[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6DSGCCB0RFSEG4Q8RMSN329":3,"skill-same:01M6DSGCCB0RFSEG4Q8RMSN329":116},{"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":28,"publishedAt":49,"linkOnly":50,"markdownContent":51,"markdownBody":52,"frontMatter":53,"refName":65,"commitSha":66,"skillDirectory":67,"forksCount":68,"repositoryHtmlUrl":69,"repositoryHomepageUrl":6,"ownerHtmlUrl":70,"ownerBlogUrl":6,"ownerDescription":6,"updatedAt":71,"install":72,"resources":85},"01M6DSGCCB0RFSEG4Q8RMSN329","social-media-analyzer",null,"Social media campaign analysis and performance tracking. Calculates engagement rates, ROI, and benchmarks across platforms. Use for analyzing social media performance, calculating engagement rate, measuring campaign ROI, comparing platform metrics, or benchmarking against industry standards.","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\u002Fmarketing-skill\u002Fsocial-media-analyzer\u002FSKILL.md",[18,23],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000019","营销推广","SCENARIO","使用场景",{"categoryNo":24,"categoryName":25,"taxonomyType":26,"taxonomyTypeDesc":27},"01JBSEEDCAT000000000000035","市场营销","PROFESSION","适用职业",[29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48],"Media","social","social media","social media analyzer","use","platform","across","performance tracking","facebook","tiktok","benchmarks","standards","campaign","performance","linkedin engagement","instagram","linkedin","analyze","analysis","roi","2026-11-10 10:12:30",false,"---\nname: \"social-media-analyzer\"\ndescription: Social media campaign analysis and performance tracking. Calculates engagement rates, ROI, and benchmarks across platforms. Use for analyzing social media performance, calculating engagement rate, measuring campaign ROI, comparing platform metrics, or benchmarking against industry standards.\ntriggers:\n  - analyze social media\n  - calculate engagement rate\n  - social media ROI\n  - campaign performance\n  - compare platforms\n  - benchmark engagement\n  - Instagram analytics\n  - Facebook metrics\n  - TikTok performance\n  - LinkedIn engagement\n---\n\n# Social Media Analyzer\n\nCampaign performance analysis with engagement metrics, ROI calculations, and platform benchmarks.\n\n---\n\n## Table of Contents\n\n- [Analysis Workflow](#analysis-workflow)\n- [Engagement Metrics](#engagement-metrics)\n- [ROI Calculation](#roi-calculation)\n- [Platform Benchmarks](#platform-benchmarks)\n- [Tools](#tools)\n- [Examples](#examples)\n\n---\n\n## Analysis Workflow\n\nAnalyze social media campaign performance:\n\n1. Validate input data completeness (reach > 0, dates valid)\n2. Calculate engagement metrics per post\n3. Aggregate campaign-level metrics\n4. Calculate ROI if ad spend provided\n5. Compare against platform benchmarks\n6. Identify top and bottom performers\n7. Generate recommendations\n8. **Validation:** Engagement rate \u003C 100%, ROI matches spend data\n\n### Input Requirements\n\n| Field | Required | Description |\n|-------|----------|-------------|\n| platform | Yes | instagram, facebook, twitter, linkedin, tiktok |\n| posts[] | Yes | Array of post data |\n| posts[].likes | Yes | Like\u002Freaction count |\n| posts[].comments | Yes | Comment count |\n| posts[].reach | Yes | Unique users reached |\n| posts[].impressions | No | Total views |\n| posts[].shares | No | Share\u002Fretweet count |\n| posts[].saves | No | Save\u002Fbookmark count |\n| posts[].clicks | No | Link clicks |\n| total_spend | No | Ad spend (for ROI) |\n\n### Data Validation Checks\n\nBefore analysis, verify:\n\n- [ ] Reach > 0 for all posts (avoid division by zero)\n- [ ] Engagement counts are non-negative\n- [ ] Date range is valid (start \u003C end)\n- [ ] Platform is recognized\n- [ ] Spend > 0 if ROI requested\n\n---\n\n## Engagement Metrics\n\n### Engagement Rate Calculation\n\n```\nEngagement Rate = (Likes + Comments + Shares + Saves) \u002F Reach × 100\n```\n\n### Metric Definitions\n\n| Metric | Formula | Interpretation |\n|--------|---------|----------------|\n| Engagement Rate | Engagements \u002F Reach × 100 | Audience interaction level |\n| CTR | Clicks \u002F Impressions × 100 | Content click appeal |\n| Reach Rate | Reach \u002F Followers × 100 | Content distribution |\n| Virality Rate | Shares \u002F Impressions × 100 | Share-worthiness |\n| Save Rate | Saves \u002F Reach × 100 | Content value |\n\n### Performance Categories\n\n| Rating | Engagement Rate | Action |\n|--------|-----------------|--------|\n| Excellent | > 6% | Scale and replicate |\n| Good | 3-6% | Optimize and expand |\n| Average | 1-3% | Test improvements |\n| Poor | \u003C 1% | Analyze and pivot |\n\n---\n\n## ROI Calculation\n\nCalculate return on ad spend:\n\n1. Sum total engagements across posts\n2. Calculate cost per engagement (CPE)\n3. Calculate cost per click (CPC) if clicks available\n4. Estimate engagement value using benchmark rates\n5. Calculate ROI percentage\n6. **Validation:** ROI = (Value - Spend) \u002F Spend × 100\n\n### ROI Formulas\n\n| Metric | Formula |\n|--------|---------|\n| Cost Per Engagement (CPE) | Total Spend \u002F Total Engagements |\n| Cost Per Click (CPC) | Total Spend \u002F Total Clicks |\n| Cost Per Thousand (CPM) | (Spend \u002F Impressions) × 1000 |\n| Return on Ad Spend (ROAS) | Revenue \u002F Ad Spend |\n\n### Engagement Value Estimates\n\n| Action | Value | Rationale |\n|--------|-------|-----------|\n| Like | $0.50 | Brand awareness |\n| Comment | $2.00 | Active engagement |\n| Share | $5.00 | Amplification |\n| Save | $3.00 | Intent signal |\n| Click | $1.50 | Traffic value |\n\n### ROI Interpretation\n\n| ROI % | Rating | Recommendation |\n|-------|--------|----------------|\n| > 500% | Excellent | Scale budget significantly |\n| 200-500% | Good | Increase budget moderately |\n| 100-200% | Acceptable | Optimize before scaling |\n| 0-100% | Break-even | Review targeting and creative |\n| \u003C 0% | Negative | Pause and restructure |\n\n---\n\n## Platform Benchmarks\n\n### Engagement Rate by Platform\n\n| Platform | Average | Good | Excellent |\n|----------|---------|------|-----------|\n| Instagram | 1.22% | 3-6% | >6% |\n| Facebook | 0.07% | 0.5-1% | >1% |\n| Twitter\u002FX | 0.05% | 0.1-0.5% | >0.5% |\n| LinkedIn | 2.0% | 3-5% | >5% |\n| TikTok | 5.96% | 8-15% | >15% |\n\n### CTR by Platform\n\n| Platform | Average | Good | Excellent |\n|----------|---------|------|-----------|\n| Instagram | 0.22% | 0.5-1% | >1% |\n| Facebook | 0.90% | 1.5-2.5% | >2.5% |\n| LinkedIn | 0.44% | 1-2% | >2% |\n| TikTok | 0.30% | 0.5-1% | >1% |\n\n### CPC by Platform\n\n| Platform | Average | Good |\n|----------|---------|------|\n| Facebook | $0.97 | \u003C$0.50 |\n| Instagram | $1.20 | \u003C$0.70 |\n| LinkedIn | $5.26 | \u003C$3.00 |\n| TikTok | $1.00 | \u003C$0.50 |\n\nSee `references\u002Fplatform-benchmarks.md` for complete benchmark data.\n\n---\n\n## Tools\n\n### Calculate Metrics\n\n```bash\npython scripts\u002Fcalculate_metrics.py assets\u002Fsample_input.json\n```\n\nCalculates engagement rate, CTR, reach rate for each post and campaign totals.