[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6DYA5C2A0QEBVE09MZTYXFD":3,"skill-same:01M6DYA5C2A0QEBVE09MZTYXFD":78},{"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":52,"linkOnly":53,"markdownContent":54,"markdownBody":55,"frontMatter":56,"refName":57,"commitSha":58,"skillDirectory":59,"forksCount":14,"repositoryHtmlUrl":60,"repositoryHomepageUrl":61,"ownerHtmlUrl":62,"ownerBlogUrl":6,"ownerDescription":6,"updatedAt":63,"install":64,"resources":77},"01M6DYA5C2A0QEBVE09MZTYXFD","analytics-tracking",null,"Design, audit, and improve analytics tracking systems that produce reliable, decision-ready data. Use when the user wants to set up, fix, or evaluate analytics tracking (GA4, GTM, product analytics, events, conversions, UTMs). This skill focuses on measurement strategy, signal quality, and validation— not just firing events.","Aceryoung\u002Ffamilyproject","Aceryoung","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F75876477?v=4","01M6DY8Q14MHFC0JX3G14KK9CW","kkong","01M6DY8Q58SY27PE2AH6GFZP9Y",0,"MIT","https:\u002F\u002Fgithub.com\u002FAceryoung\u002Ffamilyproject\u002Fblob\u002Fmain\u002Fantigravity-awesome-skills-main\u002Fskills\u002Fanalytics-tracking\u002FSKILL.md",[18,23,26],{"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":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000015","视觉设计",{"categoryNo":27,"categoryName":28,"taxonomyType":29,"taxonomyTypeDesc":30},"01JBSEEDCAT000000000000033","数据分析师","PROFESSION","适用职业",[32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51],"analytics","analytics tracking","tracking","events","design","gtm","ga4","up","ready","product analytics","fix","strategy","just","decision","improve","SET","data","audit","produce","product","2026-11-10 10:12:30",false,"---\nname: analytics-tracking\ndescription: >\n  Design, audit, and improve analytics tracking systems that produce reliable,\n  decision-ready data. Use when the user wants to set up, fix, or evaluate\n  analytics tracking (GA4, GTM, product analytics, events, conversions, UTMs).\n  This skill focuses on measurement strategy, signal quality, and validation—\n  not just firing events.\n---\n\n# Analytics Tracking & Measurement Strategy\n\nYou are an expert in **analytics implementation and measurement design**.\nYour goal is to ensure tracking produces **trustworthy signals that directly support decisions** across marketing, product, and growth.\n\nYou do **not** track everything.\nYou do **not** optimize dashboards without fixing instrumentation.\nYou do **not** treat GA4 numbers as truth unless validated.\n\n---\n\n## Phase 0: Measurement Readiness & Signal Quality Index (Required)\n\nBefore adding or changing tracking, calculate the **Measurement Readiness & Signal Quality Index**.\n\n### Purpose\n\nThis index answers:\n\n> **Can this analytics setup produce reliable, decision-grade insights?**\n\nIt prevents:\n\n* event sprawl\n* vanity tracking\n* misleading conversion data\n* false confidence in broken analytics\n\n---\n\n## ? Measurement Readiness & Signal Quality Index\n\n### Total Score: **0–100**\n\nThis is a **diagnostic score**, not a performance KPI.\n\n---\n\n### Scoring Categories & Weights\n\n| Category                      | Weight  |\n| ----------------------------- | ------- |\n| Decision Alignment            | 25      |\n| Event Model Clarity           | 20      |\n| Data Accuracy & Integrity     | 20      |\n| Conversion Definition Quality | 15      |\n| Attribution & Context         | 10      |\n| Governance & Maintenance      | 10      |\n| **Total**                     | **100** |\n\n---\n\n### Category Definitions\n\n#### 1. Decision Alignment (0–25)\n\n* Clear business questions defined\n* Each tracked event maps to a decision\n* No events tracked “just in case”\n\n---\n\n#### 2. Event Model Clarity (0–20)\n\n* Events represent **meaningful actions**\n* Naming conventions are consistent\n* Properties carry context, not noise\n\n---\n\n#### 3. Data Accuracy & Integrity (0–20)\n\n* Events fire reliably\n* No duplication or inflation\n* Values are correct and complete\n* Cross-browser