[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6EHMZJ2BHTTP1F38CSKVKZT":3,"skill-same:01M6EHMZJ2BHTTP1F38CSKVKZT":73},{"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":18,"publishedAt":37,"linkOnly":38,"markdownContent":39,"markdownBody":40,"frontMatter":41,"refName":50,"commitSha":51,"skillDirectory":52,"forksCount":53,"repositoryHtmlUrl":54,"repositoryHomepageUrl":6,"ownerHtmlUrl":55,"ownerBlogUrl":56,"ownerDescription":57,"updatedAt":58,"install":59,"resources":72},"01M6EHMZJ2BHTTP1F38CSKVKZT","org-health-diagnostic",null,"Cross-functional organizational health check combining signals from all C-suite roles. Scores 8 dimensions on a traffic-light scale with drill-down recommendations. Use when assessing overall company health, preparing for board reviews, identifying at-risk functions, or when user mentions org health, health check, or health dashboard.","levalencia\u002Fagent-god-mode","levalencia","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F6962857?v=4","01M6EB0FZZ4BPQPC4HET4QY6NM","Luis Valencia ","01M6EB0G4HWHPWW0H9X7QKSAHP",3,"MIT","https:\u002F\u002Fgithub.com\u002Flevalencia\u002Fagent-god-mode\u002Fblob\u002Fmain\u002Forganized-skills\u002Forg-health-diagnostic\u002FSKILL.md",[],[19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36],"health","org","org health diagnostic","functions","scale","drill","roles","recommendations","signals","dimensions","benchmarks","dashboard","health check","use","user","board","check","risk","2026-11-10 10:12:30",false,"---\nname: \"org-health-diagnostic\"\ndescription: \"Cross-functional organizational health check combining signals from all C-suite roles. Scores 8 dimensions on a traffic-light scale with drill-down recommendations. Use when assessing overall company health, preparing for board reviews, identifying at-risk functions, or when user mentions org health, health check, or health dashboard.\"\nlicense: MIT\nmetadata:\n  version: 1.0.0\n  author: Alireza Rezvani\n  category: c-level\n  domain: organizational-health\n  updated: 2026-03-05\n  python-tools: health_scorer.py\n  frameworks: health-benchmarks\n---\n\n# Org Health Diagnostic\n\nEight dimensions. Traffic lights. Real benchmarks. Surfaces the problems you don't know you have.\n\n## Keywords\norg health, organizational health, health diagnostic, health dashboard, health check, company health, functional health, team health, startup health, health scorecard, health assessment, risk dashboard\n\n## Quick Start\n\n```bash\npython scripts\u002Fhealth_scorer.py        # Guided CLI — enter metrics, get scored dashboard\npython scripts\u002Fhealth_scorer.py --json # Output raw JSON for integration\n```\n\nOr describe your metrics:\n```\n\u002Fhealth [paste your key metrics or answer prompts]\n\u002Fhealth:dimension [financial|revenue|product|engineering|people|ops|security|market]\n```\n\n## The 8 Dimensions\n\n### 1. ? Financial Health (CFO)\n**What it measures:** Can we fund operations and invest in growth?\n\nKey metrics:\n- **Runway** — months at current burn (Green: >12, Yellow: 6-12, Red: \u003C6)\n- **Burn multiple** — net burn \u002F net new ARR (Green: \u003C1.5x, Yellow: 1.5-2.5x, Red: >2.5x)\n- **Gross margin** — SaaS target: >65% (Green: >70%, Yellow: 55-70%, Red: \u003C55%)\n- **MoM growth rate** — contextual by stage (see benchmarks)\n- **Revenue concentration** — top customer % of ARR (Green: \u003C15%, Yellow: 15-25%, Red: >25%)\n\n### 2. ? Revenue Health (CRO)\n**What it measures:** Are customers staying, growing, and recommending us?