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数据中自主发现策略。涵盖生成-回测-选择-进化循环、向量化回测、样本外验证和策略梯度。在发现交易模式、运行回测、进化策略或审查进化日志时使用。由“evolve”、“discover patterns”、“backtest”、“evolution”、“strategy generation”、“candidate strategy”触发。",{"claudeCode":447},"mnemox-ai/tradememory-protocol","TradeMemory Protocol","https://github.com/mnemox-ai/tradememory-protocol",{"basePath":451,"githubOwner":452,"githubRepo":453,"locale":18,"slug":454,"type":244},"tradememory-plugin/skills/evolution-engine","mnemox-ai","tradememory-protocol","evolution-engine",{"evaluate":456,"extract":463},{"promptVersionExtension":203,"promptVersionScoring":204,"score":457,"tags":458,"targetMarket":271,"tier":215},100,[459,210,460,461,462,211],"trading","memory","audit","compliance",{"commitSha":273,"license":234},{"parentExtensionId":465,"repoId":466,"translatedFrom":467},"k170vxkqee48k2xq1v55a025nh86nzn7","kd73z11kfekksxyrs8ds0snacs86ncdy","k171p5pgbfbm5g4k5sa3y4cj9s86m6hk",[210,461,462,211,460,459],{"evaluatedAt":470,"extractAt":471,"updatedAt":472},1778693678813,1778693539593,1778693805112,{"_creationTime":474,"_id":475,"community":476,"display":477,"identity":483,"providers":488,"relations":495,"tags":498,"workflow":499},1778691104676.0042,"k17c25w174y6873nhdh566etts86mv7m",{"reviewCount":8},{"description":478,"installMethods":479,"name":481,"sourceUrl":482},"Transform images with resize, crop, smart crop, upscale, remove background, and 20+ operations.",{"claudeCode":480},"iterationlayer/skills","Image Transformation API","https://github.com/iterationlayer/skills",{"basePath":484,"githubOwner":485,"githubRepo":486,"locale":254,"slug":487,"type":244},"skills/image-transformation-api","iterationlayer","skills","image-transformation-api",{"evaluate":489,"extract":494},{"promptVersionExtension":203,"promptVersionScoring":204,"score":457,"tags":490,"targetMarket":271,"tier":215},[491,492,493,212,210],"image","transformation","editing",{"commitSha":273,"license":234},{"parentExtensionId":496,"repoId":497},"k1721s0xmp59902ybtpakrrffn86n10s","kd76p4g2qmtrkgx99cnab3683d86n4g8",[210,212,493,491,492],{"evaluatedAt":500,"extractAt":501,"updatedAt":500},1778693613399,1778691104676,{"_creationTime":503,"_id":504,"community":505,"display":506,"identity":512,"providers":516,"relations":524,"tags":528,"workflow":529},1778695002445.9265,"k17f3bbm7ztgr1r8jg4ztnjb0s86mgqd",{"reviewCount":8},{"description":507,"installMethods":508,"name":510,"sourceUrl":511},"在用户希望查找、筛选、审核或丰富美国网络安全公司信息时使用——包括渗透测试/红队、安全审计、vCISO、SOC 2 准备、事件响应、托管 SOC、IAM、云安全和 AppSec。当用户输入“为我们的 SOC 2 审计找一家渗透测试公司”、“为我们医疗科技初创公司筛选三家 vCISO 服务商”、“我们需要事件响应服务合同”或“拉取这 8 家安全公司域名的联系信息”等请求时触发，即使是以间接方式描述（我们被攻击了，为合规审计做准备，让我们准备好 SOC 2）。它会驱动 ServiceGraph API (api.servicegraph.co) —— 一个拥有超过 10 万家美国公司目录的数据库，可按行业、服务、地点、规模、评分进行筛选。排除内部安全招聘、关于“如何修补 CVE-X”或“配置防火墙 Y”的 DIY 问题、安全产品评测（如 CrowdStrike vs SentinelOne 等）、通用安全知识问题、面向消费者的个人安全建议、非美国公司、个人自由职业者和赏金猎人。",{"claudeCode":509},"nostrband/ServiceGraph","find-cybersecurity-firm","https://github.com/nostrband/ServiceGraph",{"basePath":513,"githubOwner":514,"githubRepo":515,"locale":18,"slug":510,"type":244},"skills/find-cybersecurity-firm","nostrband","ServiceGraph",{"evaluate":517,"extract":523},{"promptVersionExtension":203,"promptVersionScoring":204,"score":457,"tags":518,"targetMarket":271,"tier":215},[519,520,521,522,212,213],"cybersecurity","servicegraph","business","procurement",{"commitSha":273},{"parentExtensionId":525,"repoId":526,"translatedFrom":527},"k170hexh2b1y2ab8gj4acbt6t186mmhn","kd73je8ge8dvxgqqy6nvhxz1e186nhcc","k17f5djrtgcfht64yn209hdmqh86n8kv",[212,521,519,522,213,520],{"evaluatedAt":530,"extractAt":531,"updatedAt":532},1778694766522,1778694690188,1778695002445,{"_creationTime":534,"_id":535,"community":536,"display":537,"identity":543,"providers":546,"relations":553,"tags":556,"workflow":557},1778692394292.7976,"k1769yhtdcsq8qjbfsegfcybc586nd4b",{"reviewCount":8},{"description":538,"installMethods":539,"name":541,"sourceUrl":542},"跨越 180 多家航空公司的航班搜索和预订，无任何加价——比 OTA（在线旅行社）便宜 20-50 美元。