeDesc":71,"sizeBytes":50,"sourceHtmlUrl":98},"validation.md","https:\u002F\u002Fgithub.com\u002Fhefarica\u002Farbitragex-v2\u002Fblob\u002Fmain\u002F.claude\u002Fagents\u002Fskills\u002F05-initial-snapshot-live-update-engineer\u002Fvalidation.md",[100,124,149,176,196,219],{"skillNo":101,"name":102,"nameZh":6,"description":103,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":104,"categories":105,"keywords":106,"publishedAt":42},"01M6DSNYM8PZKEXGYMRX53PVPH","risk-management-specialist","Medical device risk management specialist implementing ISO 14971 throughout product lifecycle. Provides risk analysis, risk evaluation, risk control, and post-production information analysis. Use when user mentions risk management, ISO 14971, risk analysis, FMEA, fault tree analysis, hazard identification, risk control, risk matrix, benefit-risk analysis, residual risk, risk acceptability, or post-market risk.","https:\u002F\u002Fgithub.com\u002Fzhangzhang-111-i\u002Fclaude-skills111\u002Fblob\u002Fmain\u002Fra-qm-team\u002Frisk-management-specialist\u002FSKILL.md",[],[107,108,109,110,111,112,33,113,114,115,36,116,39,117,118,119,120,121,122,123],"risk","risk management specialist","management","risk management","risk analysis","risk evaluation","Evaluation","Production","lifecycle","user","risk matrix","Market","device","control","iso","medical","iso 14971",{"skillNo":125,"name":126,"nameZh":6,"description":127,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":128,"categories":129,"keywords":130,"publishedAt":42},"01M6DSNSRBGVZWS23TK0ZQ52QC","regulatory-affairs-head","Senior Regulatory Affairs Manager for HealthTech and MedTech companies. Prepares FDA 510(k), De Novo, and PMA submission packages; analyzes regulatory pathways for new medical devices; drafts responses to FDA deficiency letters and Notified Body queries; develops CE marking technical documentation under EU MDR 2017\u002F745; coordinates multi-market approval strategies across FDA, EU, Health Canada, PMDA, and NMPA; and maintains regulatory intelligence on evolving standards. Use when users need to plan or execute FDA submissions, navigate 510(k) or PMA approval processes, achieve CE marking, prepare pre-submission meeting materials, write regulatory strategy documents, respond to agency queries, or manage compliance documentation for medical device market access.","https:\u002F\u002Fgithub.com\u002Fzhangzhang-111-i\u002Fclaude-skills111\u002Fblob\u002Fmain\u002Fra-qm-team\u002Fregulatory-affairs-head\u002FSKILL.md",[],[131,132,133,134,135,136,137,138,139,140,141,142,143,144,145,146,40,147,122,148],"regulatory affairs head","regulatory","head","documentation","documents","packages","planning","devices","plan","access","write","strategy","evidence","standards","manage","intelligence","strategies","clinical",{"skillNo":150,"name":151,"nameZh":6,"description":152,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":153,"categories":154,"keywords":161,"publishedAt":42},"01M6DSNN7GNR2HZE66S4D31EP8","quality-manager-qms-iso13485","ISO 13485 Quality Management System implementation and maintenance for medical device organizations. Provides QMS design, documentation control, internal auditing, CAPA management, and certification support. Use when working with medical device quality systems, preparing for ISO 13485 audits, managing regulatory compliance documentation, setting up corrective actions, or building audit preparation programs. Useful for quality management, audit preparation, regulatory compliance, medical device documentation, and corrective action workflows.","https:\u002F\u002Fgithub.com\u002Fzhangzhang-111-i\u002Fclaude-skills111\u002Fblob\u002Fmain\u002Fra-qm-team\u002Fquality-manager-qms-iso13485\u002FSKILL.md",[155,158],{"categoryNo":156,"categoryName":157,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000015","视觉设计",{"categoryNo":159,"categoryName":160,"taxonomyType":26,"taxonomyTypeDesc":27},"01JBSEEDCAT000000000000032","设计师",[162,163,164,165,166,167,134,168,169,170,171,172,39,132,173,174,175,120,121,122],"quality manager qms iso13485","quality","design","review","support","workflows","audit","actions","compliance","system","process","up","maintenance","document",{"skillNo":177,"name":178,"nameZh":6,"description":179,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":180,"categories":181,"keywords":185,"publishedAt":42},"01M6DSNE5PQM106PM4EDGPBWGZ","quality-manager-qmr","Senior Quality Manager Responsible Person (QMR) for HealthTech and MedTech companies. Provides quality system governance, management review leadership, regulatory compliance oversight, and quality performance monitoring per ISO 13485 Clause 5.5.2.","https:\u002F\u002Fgithub.com\u002Fzhangzhang-111-i\u002Fclaude-skills111\u002Fblob\u002Fmain\u002Fra-qm-team\u002Fquality-manager-qmr\u002FSKILL.md",[182],{"categoryNo":183,"categoryName":184,"taxonomyType":26,"taxonomyTypeDesc":27},"01JBSEEDCAT000000000000037","律师与法务",[186,163,165,187,188,189,190,170,191,171,109,192,132,193,194,195,121],"quality manager qmr","policy","performance","governance","monitoring","regulatory compliance","oversight","cost","culture","leadership",{"skillNo":197,"name":198,"nameZh":6,"description":199,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":200,"categories":201,"keywords":206,"publishedAt":42},"01M6DSN7MYXB6X42TB1GH2TNSB","quality-documentation-manager","Document control system management for medical device QMS. Covers document numbering, version control, change management, and 21 CFR Part 11 compliance. Use for document control procedures, change control workflow, document numbering, version management, electronic signature compliance, or regulatory documentation review.","https:\u002F\u002Fgithub.com\u002Fzhangzhang-111-i\u002Fclaude-skills111\u002Fblob\u002Fmain\u002Fra-qm-team\u002Fquality-documentation-manager\u002FSKILL.md",[202,205],{"categoryNo":203,"categoryName":204,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000002","文档处理",{"categoryNo":183,"categoryName":184,"taxonomyType":26,"taxonomyTypeDesc":27},[134,207,163,165,208,209,168,115,210,171,211,212,39,213,214,215,122,216,217,218],"quality documentation manager","workflow","change","document lifecycle","change management","list","master","system management","documentation review","cfr","21 cfr part 11","change control",{"skillNo":220,"name":221,"nameZh":6,"description":222,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":223,"categories":224,"keywords":225,"publishedAt":42},"01M6DSN3R749H3R20K15QE8X8W","qms-audit-expert","ISO 13485 internal audit expertise for medical device QMS. Covers audit planning, execution, nonconformity classification, and CAPA verification. Use for internal audit planning, audit execution, finding classification, external audit preparation, or audit program management.","https:\u002F\u002Fgithub.com\u002Fzhangzhang-111-i\u002Fclaude-skills111\u002Fblob\u002Fmain\u002Fra-qm-team\u002Fqms-audit-expert\u002FSKILL.md",[],[168,226,227,137,228,229,230,231,109,39,232,119,121,122],"qms audit expert","expert","verification","execution","classification","schedule","checklist"]