\n\nKey metrics:\n- **NRR (Net Revenue Retention)** — Green: >110%, Yellow: 100-110%, Red: \u003C100%\n- **Logo churn rate (annualized)** — Green: \u003C5%, Yellow: 5-10%, Red: >10%\n- **Pipeline coverage (next quarter)** — Green: >3x, Yellow: 2-3x, Red: \u003C2x\n- **CAC payback period** — Green: \u003C12 months, Yellow: 12-18, Red: >18 months\n- **Average ACV trend** — directional: growing, flat, declining\n\n### 3. ? Product Health (CPO)\n**What it measures:** Do customers love and use the product?\n\nKey metrics:\n- **NPS** — Green: >40, Yellow: 20-40, Red: \u003C20\n- **DAU\u002FMAU ratio** — engagement proxy (Green: >40%, Yellow: 20-40%, Red: \u003C20%)\n- **Core feature adoption** — % of users using primary value feature (Green: >60%)\n- **Time-to-value** — days from signup to first core action (lower is better)\n- **Customer satisfaction (CSAT)** — Green: >4.2\u002F5, Yellow: 3.5-4.2, Red: \u003C3.5\n\n### 4. ⚙️ Engineering Health (CTO)\n**What it measures:** Can we ship reliably and sustain velocity?\n\nKey metrics:\n- **Deployment frequency** — Green: daily, Yellow: weekly, Red: monthly or less\n- **Change failure rate** — % of deployments causing incidents (Green: \u003C5%, Red: >15%)\n- **Mean time to recovery (MTTR)** — Green: \u003C1 hour, Yellow: 1-4 hours, Red: >4 hours\n- **Tech debt ratio** — % of sprint capacity on debt (Green: \u003C20%, Yellow: 20-35%, Red: >35%)\n- **Incident frequency** — P0\u002FP1 per month (Green: \u003C2, Yellow: 2-5, Red: >5)\n\n### 5. ? People Health (CHRO)\n**What it measures:** Is the team stable, engaged, and growing?\n\nKey metrics:\n- **Regrettable attrition (annualized)** — Green: \u003C10%, Yellow: 10-20%, Red: >20%\n- **Engagement score** — (eNPS or similar; Green: >30, Yellow: 0-30, Red: \u003C0)\n- **Time-to-fill (avg days)** — Green: \u003C45, Yellow: 45-90, Red: >90\n- **Manager-to-IC ratio** — Green: 1:5–1:8, Yellow: 1:3–1:5 or 1:8–1:12, Red: outside\n- **Internal promotion rate** — at least 25-30% of senior roles filled internally\n\n### 6. ? Operational Health (COO)\n**What it measures:** Are we executing our strategy with discipline?\n\nKey metrics:\n- **OKR completion rate** — % of key results hitting target (Green: >70%, Yellow: 50-70%, Red: \u003C50%)\n- **Decision cycle time** — days from decision needed to decision made (Green: \u003C48h, Yellow: 48h-1w)\n- **Meeting effectiveness** — % of meetings with clear outcome (qualitative)\n- **Process maturity** — level 1-5 scale (see COO advisor)\n- **Cross-functional initiative completion** — % on time, on scope\n\n### 7. ? Security Health (CISO)\n**What it measures:** Are we protecting customers and maintaining compliance?\n\nKey metrics:\n- **Security incidents (last 90 days)** — Green: 0, Yellow: 1-2 minor, Red: 1+ major\n- **Compliance status** — certifications current\u002Fin-progress vs. overdue\n- **Vulnerability remediation SLA** — % of critical CVEs patched within SLA (Green: 100%)\n- **Security training completion** — % of team current (Green: >95%)\n- **Pen test recency** — Green: \u003C12 months, Yellow: 12-24, Red: >24 months\n\n### 8. ? Market Health (CMO)\n**What it measures:** Are we winning in the market and growing efficiently?\n\nKey metrics:\n- **CAC trend** — improving, flat, or worsening QoQ\n- **Organic vs paid lead mix** — more organic = healthier (less fragile)\n- **Win rate** — % of qualified opportunities closed-won (Green: >25%, Yellow: 15-25%, Red: \u003C15%)\n- **Competitive win rate** — against primary competitors specifically\n- **Brand NPS** — awareness + preference scores in ICP\n\n---\n\n## Scoring & Traffic Lights\n\nEach dimension is scored 1-10 with traffic light:\n- ? **Green (7-10):** Healthy — maintain and optimize\n- ? **Yellow (4-6):** Watch — trend matters; improving or declining?\n- ? **Red (1-3):** Action required — address within 30 days\n\n**Overall Health Score:**\nWeighted average by company stage (see `references\u002Fhealth-benchmarks.md` for weights).