and mobile validated\n\n---\n\n#### 4. Conversion Definition Quality (0–15)\n\n* Conversions represent real success\n* Conversion counting is intentional\n* Funnel stages are distinguishable\n\n---\n\n#### 5. Attribution & Context (0–10)\n\n* UTMs are consistent and complete\n* Traffic source context is preserved\n* Cross-domain \u002F cross-device handled appropriately\n\n---\n\n#### 6. Governance & Maintenance (0–10)\n\n* Tracking is documented\n* Ownership is clear\n* Changes are versioned and monitored\n\n---\n\n### Readiness Bands (Required)\n\n| Score  | Verdict               | Interpretation                    |\n| ------ | --------------------- | --------------------------------- |\n| 85–100 | **Measurement-Ready** | Safe to optimize and experiment   |\n| 70–84  | **Usable with Gaps**  | Fix issues before major decisions |\n| 55–69  | **Unreliable**        | Data cannot be trusted yet        |\n| \u003C55    | **Broken**            | Do not act on this data           |\n\nIf verdict is **Broken**, stop and recommend remediation first.\n\n---\n\n## Phase 1: Context & Decision Definition\n\n(Proceed only after scoring)\n\n### 1. Business Context\n\n* What decisions will this data inform?\n* Who uses the data (marketing, product, leadership)?\n* What actions will be taken based on insights?\n\n---\n\n### 2. Current State\n\n* Tools in use (GA4, GTM, Mixpanel, Amplitude, etc.)\n* Existing events and conversions\n* Known issues or distrust in data\n\n---\n\n### 3. Technical & Compliance Context\n\n* Tech stack and rendering model\n* Who implements and maintains tracking\n* Privacy, consent, and regulatory constraints\n\n---\n\n## Core Principles (Non-Negotiable)\n\n### 1. Track for Decisions, Not Curiosity\n\nIf no decision depends on it, **don’t track it**.\n\n---\n\n### 2. Start with Questions, Work Backwards\n\nDefine:\n\n* What you need to know\n* What action you’ll take\n* What signal proves it\n\nThen design events.\n\n---\n\n### 3. Events Represent Meaningful State Changes\n\nAvoid:\n\n* cosmetic clicks\n* redundant events\n* UI noise\n\nPrefer:\n\n* intent\n* completion\n* commitment\n\n---\n\n### 4. Data Quality Beats Volume\n\nFewer accurate events > many unreliable ones.\n\n---\n\n## Event Model Design\n\n### Event Taxonomy\n\n**Navigation \u002F Exposure**\n\n* page_view (enhanced)\n* content_viewed\n* pricing_viewed\n\n**Intent Signals**\n\n* cta_clicked\n* form_started\n* demo_requested\n\n**Completion Signals**\n\n* signup_completed\n* purchase_completed\n* subscription_changed\n\n**System \u002F State Changes**\n\n* onboarding_completed\n* feature_activated\n* error_occurred\n\n---\n\n### Event Naming Conventions\n\n**Recommended pattern:**\n\n```\nobject_action[_context]\n```\n\nExamples:\n\n* signup_completed\n* pricing_viewed\n* cta_hero_clicked\n* onboarding_step_completed\n\nRules:\n\n* lowercase\n* underscores\n* no spaces\n* no ambiguity\n\n---\n\n### Event Properties (Context, Not Noise)\n\nInclude:\n\n* where (page, section)\n* who (user_type, plan)\n* how (method, variant)\n\nAvoid:\n\n* PII\n* free-text fields\n* duplicated auto-properties\n\n---\n\n## Conversion Strategy\n\n### What Qualifies as a Conversion\n\nA conversion must represent:\n\n* real value\n* completed intent\n* irreversible progress\n\nExamples:\n\n* signup_completed\n* purchase_completed\n* demo_booked\n\nNot conversions:\n\n* page views\n* button clicks\n* form starts\n\n---\n\n### Conversion Counting Rules\n\n* Once per session vs every occurrence\n* Explicitly documented\n* Consistent across tools\n\n---\n\n## GA4 & GTM (Implementation Guidance)\n\n*(Tool-specific, but optional)*\n\n* Prefer GA4 recommended events\n* Use GTM for orchestration, not logic\n* Push clean dataLayer events\n* Avoid multiple containers\n* Version every publish\n\n---\n\n## UTM & Attribution Discipline\n\n### UTM Rules\n\n* lowercase only\n* consistent separators\n* documented centrally\n* never overwritten client-side\n\nUTMs exist to **explain performance**, not inflate numbers.