\n\n### Analyze Performance\n\n```bash\npython scripts\u002Fanalyze_performance.py assets\u002Fsample_input.json\n```\n\nGenerates full performance analysis with ROI, benchmarks, and recommendations.\n\n**Output includes:**\n- Campaign-level metrics\n- Post-by-post breakdown\n- Benchmark comparisons\n- Top performers ranked\n- Actionable recommendations\n\n---\n\n## Examples\n\n### Sample Input\n\nSee `assets\u002Fsample_input.json`:\n\n```json\n{\n  \"platform\": \"instagram\",\n  \"total_spend\": 500,\n  \"posts\": [\n    {\n      \"post_id\": \"post_001\",\n      \"content_type\": \"image\",\n      \"likes\": 342,\n      \"comments\": 28,\n      \"shares\": 15,\n      \"saves\": 45,\n      \"reach\": 5200,\n      \"impressions\": 8500,\n      \"clicks\": 120\n    }\n  ]\n}\n```\n\n### Sample Output\n\nSee `assets\u002Fexpected_output.json`:\n\n```json\n{\n  \"campaign_metrics\": {\n    \"total_engagements\": 1521,\n    \"avg_engagement_rate\": 8.36,\n    \"ctr\": 1.55\n  },\n  \"roi_metrics\": {\n    \"total_spend\": 500.0,\n    \"cost_per_engagement\": 0.33,\n    \"roi_percentage\": 660.5\n  },\n  \"insights\": {\n    \"overall_health\": \"excellent\",\n    \"benchmark_comparison\": {\n      \"engagement_status\": \"excellent\",\n      \"engagement_benchmark\": \"1.22%\",\n      \"engagement_actual\": \"8.36%\"\n    }\n  }\n}\n```\n\n### Interpretation\n\nThe sample campaign shows:\n- **Engagement rate 8.36%** vs 1.22% benchmark = Excellent (6.8x above average)\n- **CTR 1.55%** vs 0.22% benchmark = Excellent (7x above average)\n- **ROI 660%** = Outstanding return on $500 spend\n- **Recommendation:** Scale budget, replicate successful elements\n\n---\n\n## Reference Documentation\n\n### Platform Benchmarks\n\n`references\u002Fplatform-benchmarks.md` contains:\n\n- Engagement rate benchmarks by platform and industry\n- CTR benchmarks for organic and paid content\n- Cost benchmarks (CPC, CPM, CPE)\n- Content type performance by platform\n- Optimal posting times and frequency\n- ROI calculation formulas\n\n## Proactive Triggers\n\n- **Engagement rate below platform average** → Content isn't resonating. Analyze top performers for patterns.\n- **Follower growth stalled** → Content distribution or frequency issue. Audit posting patterns.\n- **High impressions, low engagement** → Reach without resonance. Content quality issue.\n- **Competitor outperforming significantly** → Content gap. Analyze their successful posts.\n\n## Output Artifacts\n\n| When you ask for... | You get... |\n|---------------------|------------|\n| \"Social media audit\" | Performance analysis across platforms with benchmarks |\n| \"What's performing?\" | Top content analysis with patterns and recommendations |\n| \"Competitor social analysis\" | Competitive social media comparison with gaps |\n\n## Communication\n\nAll output passes quality verification:\n- Self-verify: source attribution, assumption audit, confidence scoring\n- Output format: Bottom Line → What (with confidence) → Why → How to Act\n- Results only. Every finding tagged: ? verified, ? medium, ? assumed.\n\n## Related Skills\n\n- **social-content**: For creating social posts. Use this skill for analyzing performance.\n- **campaign-analytics**: For cross-channel analytics including social.\n- **content-strategy**: For planning social content themes.\n- **marketing-context**: Provides audience context for better analysis.\n","# Social Media Analyzer\n\nCampaign performance analysis with engagement metrics, ROI calculations, and platform benchmarks.