\n\n---\n\n## Dimension Interactions (Why One Problem Creates Another)\n\n| If this dimension is red... | Watch these dimensions next |\n|-----------------------------|----------------------------|\n| Financial Health | People (freeze hiring) → Engineering (freeze infra) → Product (cut scope) |\n| Revenue Health | Financial (cash gap) → People (attrition risk) → Market (lose positioning) |\n| People Health | Engineering (velocity drops) → Product (quality drops) → Revenue (churn rises) |\n| Engineering Health | Product (features slip) → Revenue (deals stall on product) |\n| Product Health | Revenue (NRR drops, churn rises) → Market (CAC rises; referrals dry up) |\n| Operational Health | All dimensions degrade over time (execution failure cascades everywhere) |\n\n---\n\n## Dashboard Output Format\n\n```\nORG HEALTH DIAGNOSTIC — [Company] — [Date]\nStage: [Seed\u002FA\u002FB\u002FC]   Overall: [Score]\u002F10   Trend: [↑ Improving \u002F → Stable \u002F ↓ Declining]\n\nDIMENSION SCORES\n━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\n? Financial    ? 8.2  Runway 14mo, burn 1.6x — strong\n? Revenue      ? 5.8  NRR 104%, pipeline thin (1.8x coverage)\n? Product      ? 7.4  NPS 42, DAU\u002FMAU 38%\n⚙️  Engineering  ? 5.2  Debt at 30%, MTTR 3.2h\n? People       ? 3.8  Attrition 24%, eng morale low\n? Operations   ? 6.0  OKR 65% completion\n? Security     ? 7.8  SOC 2 Type II complete, 0 incidents\n? Market       ? 5.5  CAC rising, win rate dropped to 22%\n━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\n\nTOP PRIORITIES\n? [1] People: attrition at 24% — engineering velocity will drop in 60 days\n   Action: CHRO + CEO to run retention audit; target top 5 at-risk this week\n? [2] Revenue: pipeline coverage at 1.8x — Q+1 miss risk is high\n   Action: CRO to add 3 qualified opps within 30 days or shift forecast down\n? [3] Engineering: tech debt at 30% of sprint — shipping will slow by Q3\n   Action: CTO to propose debt sprint plan; COO to protect capacity\n\nWATCH\n→ People → Engineering cascade risk if attrition continues (see dimension interactions)\n```\n\n---\n\n## Graceful Degradation\n\nYou don't need all metrics to run a diagnostic. The tool handles partial data:\n- Missing metric → excluded from score, flagged as \"[data needed]\"\n- Score still valid for available dimensions\n- Report flags which gaps to fill for next cycle\n\n## References\n- `references\u002Fhealth-benchmarks.md` — benchmarks by stage (Seed, A, B, C)\n- `scripts\u002Fhealth_scorer.py` — CLI scoring tool with traffic light output\n","# Org Health Diagnostic\n\nEight dimensions. Traffic lights. Real benchmarks. Surfaces the problems you don't know you have.\n\n## Keywords\norg health, organizational health, health diagnostic, health dashboard, health check, company health, functional health, team health, startup health, health scorecard, health assessment, risk dashboard\n\n## Quick Start\n\n```bash\npython scripts\u002Fhealth_scorer.py        # Guided CLI — enter metrics, get scored dashboard\npython scripts\u002Fhealth_scorer.py --json # Output raw JSON for integration\n```\n\nOr describe your metrics:\n```\n\u002Fhealth [paste your key metrics or answer prompts]\n\u002Fhealth:dimension [financial|revenue|product|engineering|people|ops|security|market]\n```\n\n## The 8 Dimensions\n\n### 1. ? Financial Health (CFO)\n**What it measures:** Can we fund operations and invest in growth?\n\nKey metrics:\n- **Runway** — months at current burn (Green: >12, Yellow: 6-12, Red: \u003C6)\n- **Burn multiple** — net burn \u002F net new ARR (Green: \u003C1.5x, Yellow: 1.5-2.5x, Red: >2.5x)\n- **Gross margin** — SaaS target: >65% (Green: >70%, Yellow: 55-70%, Red: \u003C55%)\n- **MoM growth rate** — contextual by stage (see benchmarks)\n- **Revenue concentration** — top customer % of ARR (Green: \u003C15%, Yellow: 15-25%, Red: >25%)\n\n### 2. ? Revenue Health (CRO)\n**What it measures:** Are customers staying, growing, and recommending us?