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Outbound calls for LLM processing are standard and documented, with no evidence of confidential data exfiltration.",{"category":65,"check":84,"severity":24,"summary":85},"Hidden Text Tricks","The bundled content and documentation do not contain hidden steering tricks, invisible characters, or obfuscated instructions.",{"category":87,"check":88,"severity":24,"summary":89},"Hooks","Opaque code execution","The provided skill code is plain and readable, with no evidence of obfuscation techniques like base64 encoding or dynamic script fetching.",{"category":91,"check":92,"severity":24,"summary":93},"Portability","Structural Assumption","The skill's CLI commands operate independently and do not make assumptions about the user's project structure beyond requiring the `hindsight-embed` CLI to be configured.",{"category":95,"check":96,"severity":24,"summary":97},"Trust","Issues Attention","The repository shows a healthy ratio of closed to open issues (233 closed vs. 70 open in 90 days), indicating active maintenance and responsiveness.",{"category":99,"check":100,"severity":24,"summary":101},"Versioning","Release Management","The project has a MIT license declared, and the presence of recent commits and CI suggests a maintainable release process, although a formal versioning scheme like semver is not explicitly detailed in the frontmatter.",{"category":103,"check":104,"severity":24,"summary":105},"Code Execution","Validation","The documentation implies structured processing of input content and mentions extraction of facts and entities, suggesting internal validation mechanisms.",{"category":65,"check":107,"severity":24,"summary":108},"Unguarded Destructive Operations","The extension's primary operations involve storing and recalling data, not destructive file operations, and thus this check is not applicable.",{"category":103,"check":110,"severity":24,"summary":111},"Error Handling","The setup instructions for the `hindsight-embed` CLI include troubleshooting steps for failures, indicating that errors are likely handled and reported.",{"category":103,"check":113,"severity":24,"summary":114},"Logging","The setup instructions for the CLI daemon and Docker images suggest logging capabilities for auditing and debugging purposes.",{"category":116,"check":117,"severity":24,"summary":118},"Compliance","GDPR","The extension handles user-provided content which may contain personal data, but it's processed internally for memory extraction. It does not explicitly submit personal data to third parties without user configuration or approval for LLM providers.",{"category":116,"check":120,"severity":24,"summary":121},"Target market","The extension's functionality is not geographically bound and operates on user-provided data, making it globally applicable.",{"category":91,"check":123,"severity":24,"summary":124},"Runtime stability","The extension relies on standard CLI tools and Docker, with clear setup instructions for different environments, suggesting good cross-platform compatibility.",{"category":44,"check":126,"severity":24,"summary":127},"README","The README file is comprehensive, detailing the extension's purpose, architecture, setup, usage, and community links.",{"category":33,"check":129,"severity":24,"summary":130},"Tool surface size","The extension exposes a focused set of three core commands: `retain`, `recall`, and `reflect`.",{"category":40,"check":132,"severity":24,"summary":133},"Overlapping near-synonym 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Use when building features that need research, planning, and implementation