\n\n---\n\n## Table of Contents\n\n- [Analysis Workflow](#analysis-workflow)\n- [Engagement Metrics](#engagement-metrics)\n- [ROI Calculation](#roi-calculation)\n- [Platform Benchmarks](#platform-benchmarks)\n- [Tools](#tools)\n- [Examples](#examples)\n\n---\n\n## Analysis Workflow\n\nAnalyze social media campaign performance:\n\n1. Validate input data completeness (reach > 0, dates valid)\n2. Calculate engagement metrics per post\n3. Aggregate campaign-level metrics\n4. Calculate ROI if ad spend provided\n5. Compare against platform benchmarks\n6. Identify top and bottom performers\n7. Generate recommendations\n8. **Validation:** Engagement rate \u003C 100%, ROI matches spend data\n\n### Input Requirements\n\n| Field | Required | Description |\n|-------|----------|-------------|\n| platform | Yes | instagram, facebook, twitter, linkedin, tiktok |\n| posts[] | Yes | Array of post data |\n| posts[].likes | Yes | Like\u002Freaction count |\n| posts[].comments | Yes | Comment count |\n| posts[].reach | Yes | Unique users reached |\n| posts[].impressions | No | Total views |\n| posts[].shares | No | Share\u002Fretweet count |\n| posts[].saves | No | Save\u002Fbookmark count |\n| posts[].clicks | No | Link clicks |\n| total_spend | No | Ad spend (for ROI) |\n\n### Data Validation Checks\n\nBefore analysis, verify:\n\n- [ ] Reach > 0 for all posts (avoid division by zero)\n- [ ] Engagement counts are non-negative\n- [ ] Date range is valid (start \u003C end)\n- [ ] Platform is recognized\n- [ ] Spend > 0 if ROI requested\n\n---\n\n## Engagement Metrics\n\n### Engagement Rate Calculation\n\n```\nEngagement Rate = (Likes + Comments + Shares + Saves) \u002F Reach × 100\n```\n\n### Metric Definitions\n\n| Metric | Formula | Interpretation |\n|--------|---------|----------------|\n| Engagement Rate | Engagements \u002F Reach × 100 | Audience interaction level |\n| CTR | Clicks \u002F Impressions × 100 | Content click appeal |\n| Reach Rate | Reach \u002F Followers × 100 | Content distribution |\n| Virality Rate | Shares \u002F Impressions × 100 | Share-worthiness |\n| Save Rate | Saves \u002F Reach × 100 | Content value |\n\n### Performance Categories\n\n| Rating | Engagement Rate | Action |\n|--------|-----------------|--------|\n| Excellent | > 6% | Scale and replicate |\n| Good | 3-6% | Optimize and expand |\n| Average | 1-3% | Test improvements |\n| Poor | \u003C 1% | Analyze and pivot |\n\n---\n\n## ROI Calculation\n\nCalculate return on ad spend:\n\n1. Sum total engagements across posts\n2. Calculate cost per engagement (CPE)\n3. Calculate cost per click (CPC) if clicks available\n4. Estimate engagement value using benchmark rates\n5. Calculate ROI percentage\n6. **Validation:** ROI = (Value - Spend) \u002F Spend × 100\n\n### ROI Formulas\n\n| Metric | Formula |\n|--------|---------|\n| Cost Per Engagement (CPE) | Total Spend \u002F Total Engagements |\n| Cost Per Click (CPC) | Total Spend \u002F Total Clicks |\n| Cost Per Thousand (CPM) | (Spend \u002F Impressions) × 1000 |\n| Return on Ad Spend (ROAS) | Revenue \u002F Ad Spend |\n\n### Engagement Value Estimates\n\n| Action | Value | Rationale |\n|--------|-------|-----------|\n| Like | $0.50 | Brand awareness |\n| Comment | $2.00 | Active engagement |\n| Share | $5.00 | Amplification |\n| Save | $3.00 | Intent signal |\n| Click | $1.50 | Traffic value |\n\n### ROI Interpretation\n\n| ROI % | Rating | Recommendation |\n|-------|--------|----------------|\n| > 500% | Excellent | Scale budget significantly |\n| 200-500% | Good | Increase budget moderately |\n| 100-200% | Acceptable | Optimize before scaling |\n| 0-100% | Break-even | Review targeting and creative |\n| \u003C 0% | Negative | Pause and restructure |\n\n---\n\n## Platform