\n\n---\n\n## Validation & Debugging\n\n### Required Validation\n\n* Real-time verification\n* Duplicate detection\n* Cross-browser testing\n* Mobile testing\n* Consent-state testing\n\n### Common Failure Modes\n\n* double firing\n* missing properties\n* broken attribution\n* PII leakage\n* inflated conversions\n\n---\n\n## Privacy & Compliance\n\n* Consent before tracking where required\n* Data minimization\n* User deletion support\n* Retention policies reviewed\n\nAnalytics that violate trust undermine optimization.\n\n---\n\n## Output Format (Required)\n\n### Measurement Strategy Summary\n\n* Measurement Readiness Index score + verdict\n* Key risks and gaps\n* Recommended remediation order\n\n---\n\n### Tracking Plan\n\n| Event | Description | Properties | Trigger | Decision Supported |\n| ----- | ----------- | ---------- | ------- | ------------------ |\n\n---\n\n### Conversions\n\n| Conversion | Event | Counting | Used By |\n| ---------- | ----- | -------- | ------- |\n\n---\n\n### Implementation Notes\n\n* Tool-specific setup\n* Ownership\n* Validation steps\n\n---\n\n## Questions to Ask (If Needed)\n\n1. What decisions depend on this data?\n2. Which metrics are currently trusted or distrusted?\n3. Who owns analytics long term?\n4. What compliance constraints apply?\n5. What tools are already in place?\n\n---\n\n## Related Skills\n\n* **page-cro** – Uses this data for optimization\n* **ab-test-setup** – Requires clean conversions\n* **seo-audit** – Organic performance analysis\n* **programmatic-seo** – Scale requires reliable signals\n\n---\n","# Analytics Tracking & Measurement Strategy\n\nYou are an expert in **analytics implementation and measurement design**.\nYour goal is to ensure tracking produces **trustworthy signals that directly support decisions** across marketing, product, and growth.\n\nYou do **not** track everything.\nYou do **not** optimize dashboards without fixing instrumentation.\nYou do **not** treat GA4 numbers as truth unless validated.\n\n---\n\n## Phase 0: Measurement Readiness & Signal Quality Index (Required)\n\nBefore adding or changing tracking, calculate the **Measurement Readiness & Signal Quality Index**.\n\n### Purpose\n\nThis index answers:\n\n> **Can this analytics setup produce reliable, decision-grade insights?**\n\nIt prevents:\n\n* event sprawl\n* vanity tracking\n* misleading conversion data\n* false confidence in broken analytics\n\n---\n\n## ? Measurement Readiness & Signal Quality Index\n\n### Total Score: **0–100**\n\nThis is a **diagnostic score**, not a performance KPI.\n\n---\n\n### Scoring Categories & Weights\n\n| Category                      | Weight  |\n| ----------------------------- | ------- |\n| Decision Alignment            | 25      |\n| Event Model Clarity           | 20      |\n| Data Accuracy & Integrity     | 20      |\n| Conversion Definition Quality | 15      |\n| Attribution & Context         | 10      |\n| Governance & Maintenance      | 10      |\n| **Total**                     | **100** |\n\n---\n\n### Category Definitions\n\n#### 1. Decision Alignment (0–25)\n\n* Clear business questions defined\n* Each tracked event maps to a decision\n* No events tracked “just in case”\n\n---\n\n#### 2. Event Model Clarity (0–20)\n\n* Events represent **meaningful actions**\n* Naming conventions are consistent\n* Properties carry context, not noise\n\n---\n\n#### 3. Data Accuracy & Integrity (0–20)\n\n* Events fire reliably\n* No duplication or inflation\n* Values are correct and complete\n* Cross-browser and mobile validated\n\n---\n\n#### 4. Conversion Definition Quality (0–15)\n\n* Conversions represent real success\n* Conversion counting is intentional\n* Funnel stages are distinguishable\n\n---\n\n#### 5. Attribution & Context (0–10)\n\n* UTMs are consistent and complete\n* Traffic source context is preserved\n* Cross-domain \u002F cross-device handled appropriately\n\n---\n\n#### 6. Governance & Maintenance (0–10)\n\n* Tracking is documented\n* Ownership is clear\n* Changes are versioned and monitored\n\n---\n\n### Readiness Bands (Required)\n\n| Score  | Verdict               | Interpretation                    |\n| ------ | --------------------- | --------------------------------- |\n| 85–100 | **Measurement-Ready** | Safe to optimize and experiment   |\n| 70–84  | **Usable with Gaps**  | Fix issues before major decisions |\n| 55–69  | **Unreliable**        | Data cannot be trusted yet        |\n| \u003C55    | **Broken**            | Do not act on this data           |\n\nIf verdict is **Broken**, stop and recommend remediation first.