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Informed by logistics professionals with 15+ years operational experience. Includes escalation protocols, carrier-specific behaviors, claims procedures, and judgment frameworks. Use when handling shipping exceptions, freight claims, delivery issues, or carrier disputes.","https:\u002F\u002Fgithub.com\u002Fsakamoto-family-smile\u002Fagent_monorepo\u002Fblob\u002Fmain\u002F.claude\u002Fskills\u002Fecc\u002Flogistics-exception-management\u002FSKILL.md",[],[503,504,152,387,505,506,507,508,509,341,510,511,512,513,422,514,230,515,516,351],"management","logistics exception management","shipping","issues","protocols","https","escalation","frameworks","delivery","claude-code","judgment","claims","expertise","freight",{"skillNo":518,"name":519,"nameZh":13,"description":520,"descriptionZh":13,"repositoryFullName":201,"ownerLogin":202,"ownerAvatarUrl":203,"ownerAccountNo":204,"ownerDisplayName":13,"repositoryNo":205,"starsCount":206,"licenseSpdxId":207,"licenseFileUrl":13,"sourceHtmlUrl":521,"categories":522,"keywords":524,"publishedAt":231},"01M6RVNE8C122FS3JEVKQ9Y5P7","llm-trading-agent-security","Security patterns for autonomous trading agents with wallet or transaction authority. Covers prompt injection, spend limits, pre-send simulation, circuit breakers, MEV protection, and key handling.","https:\u002F\u002Fgithub.com\u002Fsakamoto-family-smile\u002Fagent_monorepo\u002Fblob\u002Fmain\u002F.claude\u002Fskills\u002Fecc\u002Fllm-trading-agent-security\u002FSKILL.md",[523],{"categoryNo":262,"categoryName":263,"taxonomyType":53,"taxonomyTypeDesc":54},[525,526,527,528,529,530,531,532,533,534,319,535,536,422,230,537,538,539,540,541],"agent security","security","llm trading agent security","trading","prompt injection","simulation","prompt","autonomous","Wallet","protection","adaptation","port","trading agents","authority","autonomous trading","send","limits",{"skillNo":543,"name":544,"nameZh":13,"description":545,"descriptionZh":13,"repositoryFullName":201,"ownerLogin":202,"ownerAvatarUrl":203,"ownerAccountNo":204,"ownerDisplayName":13,"repositoryNo":205,"starsCount":206,"licenseSpdxId":207,"licenseFileUrl":13,"sourceHtmlUrl":546,"categories":547,"keywords":552,"publishedAt":231},"01M6RVMR65WVBZ6CS51C7DCXFK","liquid-glass-design","iOS 26 Liquid Glass design system — dynamic glass material with blur, reflection, and interactive morphing for SwiftUI, UIKit, and WidgetKit.","https:\u002F\u002Fgithub.com\u002Fsakamoto-family-smile\u002Fagent_monorepo\u002Fblob\u002Fmain\u002F.claude\u002Fskills\u002Fecc\u002Fliquid-glass-design\u002FSKILL.md",[548,551],{"categoryNo":549,"categoryName":550,"taxonomyType":53,"taxonomyTypeDesc":54},"01JBSEEDCAT000000000000015","视觉设计",{"categoryNo":16,"categoryName":17,"taxonomyType":6,"taxonomyTypeDesc":7},[486,553,554,555,556,216,340,557,558,559,560,561,422,562,230],"liquid glass","liquid glass design","liquid","design system","swiftui","uikit","interactive","reflection","material","blur",{"skillNo":564,"name":565,"nameZh":13,"description":566,"descriptionZh":13,"repositoryFullName":201,"ownerLogin":202,"ownerAvatarUrl":203,"ownerAccountNo":204,"ownerDisplayName":13,"repositoryNo":205,"starsCount":206,"licenseSpdxId":207,"licenseFileUrl":13,"sourceHtmlUrl":567,"categories":568,"keywords":572,"publishedAt":231},"01M6RVMG13BPACES816K5H9WAR","lead-intelligence","AI-native lead intelligence and outreach pipeline. Replaces Apollo, Clay, and ZoomInfo with agent-powered signal scoring, mutual ranking, warm path discovery, source-derived voice modeling, and channel-specific outreach across email, LinkedIn, and X. Use when the user wants to find, qualify, and reach high-value contacts.","https:\u002F\u002Fgithub.com\u002Fsakamoto-family-smile\u002Fagent_monorepo\u002Fblob\u002Fmain\u002F.claude\u002Fskills\u002Fecc\u002Flead-intelligence\u002FSKILL.md",[569],{"categoryNo":570,"categoryName":571,"taxonomyType":53,"taxonomyTypeDesc":54},"01JBSEEDCAT000000000000005","邮件与沟通",[445,573,574,575,576,577,578,579,580,581,582,583,584,585,586,253,395,587,588,351],"lead intelligence","lead","email","pipeline","discovery","ai-native","scoring","clay","across","modeling","ranking","qualify","native","contacts","value","signal",{"skillNo":590,"name":591,"nameZh":13,"description":592,"descriptionZh":13,"repositoryFullName":201,"ownerLogin":202,"ownerAvatarUrl":203,"ownerAccountNo":204,"ownerDisplayName":13,"repositoryNo":205,"starsCount":206,"licenseSpdxId":207,"licenseFileUrl":13,"sourceHtmlUrl":593,"categories":594,"keywords":595,"publishedAt":231},"01M6RVKW3KBSH0FQ5B3J6K2AM1","latency-critical-systems","Use for latency-sensitive systems such as realtime dashboards, market data, streaming agents, execution gateways, queues, caches, or HFT-like infrastructure where freshness and p95 latency matter.","https:\u002F\u002Fgithub.com\u002Fsakamoto-family-smile\u002Fagent_monorepo\u002Fblob\u002Fmain\u002F.claude\u002Fskills\u002Fecc\u002Flatency-critical-systems\u002FSKILL.md",[],[596,373,597,598,599,600,601,367,602,603,604,272,605,606,341,437,252,607,608,230],"latency","critical","latency critical systems","realtime","streaming","gateways","execution","Bash","grep","write","edit","hft","market data",10874,18]