\n\nKey metrics:\n- **NRR (Net Revenue Retention)** — Green: >110%, Yellow: 100-110%, Red: \u003C100%\n- **Logo churn rate (annualized)** — Green: \u003C5%, Yellow: 5-10%, Red: >10%\n- **Pipeline coverage (next quarter)** — Green: >3x, Yellow: 2-3x, Red: \u003C2x\n- **CAC payback period** — Green: \u003C12 months, Yellow: 12-18, Red: >18 months\n- **Average ACV trend** — directional: growing, flat, declining\n\n### 3. ? Product Health (CPO)\n**What it measures:** Do customers love and use the product?\n\nKey metrics:\n- **NPS** — Green: >40, Yellow: 20-40, Red: \u003C20\n- **DAU\u002FMAU ratio** — engagement proxy (Green: >40%, Yellow: 20-40%, Red: \u003C20%)\n- **Core feature adoption** — % of users using primary value feature (Green: >60%)\n- **Time-to-value** — days from signup to first core action (lower is better)\n- **Customer satisfaction (CSAT)** — Green: >4.2\u002F5, Yellow: 3.5-4.2, Red: \u003C3.5\n\n### 4. ⚙️ Engineering Health (CTO)\n**What it measures:** Can we ship reliably and sustain velocity?\n\nKey metrics:\n- **Deployment frequency** — Green: daily, Yellow: weekly, Red: monthly or less\n- **Change failure rate** — % of deployments causing incidents (Green: \u003C5%, Red: >15%)\n- **Mean time to recovery (MTTR)** — Green: \u003C1 hour, Yellow: 1-4 hours, Red: >4 hours\n- **Tech debt ratio** — % of sprint capacity on debt (Green: \u003C20%, Yellow: 20-35%, Red: >35%)\n- **Incident frequency** — P0\u002FP1 per month (Green: \u003C2, Yellow: 2-5, Red: >5)\n\n### 5. ? People Health (CHRO)\n**What it measures:** Is the team stable, engaged, and growing?\n\nKey metrics:\n- **Regrettable attrition (annualized)** — Green: \u003C10%, Yellow: 10-20%, Red: >20%\n- **Engagement score** — (eNPS or similar; Green: >30, Yellow: 0-30, Red: \u003C0)\n- **Time-to-fill (avg days)** — Green: \u003C45, Yellow: 45-90, Red: >90\n- **Manager-to-IC ratio** — Green: 1:5–1:8, Yellow: 1:3–1:5 or 1:8–1:12, Red: outside\n- **Internal promotion rate** — at least 25-30% of senior roles filled internally\n\n### 6. ? Operational Health (COO)\n**What it measures:** Are we executing our strategy with discipline?\n\nKey metrics:\n- **OKR completion rate** — % of key results hitting target (Green: >70%, Yellow: 50-70%, Red: \u003C50%)\n- **Decision cycle time** — days from decision needed to decision made (Green: \u003C48h, Yellow: 48h-1w)\n- **Meeting effectiveness** — % of meetings with clear outcome (qualitative)\n- **Process maturity** — level 1-5 scale (see COO advisor)\n- **Cross-functional initiative completion** — % on time, on scope\n\n### 7. ? Security Health (CISO)\n**What it measures:** Are we protecting customers and maintaining compliance?\n\nKey metrics:\n- **Security incidents (last 90 days)** — Green: 0, Yellow: 1-2 minor, Red: 1+ major\n- **Compliance status** — certifications current\u002Fin-progress vs. overdue\n- **Vulnerability remediation SLA** — % of critical CVEs patched within SLA (Green: 100%)\n- **Security training completion** — % of team current (Green: >95%)\n- **Pen test recency** — Green: \u003C12 months, Yellow: 12-24, Red: >24 months\n\n### 8. ? Market Health (CMO)\n**What it measures:** Are we winning in the market and growing efficiently?\n\nKey metrics:\n- **CAC trend** — improving, flat, or worsening QoQ\n- **Organic vs paid lead mix** — more organic = healthier (less fragile)\n- **Win rate** — % of qualified opportunities closed-won (Green: >25%, Yellow: 15-25%, Red: \u003C15%)\n- **Competitive win rate** — against primary competitors specifically\n- **Brand NPS** — awareness + preference scores in ICP\n\n---\n\n## Scoring & Traffic Lights\n\nEach dimension is scored 1-10 with traffic light:\n- ? **Green (7-10):** Healthy — maintain and optimize\n- ? **Yellow (4-6):** Watch — trend matters; improving or declining?