[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6CQY3C1B2R1PEWMTYN5PRF0":3,"skill-same:01M6CQY3C1B2R1PEWMTYN5PRF0":84},{"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":23,"publishedAt":53,"linkOnly":54,"markdownContent":55,"markdownBody":56,"frontMatter":57,"refName":60,"commitSha":61,"skillDirectory":62,"forksCount":63,"repositoryHtmlUrl":64,"repositoryHomepageUrl":65,"ownerHtmlUrl":66,"ownerBlogUrl":67,"ownerDescription":68,"updatedAt":69,"install":70,"resources":83},"01M6CQY3C1B2R1PEWMTYN5PRF0","ads-attribution",null,"Cross-platform attribution health audit covering AdAttributionKit (iOS view-through 24h post-impression, WWDC 2025 configurable windows), GA4 attribution models (data-driven vs last-click), Consent Mode V2 enforcement, server-side attribution stitching, MMP integration health, and cross-device \u002F cross-platform attribution. Use when user says attribution audit, attribution model, AdAttributionKit, AAK, view-through attribution, GA4 attribution, Consent Mode V2, conversion window, attribution window, MMP audit, AppsFlyer audit, Adjust audit, Branch audit, Singular audit, cross-device attribution, or cross-platform attribution.","shenxingy\u002FClade","shenxingy","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F89829751?v=4","01M6CQXHTV3WQZJMG0JXD93MEK","Xingyu (Alex) Shen","01M6CQXHYCTGPJ5HD8Z7MD4Q5P",10,"MIT","https:\u002F\u002Fgithub.com\u002Fshenxingy\u002FClade\u002Fblob\u002Fmain\u002Fconfigs\u002Fskills\u002Fads-attribution\u002FSKILL.md",[18],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000030","开发工程师","PROFESSION","适用职业",[24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52],"attribution","ads","ads attribution","enforcement","2026","when","window","data-driven","mode","2025","false","click","attribution model","ga4","models","health audit","conversion","windows","use","view","branch","model","health","data","ios","server","integration","audit","code","2026-11-10 10:12:30",false,"---\nname: ads-attribution\ndescription: \"Cross-platform attribution health audit covering AdAttributionKit (iOS view-through 24h post-impression, WWDC 2025 configurable windows), GA4 attribution models (data-driven vs last-click), Consent Mode V2 enforcement, server-side attribution stitching, MMP integration health, and cross-device \u002F cross-platform attribution. Use when user says attribution audit, attribution model, AdAttributionKit, AAK, view-through attribution, GA4 attribution, Consent Mode V2, conversion window, attribution window, MMP audit, AppsFlyer audit, Adjust audit, Branch audit, Singular audit, cross-device attribution, or cross-platform attribution.\"\nuser_invocable: false\ntested_date: 2026-05-17\ntested_with: claude-code v2.x\n---\n\n# Cross-Platform Attribution Health Audit\n\nAttribution decay is the silent revenue killer of 2026 — Consent Mode V2 EEA\nenforcement (Jul 21, 2025), iOS ATT, SKAdNetwork → AdAttributionKit migration,\nand the death of third-party cookies have moved every advertiser's\nattribution signal toward modeled, server-side, first-party data. Misaligned\nattribution windows or unverified Consent Mode setups will mis-attribute\n15-40% of conversions and silently waste budget.