\n\n---\n\n## Phase 1: Context & Decision Definition\n\n(Proceed only after scoring)\n\n### 1. Business Context\n\n* What decisions will this data inform?\n* Who uses the data (marketing, product, leadership)?\n* What actions will be taken based on insights?\n\n---\n\n### 2. Current State\n\n* Tools in use (GA4, GTM, Mixpanel, Amplitude, etc.)\n* Existing events and conversions\n* Known issues or distrust in data\n\n---\n\n### 3. Technical & Compliance Context\n\n* Tech stack and rendering model\n* Who implements and maintains tracking\n* Privacy, consent, and regulatory constraints\n\n---\n\n## Core Principles (Non-Negotiable)\n\n### 1. Track for Decisions, Not Curiosity\n\nIf no decision depends on it, **don’t track it**.\n\n---\n\n### 2. Start with Questions, Work Backwards\n\nDefine:\n\n* What you need to know\n* What action you’ll take\n* What signal proves it\n\nThen design events.\n\n---\n\n### 3. Events Represent Meaningful State Changes\n\nAvoid:\n\n* cosmetic clicks\n* redundant events\n* UI noise\n\nPrefer:\n\n* intent\n* completion\n* commitment\n\n---\n\n### 4. Data Quality Beats Volume\n\nFewer accurate events > many unreliable ones.\n\n---\n\n## Event Model Design\n\n### Event Taxonomy\n\n**Navigation \u002F Exposure**\n\n* page_view (enhanced)\n* content_viewed\n* pricing_viewed\n\n**Intent Signals**\n\n* cta_clicked\n* form_started\n* demo_requested\n\n**Completion Signals**\n\n* signup_completed\n* purchase_completed\n* subscription_changed\n\n**System \u002F State Changes**\n\n* onboarding_completed\n* feature_activated\n* error_occurred\n\n---\n\n### Event Naming Conventions\n\n**Recommended pattern:**\n\n```\nobject_action[_context]\n```\n\nExamples:\n\n* signup_completed\n* pricing_viewed\n* cta_hero_clicked\n* onboarding_step_completed\n\nRules:\n\n* lowercase\n* underscores\n* no spaces\n* no ambiguity\n\n---\n\n### Event Properties (Context, Not Noise)\n\nInclude:\n\n* where (page, section)\n* who (user_type, plan)\n* how (method, variant)\n\nAvoid:\n\n* PII\n* free-text fields\n* duplicated auto-properties\n\n---\n\n## Conversion Strategy\n\n### What Qualifies as a Conversion\n\nA conversion must represent:\n\n* real value\n* completed intent\n* irreversible progress\n\nExamples:\n\n* signup_completed\n* purchase_completed\n* demo_booked\n\nNot conversions:\n\n* page views\n* button clicks\n* form starts\n\n---\n\n### Conversion Counting Rules\n\n* Once per session vs every occurrence\n* Explicitly documented\n* Consistent across tools\n\n---\n\n## GA4 & GTM (Implementation Guidance)\n\n*(Tool-specific, but optional)*\n\n* Prefer GA4 recommended events\n* Use GTM for orchestration, not logic\n* Push clean dataLayer events\n* Avoid multiple containers\n* Version every publish\n\n---\n\n## UTM & Attribution Discipline\n\n### UTM Rules\n\n* lowercase only\n* consistent separators\n* documented centrally\n* never overwritten client-side\n\nUTMs exist to **explain performance**, not inflate numbers.\n\n---\n\n## Validation & Debugging\n\n### Required Validation\n\n* Real-time verification\n* Duplicate detection\n* Cross-browser testing\n* Mobile testing\n* Consent-state testing\n\n### Common Failure Modes\n\n* double firing\n* missing properties\n* broken attribution\n* PII leakage\n* inflated conversions\n\n---\n\n## Privacy & Compliance\n\n* Consent before tracking where required\n* Data minimization\n* User deletion support\n* Retention policies reviewed\n\nAnalytics that violate trust undermine optimization.