Benchmarks\n\n### Engagement Rate by Platform\n\n| Platform | Average | Good | Excellent |\n|----------|---------|------|-----------|\n| Instagram | 1.22% | 3-6% | >6% |\n| Facebook | 0.07% | 0.5-1% | >1% |\n| Twitter\u002FX | 0.05% | 0.1-0.5% | >0.5% |\n| LinkedIn | 2.0% | 3-5% | >5% |\n| TikTok | 5.96% | 8-15% | >15% |\n\n### CTR by Platform\n\n| Platform | Average | Good | Excellent |\n|----------|---------|------|-----------|\n| Instagram | 0.22% | 0.5-1% | >1% |\n| Facebook | 0.90% | 1.5-2.5% | >2.5% |\n| LinkedIn | 0.44% | 1-2% | >2% |\n| TikTok | 0.30% | 0.5-1% | >1% |\n\n### CPC by Platform\n\n| Platform | Average | Good |\n|----------|---------|------|\n| Facebook | $0.97 | \u003C$0.50 |\n| Instagram | $1.20 | \u003C$0.70 |\n| LinkedIn | $5.26 | \u003C$3.00 |\n| TikTok | $1.00 | \u003C$0.50 |\n\nSee `references\u002Fplatform-benchmarks.md` for complete benchmark data.\n\n---\n\n## Tools\n\n### Calculate Metrics\n\n```bash\npython scripts\u002Fcalculate_metrics.py assets\u002Fsample_input.json\n```\n\nCalculates engagement rate, CTR, reach rate for each post and campaign totals.\n\n### Analyze Performance\n\n```bash\npython scripts\u002Fanalyze_performance.py assets\u002Fsample_input.json\n```\n\nGenerates full performance analysis with ROI, benchmarks, and recommendations.\n\n**Output includes:**\n- Campaign-level metrics\n- Post-by-post breakdown\n- Benchmark comparisons\n- Top performers ranked\n- Actionable recommendations\n\n---\n\n## Examples\n\n### Sample Input\n\nSee `assets\u002Fsample_input.json`:\n\n```json\n{\n  \"platform\": \"instagram\",\n  \"total_spend\": 500,\n  \"posts\": [\n    {\n      \"post_id\": \"post_001\",\n      \"content_type\": \"image\",\n      \"likes\": 342,\n      \"comments\": 28,\n      \"shares\": 15,\n      \"saves\": 45,\n      \"reach\": 5200,\n      \"impressions\": 8500,\n      \"clicks\": 120\n    }\n  ]\n}\n```\n\n### Sample Output\n\nSee `assets\u002Fexpected_output.json`:\n\n```json\n{\n  \"campaign_metrics\": {\n    \"total_engagements\": 1521,\n    \"avg_engagement_rate\": 8.36,\n    \"ctr\": 1.55\n  },\n  \"roi_metrics\": {\n    \"total_spend\": 500.0,\n    \"cost_per_engagement\": 0.33,\n    \"roi_percentage\": 660.5\n  },\n  \"insights\": {\n    \"overall_health\": \"excellent\",\n    \"benchmark_comparison\": {\n      \"engagement_status\": \"excellent\",\n      \"engagement_benchmark\": \"1.22%\",\n      \"engagement_actual\": \"8.36%\"\n    }\n  }\n}\n```\n\n### Interpretation\n\nThe sample campaign shows:\n- **Engagement rate 8.36%** vs 1.22% benchmark = Excellent (6.8x above average)\n- **CTR 1.55%** vs 0.22% benchmark = Excellent (7x above average)\n- **ROI 660%** = Outstanding return on $500 spend\n- **Recommendation:** Scale budget, replicate successful elements\n\n---\n\n## Reference Documentation\n\n### Platform Benchmarks\n\n`references\u002Fplatform-benchmarks.md` contains:\n\n- Engagement rate benchmarks by platform and industry\n- CTR benchmarks for organic and paid content\n- Cost benchmarks (CPC, CPM, CPE)\n- Content type performance by platform\n- Optimal posting times and frequency\n- ROI calculation formulas\n\n## Proactive Triggers\n\n- **Engagement rate below platform average** → Content isn't resonating. Analyze top performers for patterns.\n- **Follower growth stalled** → Content distribution or frequency issue. Audit posting patterns.\n- **High impressions, low engagement** → Reach without resonance. Content quality issue.\n- **Competitor outperforming significantly** → Content gap. Analyze their successful posts.