\n- ? **Red (1-3):** Action required — address within 30 days\n\n**Overall Health Score:**\nWeighted average by company stage (see `references\u002Fhealth-benchmarks.md` for weights).\n\n---\n\n## Dimension Interactions (Why One Problem Creates Another)\n\n| If this dimension is red... | Watch these dimensions next |\n|-----------------------------|----------------------------|\n| Financial Health | People (freeze hiring) → Engineering (freeze infra) → Product (cut scope) |\n| Revenue Health | Financial (cash gap) → People (attrition risk) → Market (lose positioning) |\n| People Health | Engineering (velocity drops) → Product (quality drops) → Revenue (churn rises) |\n| Engineering Health | Product (features slip) → Revenue (deals stall on product) |\n| Product Health | Revenue (NRR drops, churn rises) → Market (CAC rises; referrals dry up) |\n| Operational Health | All dimensions degrade over time (execution failure cascades everywhere) |\n\n---\n\n## Dashboard Output Format\n\n```\nORG HEALTH DIAGNOSTIC — [Company] — [Date]\nStage: [Seed\u002FA\u002FB\u002FC]   Overall: [Score]\u002F10   Trend: [↑ Improving \u002F → Stable \u002F ↓ Declining]\n\nDIMENSION SCORES\n━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\n? Financial    ? 8.2  Runway 14mo, burn 1.6x — strong\n? Revenue      ? 5.8  NRR 104%, pipeline thin (1.8x coverage)\n? Product      ? 7.4  NPS 42, DAU\u002FMAU 38%\n⚙️  Engineering  ? 5.2  Debt at 30%, MTTR 3.2h\n? People       ? 3.8  Attrition 24%, eng morale low\n? Operations   ? 6.0  OKR 65% completion\n? Security     ? 7.8  SOC 2 Type II complete, 0 incidents\n? Market       ? 5.5  CAC rising, win rate dropped to 22%\n━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\n\nTOP PRIORITIES\n? [1] People: attrition at 24% — engineering velocity will drop in 60 days\n   Action: CHRO + CEO to run retention audit; target top 5 at-risk this week\n? [2] Revenue: pipeline coverage at 1.8x — Q+1 miss risk is high\n   Action: CRO to add 3 qualified opps within 30 days or shift forecast down\n? [3] Engineering: tech debt at 30% of sprint — shipping will slow by Q3\n   Action: CTO to propose debt sprint plan; COO to protect capacity\n\nWATCH\n→ People → Engineering cascade risk if attrition continues (see dimension interactions)\n```\n\n---\n\n## Graceful Degradation\n\nYou don't need all metrics to run a diagnostic. The tool handles partial data:\n- Missing metric → excluded from score, flagged as \"[data needed]\"\n- Score still valid for available dimensions\n- Report flags which gaps to fill for next cycle\n\n## References\n- `references\u002Fhealth-benchmarks.md` — benchmarks by stage (Seed, A, B, C)\n- `scripts\u002Fhealth_scorer.py` — CLI scoring tool with traffic light output\n",{"name":5,"license":15,"metadata":42,"description":7},{"author":43,"domain":44,"updated":45,"version":46,"category":47,"frameworks":48,"python-tools":49},"Alireza Rezvani","organizational-health",1772668800000,"1.0.0","c-level","health-benchmarks","health_scorer.py","main","fa638b97a18ff6d9f26cf0eaf3dfa123531bcc87","organized-skills\u002Forg-health-diagnostic",1,"https:\u002F\u002Fgithub.com\u002Flevalencia\u002Fagent-god-mode","https:\u002F\u002Fgithub.com\u002Flevalencia","https:\u002F\u002Fmedium.com\u002F@luisevalencia","Microsoft MVP - Artificial Intelligence\r\nMachine Learning Enthusiast\r\n","2026-05-02 06:55:36",{"source":8,"skillName":5,"commands":60,"prompt":70,"zipAvailable":71},[61,64,67],{"tool":62,"command":63},"npx","npx skills add levalencia\u002Fagent-god-mode --skill