\n\n## Process\n\n1. Collect current attribution stack: GA4 property ID, Google Ads conversion\n   actions, Meta CAPI config, Apple Ads \u002F AdAttributionKit registration,\n   MMP dashboard (AppsFlyer \u002F Adjust \u002F Branch \u002F Singular), any sGTM container\n2. Read `ads\u002Freferences\u002Fconversion-tracking.md` for the cross-platform\n   tracking baseline\n3. Evaluate attribution health per surface (web, iOS app, Android app,\n   server-side)\n4. Score each surface PASS \u002F WARNING \u002F FAIL\n5. Generate findings report with cross-channel attribution map and remediation\n   plan\n\n## What to Analyze\n\n### iOS Attribution (AdAttributionKit + ATT)\n\n- **AdAttributionKit registered** with Apple Ads (post-Apr 10, 2025 cutover);\n  registration creates dual attribution with SKAdNetwork (SKAN v1-3)\n- **View-through attribution** active — 24h post-impression view window\n  configured on Apple Ads campaigns where applicable\n- **Configurable attribution windows** (WWDC 2025): per-campaign window\n  customization audited; overlapping re-engagement windows used for\n  subscription \u002F re-acquisition campaigns\n- **Country code in postbacks** (WWDC 2025): enabled if you need geo\n  attribution detail\n- **ATT (App Tracking Transparency) opt-in rate** monitored; \u003C30% opt-in\n  means heavy reliance on SKAN\u002FAAK + privacy threshold\n- **Privacy threshold awareness** — low-volume campaigns may receive null\n  postbacks; campaign consolidation recommended below 1k installs\u002Fweek\n\n### Web Attribution (GA4 + Google Ads + Meta CAPI)\n\n- **GA4 attribution model**: Data-Driven (default for properties with enough\n  data) vs Last-Click — confirm setting is intentional, not residue from a\n  pre-2026 migration\n- **Google Ads attribution model**: Data-Driven default; per-conversion\n  override allowed but audit any Last-Click overrides for justification\n- **Cross-channel attribution** in GA4: confirm Google Ads, Meta, LinkedIn,\n  TikTok, Microsoft are integrated as platforms with consent + auto-tagging\n- **Conversion windows per channel** appropriate to sales cycle:\n  - E-commerce: 7-day click, 1-day view\n  - B2B \u002F lead gen: 30-90 day click, no view\n  - SaaS subscription: 30 day click, 1-day view, plus offline conversion\n    import for the activation event\n- **Conversion lag analysis** run quarterly to validate window choice\n\n### Consent Mode V2 (EU\u002FEEA + recommended globally)\n\n- **Consent Mode V2 active** (enforcement began Jul 21, 2025 for EEA\u002FUK)\n- **Advanced Mode** (not Basic) — Basic loses ~25% of EEA conversion signal\n- **700+ ad clicks\u002Fday over 7 days per country\u002Fdomain** threshold met for\n  Advanced Mode behavioral modeling to activate\n- **Signal recovery measured**: aim 15-25% conversion recovery vs pre-CMV2\n  baseline\n- **Consent banner** correctly reads CMV2 signals (not just GDPR boilerplate)\n\n### Server-Side Attribution Stitching\n\n- **First-party server logs** stored with `user_id` + `event_id` + timestamp\n  + platform tag for every conversion event\n- **MMP + first-party stitching**: MMP (AppsFlyer \u002F Adjust \u002F Branch \u002F\n  Singular) receives both client-side AND server-side events with shared\n  `event_id` for deduplication\n- **Server-side conversion import** to Google Ads (offline conversion import)\n  and Meta (CAPI) within 72h of the conversion event\n- **Hash quality**: email \u002F phone fields SHA-256 hashed and lowercased\n  before send; cross-platform hashing convention consistent\n- **Deduplication rate** ≥90% (matched event_id between client + server)\n\n### MMP Health (Mobile Apps)\n\n- **MMP integrated** — AppsFlyer \u002F Adjust \u002F Branch \u002F Singular set up before\n  any paid campaigns launched\n- **Apple Ads connected as a partner** in MMP dashboard\n- **Post-install events sent back** to Apple Ads, Google UAC, Meta App\n  Campaigns, TikTok (enables Maximize Conversions and ROAS bidding)\n- **Event quality**: purchase, subscription_start, trial_start, or other\n  revenue events tracked (not just install → registration)\n- **Postback configuration**: SKAN\u002FAAK conversion values map to meaningful\n  user actions\n\n### Cross-Device & Cross-Platform Attribution\n\n- **Customer Match** lists synced to Google Ads, Meta (Customer File CA),\n  LinkedIn