\n\n## Output Artifacts\n\n| When you ask for... | You get... |\n|---------------------|------------|\n| \"Social media audit\" | Performance analysis across platforms with benchmarks |\n| \"What's performing?\" | Top content analysis with patterns and recommendations |\n| \"Competitor social analysis\" | Competitive social media comparison with gaps |\n\n## Communication\n\nAll output passes quality verification:\n- Self-verify: source attribution, assumption audit, confidence scoring\n- Output format: Bottom Line → What (with confidence) → Why → How to Act\n- Results only. Every finding tagged: ? verified, ? medium, ? assumed.\n\n## Related Skills\n\n- **social-content**: For creating social posts. Use this skill for analyzing performance.\n- **campaign-analytics**: For cross-channel analytics including social.\n- **content-strategy**: For planning social content themes.\n- **marketing-context**: Provides audience context for better analysis.\n",{"name":5,"triggers":54,"description":7},[55,56,57,58,59,60,61,62,63,64],"analyze social media","calculate engagement rate","social media ROI","campaign performance","compare platforms","benchmark engagement","Instagram analytics","Facebook metrics","TikTok performance","LinkedIn engagement","main","c0a12fc98d85642fa8893e31fc5cf5dfad879de6","marketing-skill\u002Fsocial-media-analyzer",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":73,"prompt":83,"zipAvailable":84},[74,77,80],{"tool":75,"command":76},"npx","npx skills add zhangzhang-111-i\u002Fclaude-skills111 --skill social-media-analyzer",{"tool":78,"command":79},"bunx","bunx skills add zhangzhang-111-i\u002Fclaude-skills111 --skill social-media-analyzer",{"tool":81,"command":82},"pnpm","pnpm dlx skills add zhangzhang-111-i\u002Fclaude-skills111 --skill social-media-analyzer","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fzhangzhang-111-i\u002Fclaude-skills111\u002Fblob\u002Fmain\u002Fmarketing-skill\u002Fsocial-media-analyzer\u002FSKILL.md",true,[86,92,96,102,106,112],{"path":87,"resourceType":88,"resourceTypeDesc":89,"sizeBytes":90,"sourceHtmlUrl":91},"assets\u002Fexpected_output.json","ASSET","资产文件",1519,"https:\u002F\u002Fgithub.com\u002Fzhangzhang-111-i\u002Fclaude-skills111\u002Fblob\u002Fmain\u002Fmarketing-skill\u002Fsocial-media-analyzer\u002Fassets\u002Fexpected_output.json",{"path":93,"resourceType":88,"resourceTypeDesc":89,"sizeBytes":94,"sourceHtmlUrl":95},"assets\u002Fsample_input.json",867,"https:\u002F\u002Fgithub.com\u002Fzhangzhang-111-i\u002Fclaude-skills111\u002Fblob\u002Fmain\u002Fmarketing-skill\u002Fsocial-media-analyzer\u002Fassets\u002Fsample_input.json",{"path":97,"resourceType":98,"resourceTypeDesc":99,"sizeBytes":100,"sourceHtmlUrl":101},"HOW_TO_USE.md","REFERENCE","参考文档",1863,"https:\u002F\u002Fgithub.com\u002Fzhangzhang-111-i\u002Fclaude-skills111\u002Fblob\u002Fmain\u002Fmarketing-skill\u002Fsocial-media-analyzer\u002FHOW_TO_USE.md",{"path":103,"resourceType":98,"resourceTypeDesc":99,"sizeBytes":104,"sourceHtmlUrl":105},"references\u002Fplatform-benchmarks.md",6020,"https:\u002F\u002Fgithub.com\u002Fzhangzhang-111-i\u002Fclaude-skills111\u002Fblob\u002Fmain\u002Fmarketing-skill\u002Fsocial-media-analyzer\u002Freferences\u002Fplatform-benchmarks.md",{"path":107,"resourceType":108,"resourceTypeDesc":109,"sizeBytes":110,"sourceHtmlUrl":111},"scripts\u002Fanalyze_performance.py","SCRIPT","脚本",7331,"https:\u002F\u002Fgithub.com\u002Fzhangzhang-111-i\u002Fclaude-skills111\u002Fblob\u002Fmain\u002Fmarketing-skill\u002Fsocial-media-analyzer\u002Fscripts\u002Fanalyze_performance.py",{"path":113,"resourceType":108,"resourceTypeDesc":109,"sizeBytes":114,"sourceHtmlUrl":115},"scripts\u002Fcalculate_metrics.py",5540,"https:\u002F\u002Fgithub.com\u002Fzhangzhang-111-i\u002Fclaude-skills111\u002Fblob\u002Fmain\u002Fmarketing-skill\u002Fsocial-media-analyzer\u002Fscripts\u002Fcalculate_metrics.py",[117,142,166,193,212,235],{"skillNo":118,"name":119,"nameZh":6,"description":120,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":121,"categories":122,"keywords":123,"publishedAt":49},"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",[],[124,125,126,127,128,129,130,131,132,133,47,134,33,135,136,137,138,139,140,141],"risk","risk management specialist","management","risk management","risk analysis","risk evaluation","product","Evaluation","Production","lifecycle","user","risk matrix","Market","device","control","iso","medical","iso 14971",{"skillNo":143,"name":144,"nameZh":6,"description":145,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":146,"categories":147,"keywords":148,"publishedAt":49},"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",[],[149,150,151,152,153,154,155,156,157,158,159,160,161,40,162,163,35,164,140,165],"regulatory affairs head","regulatory","head","documentation","documents","packages","planning","devices","plan","access","write","strategy","evidence","manage","intelligence","strategies","clinical",{"skillNo":167,"name":168,"nameZh":6,"description":169,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":170,"categories":171,"keywords":178,"publishedAt":49},"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",[172,175],{"categoryNo":173,"categoryName":174,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000015","视觉设计",{"categoryNo":176,"categoryName":177,"taxonomyType":26,"taxonomyTypeDesc":27},"01JBSEEDCAT000000000000032","设计师",[179,180,181,182,183,184,152,185,186,187,188,189,33,150,190,191,192,138,139,140],"quality manager qms iso13485","quality","design","review","support","workflows","audit","actions","compliance","system","process","up","maintenance","document",{"skillNo":194,"name":195,"nameZh":6,"description":196,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":197,"categories":198,"keywords":202,"publishedAt":49},"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",[199],{"categoryNo":200,"categoryName":201,"taxonomyType":26,"taxonomyTypeDesc":27},"01JBSEEDCAT000000000000037","律师与法务",[203,180,182,204,42,205,206,187,207,188,126,208,150,209,210,211,139],"quality manager qmr","policy","governance","monitoring","regulatory compliance","oversight","cost","culture","leadership",{"skillNo":213,"name":214,"nameZh":6,"description":215,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":216,"categories":217,"keywords":222,"publishedAt":49},"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",[218,221],{"categoryNo":219,"categoryName":220,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000002","文档处理",{"categoryNo":200,"categoryName":201,"taxonomyType":26,"taxonomyTypeDesc":27},[152,223,180,182,224,225,185,133,226,188,227,228,33,229,230,231,140,232,233,234],"quality documentation manager","workflow","change","document lifecycle","change management","list","master","system management","documentation review","cfr","21 cfr part 11","change control",{"skillNo":236,"name":237,"nameZh":6,"description":238,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":239,"categories":240,"keywords":241,"publishedAt":49},"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",[],[185,242,243,155,244,245,246,247,126,33,248,137,139,140],"qms audit expert","expert","verification","execution","classification","schedule","checklist"]