org-health-diagnostic",{"tool":65,"command":66},"bunx","bunx skills add levalencia\u002Fagent-god-mode --skill org-health-diagnostic",{"tool":68,"command":69},"pnpm","pnpm dlx skills add levalencia\u002Fagent-god-mode --skill org-health-diagnostic","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Flevalencia\u002Fagent-god-mode\u002Fblob\u002Fmain\u002Forganized-skills\u002Forg-health-diagnostic\u002FSKILL.md",true,[],[74,95,132,159,184,212],{"skillNo":75,"name":76,"nameZh":6,"description":77,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":78,"categories":79,"keywords":80,"publishedAt":37},"01M6EM8ES5M9J4S8N78NJST0YC","zarr-python","Chunked N-D arrays for cloud storage. Compressed arrays, parallel I\u002FO, S3\u002FGCS integration, NumPy\u002FDask\u002FXarray compatible, for large-scale scientific computing pipelines.","https:\u002F\u002Fgithub.com\u002Flevalencia\u002Fagent-god-mode\u002Fblob\u002Fmain\u002Forganized-skills\u002Fzarr-python\u002FSKILL.md",[],[81,82,83,84,85,86,87,88,89,90,91,92,93,23,94],"python","zarr python","storage","integration","s3","gcs","cloud","dask","parallel","pipelines","arrays","numpy","scientific computing","scientific",{"skillNo":96,"name":97,"nameZh":6,"description":98,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":99,"categories":100,"keywords":114,"publishedAt":37},"01M6EM8AR6ZFKZ9YVW8TTG850Z","zabbix","Zabbix monitoring system automation via API and Python. Use when: (1) Managing hosts, templates, items, triggers, or host groups, (2) Automating monitoring configuration, (3) Sending data via Zabbix trapper\u002Fsender, (4) Querying historical data or events, (5) Bulk operations on Zabbix objects, (6) Maintenance window management, (7) User\u002Fpermission management","https:\u002F\u002Fgithub.com\u002Flevalencia\u002Fagent-god-mode\u002Fblob\u002Fmain\u002Forganized-skills\u002Fzabbix-api-skill\u002FSKILL.md",[101,106,109],{"categoryNo":102,"categoryName":103,"taxonomyType":104,"taxonomyTypeDesc":105},"01JBSEEDCAT000000000000010","后端与接口","SCENARIO","使用场景",{"categoryNo":107,"categoryName":108,"taxonomyType":104,"taxonomyTypeDesc":105},"01JBSEEDCAT000000000000023","Skill与智能体开发",{"categoryNo":110,"categoryName":111,"taxonomyType":112,"taxonomyTypeDesc":113},"01JBSEEDCAT000000000000030","开发工程师","PROFESSION","适用职业",[97,81,115,116,117,118,119,120,121,122,32,123,124,125,126,127,128,129,130,131],"automation","window management","monitoring","data","templates","api","system","operations","maintenance","objects","permission","bulk operations","triggers","host","events","via","bulk",{"skillNo":133,"name":134,"nameZh":6,"description":135,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":136,"categories":137,"keywords":138,"publishedAt":37},"01M6EM6Q9JG846ECQY9A210A26","x-twitter-growth","X\u002FTwitter growth engine for building audience, crafting viral content, and analyzing engagement. Use when the user wants to grow on X\u002FTwitter, write tweets or threads, analyze their X profile, research competitors on X, plan a posting strategy, or optimize engagement. Complements social-content (generic multi-platform) with X-specific depth: algorithm mechanics, thread engineering, reply strategy, profile optimization, and competitive intelligence via web search.","https:\u002F\u002Fgithub.com\u002Flevalencia\u002Fagent-god-mode\u002Fblob\u002Fmain\u002Forganized-skills\u002Fx-twitter-growth\u002FSKILL.md",[],[139,140,141,142,143,144,145,146,147,148,149,150,151,152,153,154,155,156,157,158],"twitter","x twitter growth","growth","competitive intelligence","search","analyzing","plan","marketing","web search","competitors","analyze","write","optimize","social","intelligence","viral","growth engine","mechanics","grow","competitive",{"skillNo":160,"name":161,"nameZh":6,"description":162,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":163,"categories":164,"keywords":165,"publishedAt":37},"01M6EM3FQNPYNKPC4CV9TCVNGD","what-if-oracle","Run structured What-If scenario analysis with multi-branch possibility exploration. Use this skill when the user asks speculative questions like \"what if...