Matched Audiences, TikTok Customer File for cross-device stitching\n- **Enhanced Conversions** active for Google Ads (hashed first-party data,\n  ~10% uplift on properly-implemented setups)\n- **CAPI customer_information parameters** (`em`, `ph`, `fn`, `ln`, `ct`,\n  `st`, `zp`, `external_id`) sent server-side to Meta\n- **Privacy-safe identifiers** (Customer Match hashes, GAID\u002FIDFA where\n  permitted) included in conversion exports\n\n## Key Thresholds\n\n| Metric | Pass | Warning | Fail |\n|--------|------|---------|------|\n| GA4 attribution model | Data-Driven | Last-Click (intentional) | Last-Click (residual) |\n| Consent Mode V2 | Advanced + verified | Advanced (unverified) | Basic \u002F Not implemented |\n| EMQ (Meta Purchase) | ≥8.0 | 6.0-7.9 | \u003C6.0 |\n| Event dedup rate | ≥90% | 70-89% | \u003C70% |\n| Server-side \u002F client-side hit ratio | ≥80% | 50-79% | \u003C50% |\n| ATT opt-in (iOS) | ≥30% | 15-29% | \u003C15% (heavy SKAN reliance) |\n| Offline conversion import latency | \u003C24h | 24-72h | >72h |\n| Customer Match list freshness | \u003C7 days | 7-30 days | >30 days |\n\n## Output\n\n### Attribution Health Score\n\n```\nAttribution Health Score: XX\u002F100 (Grade: X)\n\niOS (AdAttributionKit + ATT):    XX\u002F100  ████████░░  (20%)\nWeb (GA4 + Ads + CAPI):           XX\u002F100  ██████████  (30%)\nConsent Mode V2:                  XX\u002F100  █████████░  (15%)\nServer-Side Stitching:            XX\u002F100  ████████░░  (20%)\nMMP Health (mobile):              XX\u002F100  ███████░░░  (10%)\nCross-Device \u002F Customer Match:    XX\u002F100  ██████░░░░  (5%)\n```\n\n### Deliverables\n\n- `ATTRIBUTION-AUDIT.md`: Full surface-by-surface findings\n- Cross-channel attribution map (which platform owns which conversion\n  windows + which events)\n- Modeled vs reported conversion delta (estimated revenue under- or\n  over-attribution)\n- Quick Wins sorted by signal-recovery $ impact\n- Pre-launch checklist for any new platform (Amazon, Apple Ads, TikTok)\n  to ensure attribution is wired before spend begins\n","# Cross-Platform Attribution Health Audit\n\nAttribution decay is the silent revenue killer of 2026 — Consent Mode V2 EEA\nenforcement (Jul 21, 2025), iOS ATT, SKAdNetwork → AdAttributionKit migration,\nand the death of third-party cookies have moved every advertiser's\nattribution signal toward modeled, server-side, first-party data. Misaligned\nattribution windows or unverified Consent Mode setups will mis-attribute\n15-40% of conversions and silently waste budget.\n\n## Process\n\n1. Collect current attribution stack: GA4 property ID, Google Ads conversion\n   actions, Meta CAPI config, Apple Ads \u002F AdAttributionKit registration,\n   MMP dashboard (AppsFlyer \u002F Adjust \u002F Branch \u002F Singular), any sGTM container\n2. Read `ads\u002Freferences\u002Fconversion-tracking.md` for the cross-platform\n   tracking baseline\n3. Evaluate attribution health per surface (web, iOS app, Android app,\n   server-side)\n4. Score each surface PASS \u002F WARNING \u002F FAIL\n5. Generate findings report with cross-channel attribution map and remediation\n   plan\n\n## What to Analyze\n\n### iOS Attribution (AdAttributionKit + ATT)\n\n- **AdAttributionKit registered** with Apple Ads (post-Apr 10, 2025 cutover);\n  registration creates dual attribution with SKAdNetwork (SKAN v1-3)\n- **View-through attribution** active — 24h post-impression view window\n  configured on Apple Ads campaigns where applicable\n- **Configurable attribution windows** (WWDC 2025): per-campaign window\n  customization audited; overlapping re-engagement windows used for\n  subscription \u002F re-acquisition campaigns\n- **Country code in postbacks** (WWDC 2025): enabled if you need geo\n  attribution