\n\n---\n\n## Output Format (Required)\n\n### Measurement Strategy Summary\n\n* Measurement Readiness Index score + verdict\n* Key risks and gaps\n* Recommended remediation order\n\n---\n\n### Tracking Plan\n\n| Event | Description | Properties | Trigger | Decision Supported |\n| ----- | ----------- | ---------- | ------- | ------------------ |\n\n---\n\n### Conversions\n\n| Conversion | Event | Counting | Used By |\n| ---------- | ----- | -------- | ------- |\n\n---\n\n### Implementation Notes\n\n* Tool-specific setup\n* Ownership\n* Validation steps\n\n---\n\n## Questions to Ask (If Needed)\n\n1. What decisions depend on this data?\n2. Which metrics are currently trusted or distrusted?\n3. Who owns analytics long term?\n4. What compliance constraints apply?\n5. What tools are already in place?\n\n---\n\n## Related Skills\n\n* **page-cro** – Uses this data for optimization\n* **ab-test-setup** – Requires clean conversions\n* **seo-audit** – Organic performance analysis\n* **programmatic-seo** – Scale requires reliable signals\n\n---\n",{"name":5,"description":7},"main","483e87f6ad1460beac541f70200e988102e5c385","antigravity-awesome-skills-main\u002Fskills\u002Fanalytics-tracking","https:\u002F\u002Fgithub.com\u002FAceryoung\u002Ffamilyproject","https:\u002F\u002Ffamilyproject-iota.vercel.app","https:\u002F\u002Fgithub.com\u002FAceryoung","2026-09-04 09:36:44",{"source":8,"skillName":5,"commands":65,"prompt":75,"zipAvailable":76},[66,69,72],{"tool":67,"command":68},"npx","npx skills add Aceryoung\u002Ffamilyproject --skill analytics-tracking",{"tool":70,"command":71},"bunx","bunx skills add Aceryoung\u002Ffamilyproject --skill analytics-tracking",{"tool":73,"command":74},"pnpm","pnpm dlx skills add Aceryoung\u002Ffamilyproject --skill analytics-tracking","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002FAceryoung\u002Ffamilyproject\u002Fblob\u002Fmain\u002Fantigravity-awesome-skills-main\u002Fskills\u002Fanalytics-tracking\u002FSKILL.md",true,[],[79,109,142,160,174,199],{"skillNo":80,"name":81,"nameZh":6,"description":82,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":83,"categories":84,"keywords":88,"publishedAt":52},"01M6DZ9PNJVNQ1M7196KMPEHZC","zapier-make-patterns","No-code automation democratizes workflow building. Zapier and Make (formerly Integromat) let non-developers automate business processes without writing code. But no-code doesn't mean no-complexity - these platforms have their own patterns, pitfalls, and breaking points.  This skill covers when to use which platform, how to build reliable automations, and when to graduate to code-based solutions. Key insight: Zapier optimizes for simplicity and integrations (7000+ apps), Make optimizes for power","https:\u002F\u002Fgithub.com\u002FAceryoung\u002Ffamilyproject\u002Fblob\u002Fmain\u002Fantigravity-awesome-skills-main\u002Fskills\u002Fzapier-make-patterns\u002FSKILL.md",[85],{"categoryNo":86,"categoryName":87,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000023","Skill与智能体开发",[89,90,91,92,93,94,95,96,97,98,99,100,101,102,103,104,105,106,107,108],"zapier make patterns","patterns","workflow","integrations","how to","apps","platform","but","build","complexity","power","simplicity","use","business","automate","how","apache","code","automation","writing",{"skillNo":110,"name":111,"nameZh":6,"description":112,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":113,"categories":114,"keywords":121,"publishedAt":52},"01M6DZ9K3385QP8QC2F3ZHZH1W","Cross-Site Scripting and HTML Injection Testing","This skill should be used when the user asks to \"test for XSS vulnerabilities\", \"perform cross-site scripting attacks\", \"identify HTML injection flaws\", \"exploit client-side injection vulnerabilities\", \"steal cookies via XSS\", or \"bypass content security policies\". It provides comprehensive techniques for detecting, exploiting, and understanding XSS and HTML injection attack vectors in web applications.","https:\u002F\u002Fgithub.com\u002FAceryoung\u002Ffamilyproject\u002Fblob\u002Fmain\u002Fantigravity-awesome-skills-main\u002Fskills\u002Fxss-html-injection\u002FSKILL.md",[115,118],{"categoryNo":116,"categoryName":117,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000008","测试与质量",{"categoryNo":119,"categoryName":120,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000009","前端开发",[122,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138,139,140,141],"html