\", \"what would happen if...\", \"what are the possibilities\", \"explore scenarios\", \"scenario analysis\", \"possibility space\", \"what could go wrong\", \"best case \u002F worst case\", \"risk analysis\", \"contingency planning\", \"strategic options\", or any question about uncertain futures. Also trigger when the user faces a fork-in-the-road decision, wants to stress-test an idea, or needs to think through consequences before committing.","https:\u002F\u002Fgithub.com\u002Flevalencia\u002Fagent-god-mode\u002Fblob\u002Fmain\u002Forganized-skills\u002Fwhat-if-oracle\u002FSKILL.md",[],[166,167,168,169,170,171,36,172,173,174,175,176,32,177,178,179,180,181,182,183],"oracle","what if oracle","test","planning","ux","futures","analysis","explore","decision","branch","question","exploration","options","stress-test","strategies","trigger","case","multi",{"skillNo":185,"name":186,"nameZh":6,"description":187,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":188,"categories":189,"keywords":193,"publishedAt":37},"01M6EM08C06RGDYCJ86HAPK0FF","vercel-react-best-practices","React and Next.js performance optimization guidelines from Vercel Engineering. This skill should be used when writing, reviewing, or refactoring React\u002FNext.js code to ensure optimal performance patterns. Triggers on tasks involving React components, Next.js pages, data fetching, bundle optimization, or performance improvements.","https:\u002F\u002Fgithub.com\u002Flevalencia\u002Fagent-god-mode\u002Fblob\u002Fmain\u002Forganized-skills\u002Fvercel-react-best-practices\u002FSKILL.md",[190],{"categoryNo":191,"categoryName":192,"taxonomyType":104,"taxonomyTypeDesc":105},"01JBSEEDCAT000000000000009","前端开发",[194,195,196,197,198,199,200,201,202,203,204,205,206,118,207,208,209,210,211,127],"react","vercel react best practices","best practices","react best practices","vercel","writing","performance","components","react components","guidelines","tasks","code","Optimization","Next.js","refactoring","performance optimization","next","pages",{"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":228,"publishedAt":37},"01M6EM00S13326QM08DTM94J6Z","venue-templates","Access comprehensive LaTeX templates, formatting requirements, and submission guidelines for major scientific publication venues (Nature, Science, PLOS, IEEE, ACM), academic conferences (NeurIPS, ICML, CVPR, CHI), research posters, and grant proposals (NSF, NIH, DOE, DARPA). This skill should be used when preparing manuscripts for journal submission, conference papers, research posters, or grant proposals and need venue-specific formatting requirements and templates.","https:\u002F\u002Fgithub.com\u002Flevalencia\u002Fagent-god-mode\u002Fblob\u002Fmain\u002Forganized-skills\u002Fvenue-templates\u002FSKILL.md",[218,221,224,225],{"categoryNo":219,"categoryName":220,"taxonomyType":104,"taxonomyTypeDesc":105},"01JBSEEDCAT000000000000018","写作与文案",{"categoryNo":222,"categoryName":223,"taxonomyType":104,"taxonomyTypeDesc":105},"01JBSEEDCAT000000000000021","资料检索与研究",{"categoryNo":107,"categoryName":108,"taxonomyType":104,"taxonomyTypeDesc":105},{"categoryNo":226,"categoryName":227,"taxonomyType":112,"taxonomyTypeDesc":113},"01JBSEEDCAT000000000000036","内容创作者",[119,229,230,203,231,232,233,234,235,236,237,150,238,239,240,241,242,243,94,244],"venue templates","research","NeurIPS","ICML","LaTeX","science","Bash","access","read","edit","proposals","Academic","requirements","formatting","journal","chi"]