detail\n- **ATT (App Tracking Transparency) opt-in rate** monitored; \u003C30% opt-in\n  means heavy reliance on SKAN\u002FAAK + privacy threshold\n- **Privacy threshold awareness** — low-volume campaigns may receive null\n  postbacks; campaign consolidation recommended below 1k installs\u002Fweek\n\n### Web Attribution (GA4 + Google Ads + Meta CAPI)\n\n- **GA4 attribution model**: Data-Driven (default for properties with enough\n  data) vs Last-Click — confirm setting is intentional, not residue from a\n  pre-2026 migration\n- **Google Ads attribution model**: Data-Driven default; per-conversion\n  override allowed but audit any Last-Click overrides for justification\n- **Cross-channel attribution** in GA4: confirm Google Ads, Meta, LinkedIn,\n  TikTok, Microsoft are integrated as platforms with consent + auto-tagging\n- **Conversion windows per channel** appropriate to sales cycle:\n  - E-commerce: 7-day click, 1-day view\n  - B2B \u002F lead gen: 30-90 day click, no view\n  - SaaS subscription: 30 day click, 1-day view, plus offline conversion\n    import for the activation event\n- **Conversion lag analysis** run quarterly to validate window choice\n\n### Consent Mode V2 (EU\u002FEEA + recommended globally)\n\n- **Consent Mode V2 active** (enforcement began Jul 21, 2025 for EEA\u002FUK)\n- **Advanced Mode** (not Basic) — Basic loses ~25% of EEA conversion signal\n- **700+ ad clicks\u002Fday over 7 days per country\u002Fdomain** threshold met for\n  Advanced Mode behavioral modeling to activate\n- **Signal recovery measured**: aim 15-25% conversion recovery vs pre-CMV2\n  baseline\n- **Consent banner** correctly reads CMV2 signals (not just GDPR boilerplate)\n\n### Server-Side Attribution Stitching\n\n- **First-party server logs** stored with `user_id` + `event_id` + timestamp\n  + platform tag for every conversion event\n- **MMP + first-party stitching**: MMP (AppsFlyer \u002F Adjust \u002F Branch \u002F\n  Singular) receives both client-side AND server-side events with shared\n  `event_id` for deduplication\n- **Server-side conversion import** to Google Ads (offline conversion import)\n  and Meta (CAPI) within 72h of the conversion event\n- **Hash quality**: email \u002F phone fields SHA-256 hashed and lowercased\n  before send; cross-platform hashing convention consistent\n- **Deduplication rate** ≥90% (matched event_id between client + server)\n\n### MMP Health (Mobile Apps)\n\n- **MMP integrated** — AppsFlyer \u002F Adjust \u002F Branch \u002F Singular set up before\n  any paid campaigns launched\n- **Apple Ads connected as a partner** in MMP dashboard\n- **Post-install events sent back** to Apple Ads, Google UAC, Meta App\n  Campaigns, TikTok (enables Maximize Conversions and ROAS bidding)\n- **Event quality**: purchase, subscription_start, trial_start, or other\n  revenue events tracked (not just install → registration)\n- **Postback configuration**: SKAN\u002FAAK conversion values map to meaningful\n  user actions\n\n### Cross-Device & Cross-Platform Attribution\n\n- **Customer Match** lists synced to Google Ads, Meta (Customer File CA),\n  LinkedIn Matched Audiences, TikTok Customer File for cross-device stitching\n- **Enhanced Conversions** active for Google Ads (hashed first-party data,\n  ~10% uplift on properly-implemented setups)\n- **CAPI customer_information parameters** (`em`, `ph`, `fn`, `ln`, `ct`,\n  `st`, `zp`, `external_id`) sent server-side to Meta\n- **Privacy-safe identifiers** (Customer Match hashes, GAID\u002FIDFA where\n  permitted) included in conversion exports\n\n## Key Thresholds\n\n| Metric | Pass | Warning | Fail |\n|--------|------|---------|------|\n| GA4 attribution model | Data-Driven | Last-Click (intentional) | Last-Click (residual) |\n| Consent Mode V2 | Advanced + verified | Advanced (unverified) | Basic \u002F Not implemented |\n| EMQ (Meta Purchase) | ≥8.0 | 6.0-7.9 | \u003C6.0 |\n| Event dedup rate | ≥90% | 70-89% | \u003C70% |\n| Server-side \u002F client-side hit ratio | ≥80% | 50-79% | \u003C50% |\n| ATT opt-in (iOS) | ≥30% | 15-29% | \u003C15% (heavy SKAN reliance) |\n| Offline conversion import latency | \u003C24h | 24-72h | >72h |\n| Customer Match list freshness | \u003C7 days | 7-30 days | >30 days |\n\n## Output\n\n### Attribution Health Score\n\n```\nAttribution Health Score: XX\u002F100 (Grade: X)\n\niOS (AdAttributionKit + ATT):    XX\u002F100  ████████░░  (20%)\nWeb (GA4 + Ads + CAPI):           XX\u002F100  ██████████  (30%)\nConsent Mode V2:                  XX\u002F100  █████████░  (15%)\nServer-Side Stitching:            XX\u002F100  ████████░░  (20%)\nMMP Health (mobile):              XX\u002F100  ███████░░░  (10%)\nCross-Device \u002F Customer Match:    XX\u002F100  ██████░░░░  (5%)\n```\n\n### Deliverables\n\n- `ATTRIBUTION-AUDIT.md`: Full surface-by-surface findings\n- Cross-channel attribution map (which platform owns which conversion\n  windows + which events)\n- Modeled vs reported conversion delta (estimated revenue under- or\n  over-attribution)\n- Quick Wins sorted by signal-recovery $ impact\n- Pre-launch checklist for any new platform (Amazon, Apple Ads, TikTok)\n  to ensure attribution is wired before spend begins\n",{"name":5,"description":7,"tested_date":58,"tested_with":59,"user_invocable":54},1778976000000,"claude-code v2.x","main","60a901a00f46e71601f58727cb5661f8d3fb6d24","configs\u002Fskills\u002Fads-attribution",6,"https:\u002F\u002Fgithub.com\u002Fshenxingy\u002FClade","https:\u002F\u002Falexshen.dev\u002Fen\u002Fblog\u002Fclade","https:\u002F\u002Fgithub.com\u002Fshenxingy","https:\u002F\u002Falexshen.dev\u002F","Founding Engineer @ Scam AI | ECE @ Duke University | Data Science @ Duke Kunshan University","2026-11-11 10:54:30",{"source":8,"skillName":5,"commands":71,"prompt":81,"zipAvailable":82},[72,75,78],{"tool":73,"command":74},"npx","npx skills add shenxingy\u002FClade --skill ads-attribution",{"tool":76,"command":77},"bunx","bunx skills add shenxingy\u002FClade --skill ads-attribution",{"tool":79,"command":80},"pnpm","pnpm dlx skills add shenxingy\u002FClade --skill ads-attribution","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fshenxingy\u002FClade\u002Fblob\u002Fmain\u002Fconfigs\u002Fskills\u002Fads-attribution\u002FSKILL.md",true,[],[85,108,137,158,183,200],{"skillNo":86,"name":87,"nameZh":6,"description":88,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":89,"categories":90,"keywords":96,"publishedAt":53},"01M6FNPBA3494GF2W7V4MMAKG3","worktree","Create or inspect runtime-adaptive isolated Git workspaces with explicit ownership and delivery routing","https:\u002F\u002Fgithub.com\u002Fshenxingy\u002FClade\u002Fblob\u002Fmain\u002Fplugins\u002Fclade\u002Fskills\u002Fworktree\u002FSKILL.md",[91],{"categoryNo":92,"categoryName":93,"taxonomyType":94,"taxonomyTypeDesc":95},"01JBSEEDCAT000000000000023","Skill与智能体开发","SCENARIO","使用场景",[87,97,98,99,100,101,102,103,104,105,106,107],"adaptive","inspect","with","ownership","delivery routing","runtime","delivery","workspaces","git","routing","create",{"skillNo":109,"name":110,"nameZh":6,"description":111,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":112,"categories":113,"keywords":116,"publishedAt":53},"01M6FNP75BY8CS006EWGN29FM0","web-search","Route online research and URL reading to native tools or TinyFish MCP\u002FAPI; prepare targeted requests, handle progress and failures, and check returned evidence. Applies to web search, fetching, and bulk collection; excludes repository\u002Ffile