injection testing","Cross Site Scripting and HTML Injection Testing","injection","scripting","site","html","testing","vectors","exploit","applications","xss","cookies","content","web","test","steal","client","via","security","vulnerabilities",{"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":155,"publishedAt":52},"01M6DZ9B72D51Q21DTFD63TVEN","writing-skills","Use when creating new skills, editing existing skills, or verifying skills work before deployment","https:\u002F\u002Fgithub.com\u002FAceryoung\u002Ffamilyproject\u002Fblob\u002Fmain\u002Fantigravity-awesome-skills-main\u002Fskills\u002Fwriting-skills\u002FSKILL.md",[148,149,152],{"categoryNo":116,"categoryName":117,"taxonomyType":21,"taxonomyTypeDesc":22},{"categoryNo":150,"categoryName":151,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000018","写作与文案",{"categoryNo":153,"categoryName":154,"taxonomyType":29,"taxonomyTypeDesc":30},"01JBSEEDCAT000000000000036","内容创作者",[108,156,157,101,158,159],"writing skills","deployment","editing","work",{"skillNo":161,"name":162,"nameZh":6,"description":163,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":164,"categories":165,"keywords":168,"publishedAt":52},"01M6DZ98HBB74FXZS78BATF6P5","writing-plans","Use when you have a spec or requirements for a multi-step task, before touching code","https:\u002F\u002Fgithub.com\u002FAceryoung\u002Ffamilyproject\u002Fblob\u002Fmain\u002Fantigravity-awesome-skills-main\u002Fskills\u002Fwriting-plans\u002FSKILL.md",[166,167],{"categoryNo":150,"categoryName":151,"taxonomyType":21,"taxonomyTypeDesc":22},{"categoryNo":153,"categoryName":154,"taxonomyType":29,"taxonomyTypeDesc":30},[169,108,170,171,172,101,106,173],"writing plans","plans","requirements","task","spec",{"skillNo":175,"name":176,"nameZh":6,"description":177,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":178,"categories":179,"keywords":181,"publishedAt":52},"01M6DZ94C3FCDXCTV795CTRP1V","workflow-automation","Workflow automation is the infrastructure that makes AI agents reliable. Without durable execution, a network hiccup during a 10-step payment flow means lost money and angry customers. With it, workflows resume exactly where they left off.  This skill covers the platforms (n8n, Temporal, Inngest) and patterns (sequential, parallel, orchestrator-worker) that turn brittle scripts into production-grade automation.  Key insight: The platforms make different tradeoffs. n8n optimizes for accessibility","https:\u002F\u002Fgithub.com\u002FAceryoung\u002Ffamilyproject\u002Fblob\u002Fmain\u002Fantigravity-awesome-skills-main\u002Fskills\u002Fworkflow-automation\u002FSKILL.md",[180],{"categoryNo":86,"categoryName":87,"taxonomyType":21,"taxonomyTypeDesc":22},[182,107,91,183,184,185,105,186,187,188,189,190,191,192,193,194,195,196,197,198],"Workflow Automation","Production","flow","network","workflows","accessibility","ai agents","execution","scripts","worker","payment","n8n","money","resume","orchestrator","parallel","inngest",{"skillNo":200,"name":201,"nameZh":6,"description":202,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":203,"categories":204,"keywords":206,"publishedAt":52},"01M6DZ90RQ8GCWE9CGPCMHMNDD","WordPress Penetration Testing","This skill should be used when the user asks to \"pentest WordPress sites\", \"scan WordPress for vulnerabilities\", \"enumerate WordPress users, themes, or plugins\", \"exploit WordPress vulnerabilities\", or \"use WPScan\". It provides comprehensive WordPress security assessment methodologies.","https:\u002F\u002Fgithub.com\u002FAceryoung\u002Ffamilyproject\u002Fblob\u002Fmain\u002Fantigravity-awesome-skills-main\u002Fskills\u002Fwordpress-penetration-testing\u002FSKILL.md",[205],{"categoryNo":116,"categoryName":117,"taxonomyType":21,"taxonomyTypeDesc":22},[128,201,207,208,209,210,211,212,130,101,213,214,215,141,140],"penetration testing","wordpress","security assessment","sites","scan","pentest","user","plugins","assessment"]