[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"extension-skill-vectorize-io-create-agent-de":3,"guides-for-vectorize-io-create-agent":677,"similar-k17b9df8dfqwr25t2sppr6cgjd86m12x-de":678},{"_creationTime":4,"_id":5,"children":6,"community":7,"display":9,"evaluation":15,"identity":242,"isFallback":225,"parentExtension":246,"providers":301,"relations":305,"repo":306,"tags":675,"workflow":676},1778698371743.7034,"k17b9df8dfqwr25t2sppr6cgjd86m12x",[],{"reviewCount":8},0,{"description":10,"installMethods":11,"name":13,"sourceUrl":14},"Create a new Hindsight-powered subagent with long-term memory. 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Use when building features that need research, planning, and implementation phases.",{"claudeCode":686},"rohitg00/pro-workflow","orchestrate","https://github.com/rohitg00/pro-workflow",{"basePath":690,"githubOwner":691,"githubRepo":692,"locale":18,"slug":687,"type":245},"skills/orchestrate","rohitg00","pro-workflow",{"evaluate":694,"extract":700},{"promptVersionExtension":204,"promptVersionScoring":205,"score":695,"tags":696,"targetMarket":216,"tier":217},100,[697,211,698,212,699],"llm-ops","workflow","knowledge-management",{"commitSha":279},{"parentExtensionId":702,"repoId":703},"k17fxtjcfh5gvxdrhv2dmgn1t986mdhv","kd7am4e918eq98hrd9s31jm4vs86nn0b",[211,699,697,212,698],{"evaluatedAt":706,"extractAt":707,"updatedAt":706},1778696881233,1778696595410,{"_creationTime":709,"_id":710,"community":711,"display":712,"identity":718,"providers":723,"relations":731,"tags":734,"workflow":735},1778694269038.6682,"k1752cypc448mke749yjbkc65186mg6f",{"reviewCount":8},{"description":713,"installMethods":714,"name":716,"sourceUrl":717},"This skill should be used when the user asks to \"compress context\", \"summarize conversation history\", \"implement compaction\", \"reduce token usage\", or mentions context compression, structured summarization, tokens-per-task optimization, or long-running agent sessions exceeding context limits.",{"claudeCode":715},"muratcankoylan/Agent-Skills-for-Context-Engineering","Context Compression","https://github.com/muratcankoylan/Agent-Skills-for-Context-Engineering",{"basePath":719,"githubOwner":720,"githubRepo":721,"locale":18,"slug":722,"type":245},"skills/context-compression","muratcankoylan","Agent-Skills-for-Context-Engineering","context-compression",{"evaluate":724,"extract":730},{"promptVersionExtension":204,"promptVersionScoring":205,"score":695,"tags":725,"targetMarket":216,"tier":217},[726,214,211,727,728,729],"context-engineering","summarization","compression","evaluation",{"commitSha":279,"license":238},{"parentExtensionId":732,"repoId":733},"k1754dy3wbsv2a5gr1a983zzs586njca","kd7f12maf5nxmx5xttjx7scfnx86m1tv",[211,728,726,729,214,727],{"evaluatedAt":736,"extractAt":737,"updatedAt":736},1778694410149,1778694269038,{"_creationTime":739,"_id":740,"community":741,"display":742,"identity":746,"providers":749,"relations":756,"tags":757,"workflow":758},1778696595410.5698,"k171sdysmt658g1cdd7hgt8p8h86nms7",{"reviewCount":8},{"description":743,"installMethods":744,"name":745,"sourceUrl":688},"End-of-session ritual that audits changes, runs quality checks, captures learnings, and produces a session summary. Use when saying \"wrap up\", \"done for the day\", \"finish coding\", or ending a coding session.",{"claudeCode":686},"Wrap-Up Ritual",{"basePath":747,"githubOwner":691,"githubRepo":692,"locale":18,"slug":748,"type":245},"skills/wrap-up","wrap-up",{"evaluate":750,"extract":755},{"promptVersionExtension":204,"promptVersionScoring":205,"score":695,"tags":751,"targetMarket":216,"tier":217},[698,214,752,212,753,754],"productivity","knowledge-base","code-quality",{"commitSha":279,"license":238},{"parentExtensionId":702,"repoId":703},[754,753,214,212,752,698],{"evaluatedAt":759,"extractAt":707,"updatedAt":759},1778697164619,{"_creationTime":761,"_id":762,"community":763,"display":764,"identity":770,"providers":776,"relations":783,"tags":787,"workflow":788},1778693798788.0542,"k170ymfjagf8xv5gd19p7dq52986mp9g",{"reviewCount":8},{"description":765,"installMethods":766,"name":768,"sourceUrl":769},"Domänenwissen