search.","https:\u002F\u002Fgithub.com\u002Fshenxingy\u002FClade\u002Fblob\u002Fmain\u002Fplugins\u002Fclade\u002Fskills\u002Fweb-search\u002FSKILL.md",[114,115],{"categoryNo":92,"categoryName":93,"taxonomyType":94,"taxonomyTypeDesc":95},{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},[117,118,119,120,121,122,123,124,125,126,127,128,129,130,131,132,133,134,135,136],"web search","search","web","repository","file","research","MCP","requests","collection","reading","URL","native","bulk","progress","file search","route","tinyfish","evidence","check","api",{"skillNo":138,"name":139,"nameZh":6,"description":140,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":141,"categories":142,"keywords":144,"publishedAt":53},"01M6FNP2616DRTZRSZJQM3HPHY","verify","Verify project behavior anchors — compilation, tests, and interaction checks after autonomous runs. NOT the Codex built-in \u002Fverify (which runs the app to observe a single change working) — this one walks the AGENTS.md \"Features (Behavior Anchors)\" list.","https:\u002F\u002Fgithub.com\u002Fshenxingy\u002FClade\u002Fblob\u002Fmain\u002Fplugins\u002Fclade\u002Fskills\u002Fverify\u002FSKILL.md",[143],{"categoryNo":92,"categoryName":93,"taxonomyType":94,"taxonomyTypeDesc":95},[139,145,146,147,148,149,150,151,152,153,154,155,156,157],"app","single","features","which","interaction","tests","project","observe","autonomous","behavior","list","change","codex",{"skillNo":159,"name":160,"nameZh":6,"description":161,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":162,"categories":163,"keywords":165,"publishedAt":53},"01M6FNNX95R9H29BNERFY15704","tasks","Coordinate dependency-aware project tasks across independent Codex, Codex, Kimi and human sessions using Beads. Use for shared plans, claiming work, task handoffs, acceptance and agent monitoring snapshots.","https:\u002F\u002Fgithub.com\u002Fshenxingy\u002FClade\u002Fblob\u002Fmain\u002Fplugins\u002Fclade\u002Fskills\u002Ftasks\u002FSKILL.md",[164],{"categoryNo":92,"categoryName":93,"taxonomyType":94,"taxonomyTypeDesc":95},[160,166,167,168,151,169,170,171,172,173,174,175,176,177,42,178,179,180,181,182,157],"for","plans","work","shared","across","human","task","coordinate","kimi","snapshots","agent monitoring","dependency","using beads","beads","monitoring","acceptance","sessions",{"skillNo":184,"name":185,"nameZh":6,"description":186,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":187,"categories":188,"keywords":190,"publishedAt":53},"01M6FNNTAD1BCZX5Q9TC55MZCH","sync","End-of-session documentation sync — updates TODO.md and PROGRESS.md only (run \u002Fcommit after to commit everything)","https:\u002F\u002Fgithub.com\u002Fshenxingy\u002FClade\u002Fblob\u002Fmain\u002Fplugins\u002Fclade\u002Fskills\u002Fsync\u002FSKILL.md",[189],{"categoryNo":92,"categoryName":93,"taxonomyType":94,"taxonomyTypeDesc":95},[185,191,192,193,194,195,196,197,130,198,199],"session","run","documentation","commit","only","documentation sync","updates","end","todo",{"skillNo":201,"name":202,"nameZh":6,"description":203,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":204,"categories":205,"keywords":207,"publishedAt":53},"01M6FNNPTR5H23MD3849E66WYA","status","Show a provider-neutral, freshness-aware snapshot of active Agent work, Git delivery, execution identity, and usage limits. Use for “what's going on right now”, what is running, progress updates, active runtime\u002Fprovider\u002Fmodel, or stuck-work checks.","https:\u002F\u002Fgithub.com\u002Fshenxingy\u002FClade\u002Fblob\u002Fmain\u002Fplugins\u002Fclade\u002Fskills\u002Fstatus\u002FSKILL.md",[206],{"categoryNo":92,"categoryName":93,"taxonomyType":94,"taxonomyTypeDesc":95},[202,102,208,209,166,197,210,211,130,212,103,213,214,42,215,168,45,216,105,217],"running","limits","usage","now","active","show","provider","snapshot","execution","identity"]