通过本地连接器（Ryanair、EasyJet、Wizz Air、Southwest、AirAsia 等 175 多家）返回原始航空公司价格。当用户询问“查找航班”、“搜索航班”、“预订航班”、“比较航空公司价格”、“查找廉价航班”、“从 X 飞往 Y”、“查找转机航班”、“查找中转选项”或任何与航班相关的旅行查询时使用。请勿用于仅限酒店的搜索、租车或非航班旅行预订。",{"claudeCode":540},"LetsFG/LetsFG","flight-search","https://github.com/LetsFG/LetsFG",{"basePath":544,"githubOwner":545,"githubRepo":545,"locale":18,"slug":541,"type":244},"skills/flight-search","LetsFG",{"evaluate":547,"extract":552},{"promptVersionExtension":203,"promptVersionScoring":204,"score":457,"tags":548,"targetMarket":271,"tier":215},[549,550,551,212,213],"flights","travel","booking",{"commitSha":273},{"repoId":554,"translatedFrom":555},"kd7d4mhwkp3k1m28hz28hyn2dd86mm88","k173ztaywbkajjk9gqy90n98fx86mnzf",[212,551,549,213,550],{"evaluatedAt":558,"extractAt":559,"updatedAt":560},1778692265291,1778692220267,1778692394292,{"_creationTime":562,"_id":563,"community":564,"display":565,"identity":571,"providers":576,"relations":585,"tags":588,"workflow":589},1778696691708.3308,"k17d3c35ws96bb55ry97apwm5n86mqp2",{"reviewCount":8},{"description":566,"installMethods":567,"name":569,"sourceUrl":570},"Format prompts for different LLM providers with chat templates and HNSW-powered context retrieval",{"claudeCode":568},"ruvnet/ruflo","Chat Format","https://github.com/ruvnet/ruflo",{"basePath":572,"githubOwner":573,"githubRepo":574,"locale":254,"slug":575,"type":244},"plugins/ruflo-ruvllm/skills/chat-format","ruvnet","ruflo","chat-format",{"evaluate":577,"extract":584},{"promptVersionExtension":203,"promptVersionScoring":204,"score":457,"tags":578,"targetMarket":271,"tier":215},[211,579,270,580,214,581,582,583],"prompting","context-retrieval","anthropic","gemini","ollama",{"commitSha":273,"license":234},{"parentExtensionId":586,"repoId":587},"k17ekc0sj70ms9kgkkgr2ypr4s86mz40","kd7ed28gj8n0y3msk5dzrp05zs86nqtc",[581,580,582,211,583,214,579,270],{"evaluatedAt":590,"extractAt":591,"updatedAt":590},1778701390930,1778696691708,{"_creationTime":593,"_id":594,"community":595,"display":596,"identity":600,"providers":602,"relations":610,"tags":611,"workflow":612},1778696691708.2996,"k175z5j3knm69exj7qpfwy3e1586nh3w",{"reviewCount":8},{"description":597,"installMethods":598,"name":599,"sourceUrl":570},"Vector embeddings with HNSW indexing, sql.js persistence, and hyperbolic support. 75x faster with agentic-flow integration. Use when: semantic search, pattern matching, similarity queries, knowledge retrieval. Skip when: exact text matching, simple lookups, no semantic understanding needed.\n",{"claudeCode":568},"embeddings",{"basePath":601,"githubOwner":573,"githubRepo":574,"locale":254,"slug":599,"type":244},".agents/skills/embeddings",{"evaluate":603,"extract":609},{"promptVersionExtension":203,"promptVersionScoring":204,"score":287,"tags":604,"targetMarket":271,"tier":215},[599,605,606,607,210,213,608],"vector-search","hnsw","sql-js","retrieval",{"commitSha":273},{"repoId":587},[210,599,606,608,213,607,605],{"evaluatedAt":613,"extractAt":591,"updatedAt":613},1778698905205]