für die Evolution Engine — LLM-gestützte autonome Strategieentdeckung aus rohen OHLCV-Daten. Behandelt die Schleife Generieren-Backtesten-Auswählen-Entwickeln, vektorisiertes Backtesting, Out-of-Sample-Validierung und Strategiegraduierung. Verwenden Sie es beim Entdecken von Handelspatterns, Ausführen von Backtests, Entwickeln von Strategien oder Überprüfen von Evolutionsprotokollen. Löst aus bei \"evolve\", \"discover patterns\", \"backtest\", \"evolution\", \"strategy generation\", \"candidate strategy\".",{"claudeCode":767},"mnemox-ai/tradememory-protocol","TradeMemory Protocol","https://github.com/mnemox-ai/tradememory-protocol",{"basePath":771,"githubOwner":772,"githubRepo":773,"locale":774,"slug":775,"type":245},"tradememory-plugin/skills/evolution-engine","mnemox-ai","tradememory-protocol","de","evolution-engine",{"evaluate":777,"extract":782},{"promptVersionExtension":204,"promptVersionScoring":205,"score":695,"tags":778,"targetMarket":216,"tier":217},[779,274,212,780,781,214],"trading","audit","compliance",{"commitSha":279,"license":238},{"parentExtensionId":784,"repoId":785,"translatedFrom":786},"k170vxkqee48k2xq1v55a025nh86nzn7","kd73z11kfekksxyrs8ds0snacs86ncdy","k171p5pgbfbm5g4k5sa3y4cj9s86m6hk",[274,780,781,214,212,779],{"evaluatedAt":789,"extractAt":790,"updatedAt":791},1778693678813,1778693539593,1778693798788,{"_creationTime":793,"_id":794,"community":795,"display":796,"identity":802,"providers":806,"relations":812,"tags":814,"workflow":815},1778696691708.2983,"k17c6tkghtgnr7jnsh6gf5mf9h86nk00",{"reviewCount":8},{"description":797,"installMethods":798,"name":800,"sourceUrl":801},"Implement persistent memory patterns for AI agents using AgentDB. Includes session memory, long-term storage, pattern learning, and context management. Use when building stateful agents, chat systems, or intelligent assistants.",{"claudeCode":799},"ruvnet/ruflo","agentdb-memory-patterns","https://github.com/ruvnet/ruflo",{"basePath":803,"githubOwner":804,"githubRepo":805,"locale":18,"slug":800,"type":245},".claude/skills/agentdb-memory-patterns","ruvnet","ruflo",{"evaluate":807,"extract":811},{"promptVersionExtension":204,"promptVersionScoring":205,"score":292,"tags":808,"targetMarket":216,"tier":217},[274,211,212,276,809,810],"typescript","nodejs",{"commitSha":279},{"repoId":813},"kd7ed28gj8n0y3msk5dzrp05zs86nqtc",[211,274,276,212,810,809],{"evaluatedAt":816,"extractAt":817,"updatedAt":816},1778698807267,1778696691708,{"_creationTime":819,"_id":820,"community":821,"display":822,"identity":828,"providers":832,"relations":838,"tags":841,"workflow":842},1778699234184.6143,"k17cnx0m6a27fw52yvt4zsbsxh86nd1c",{"reviewCount":8},{"description":823,"installMethods":824,"name":826,"sourceUrl":827},"Configure popular MCP servers for enhanced agent capabilities",{"claudeCode":825},"Yeachan-Heo/oh-my-claudecode","mcp-setup","https://github.com/Yeachan-Heo/oh-my-claudecode",{"basePath":829,"githubOwner":830,"githubRepo":831,"locale":18,"slug":826,"type":245},"skills/mcp-setup","Yeachan-Heo","oh-my-claudecode",{"evaluate":833,"extract":837},{"promptVersionExtension":204,"promptVersionScoring":205,"score":695,"tags":834,"targetMarket":216,"tier":217},[661,835,540,211,836],"configuration","tooling",{"commitSha":279},{"parentExtensionId":839,"repoId":840},"k17brg5egdw1jbncj1j4wfv3fh86n639","kd74zv63fryf9prygtq7gf4es986n22y",[211,540,835,661,836],{"evaluatedAt":843,"extractAt":844,"updatedAt":843},1778699492025,1778699234184]