phases.",{"claudeCode":661},"rohitg00/pro-workflow","orchestrate","https://github.com/rohitg00/pro-workflow",{"basePath":665,"githubOwner":666,"githubRepo":667,"locale":18,"slug":662,"type":263},"skills/orchestrate","rohitg00","pro-workflow",{"evaluate":669,"extract":675},{"promptVersionExtension":215,"promptVersionScoring":216,"score":670,"tags":671,"targetMarket":227,"tier":228},100,[672,223,673,222,674],"llm-ops","workflow","knowledge-management",{"commitSha":269},{"parentExtensionId":677,"repoId":678},"k17fxtjcfh5gvxdrhv2dmgn1t986mdhv","kd7am4e918eq98hrd9s31jm4vs86nn0b",[223,674,672,222,673],{"evaluatedAt":681,"extractAt":682,"updatedAt":681},1778696881233,1778696595410,{"_creationTime":684,"_id":685,"community":686,"display":687,"identity":693,"providers":698,"relations":706,"tags":709,"workflow":710},1778694269038.6682,"k1752cypc448mke749yjbkc65186mg6f",{"reviewCount":8},{"description":688,"installMethods":689,"name":691,"sourceUrl":692},"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":690},"muratcankoylan/Agent-Skills-for-Context-Engineering","Context Compression","https://github.com/muratcankoylan/Agent-Skills-for-Context-Engineering",{"basePath":694,"githubOwner":695,"githubRepo":696,"locale":18,"slug":697,"type":263},"skills/context-compression","muratcankoylan","Agent-Skills-for-Context-Engineering","context-compression",{"evaluate":699,"extract":705},{"promptVersionExtension":215,"promptVersionScoring":216,"score":670,"tags":700,"targetMarket":227,"tier":228},[701,226,223,702,703,704],"context-engineering","summarization","compression","evaluation",{"commitSha":269,"license":254},{"parentExtensionId":707,"repoId":708},"k1754dy3wbsv2a5gr1a983zzs586njca","kd7f12maf5nxmx5xttjx7scfnx86m1tv",[223,703,701,704,226,702],{"evaluatedAt":711,"extractAt":712,"updatedAt":711},1778694410149,1778694269038,{"_creationTime":714,"_id":715,"community":716,"display":717,"identity":721,"providers":724,"relations":731,"tags":732,"workflow":733},1778696595410.5698,"k171sdysmt658g1cdd7hgt8p8h86nms7",{"reviewCount":8},{"description":718,"installMethods":719,"name":720,"sourceUrl":663},"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":661},"Wrap-Up Ritual",{"basePath":722,"githubOwner":666,"githubRepo":667,"locale":18,"slug":723,"type":263},"skills/wrap-up","wrap-up",{"evaluate":725,"extract":730},{"promptVersionExtension":215,"promptVersionScoring":216,"score":670,"tags":726,"targetMarket":227,"tier":228},[673,226,727,222,728,729],"productivity","knowledge-base","code-quality",{"commitSha":269,"license":254},{"parentExtensionId":677,"repoId":678},[729,728,226,222,727,673],{"evaluatedAt":734,"extractAt":682,"updatedAt":734},1778697164619,{"_creationTime":736,"_id":737,"community":738,"display":739,"identity":745,"providers":751,"relations":759,"tags":763,"workflow":764},1778693798788.0542,"k170ymfjagf8xv5gd19p7dq52986mp9g",{"reviewCount":8},{"description":740,"installMethods":741,"name":743,"sourceUrl":744},"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":742},"mnemox-ai/tradememory-protocol","TradeMemory Protocol","https://github.com/mnemox-ai/tradememory-protocol",{"basePath":746,"githubOwner":747,"githubRepo":748,"locale":749,"slug":750,"type":263},"tradememory-plugin/skills/evolution-engine","mnemox-ai","tradememory-protocol","de","evolution-engine",{"evaluate":752,"extract":758},{"promptVersionExtension":215,"promptVersionScoring":216,"score":670,"tags":753,"targetMarket":227,"tier":228},[754,755,222,756,757,226],"trading","ai","audit","compliance",{"commitSha":269,"license":254},{"parentExtensionId":760,"repoId":761,"translatedFrom":762},"k170vxkqee48k2xq1v55a025nh86nzn7","kd73z11kfekksxyrs8ds0snacs86ncdy","k171p5pgbfbm5g4k5sa3y4cj9s86m6hk",[755,756,757,226,222,754],{"evaluatedAt":765,"extractAt":766,"updatedAt":767},1778693678813,1778693539593,1778693798788,{"_creationTime":769,"_id":770,"community":771,"display":772,"identity":778,"providers":783,"relations":791,"tags":794,"workflow":795},1778699234184.614,"k17f09h6q6ej58qvz0d2cds8r186mj71",{"reviewCount":8},{"description":773,"installMethods":774,"name":776,"sourceUrl":777},"Extract a learned skill from the current conversation",{"claudeCode":775},"Yeachan-Heo/oh-my-claudecode","Learner Skill","https://github.com/Yeachan-Heo/oh-my-claudecode",{"basePath":779,"githubOwner":780,"githubRepo":781,"locale":18,"slug":782,"type":263},"skills/learner","Yeachan-Heo","oh-my-claudecode","learner",{"evaluate":784,"extract":790},{"promptVersionExtension":215,"promptVersionScoring":216,"score":785,"tags":786,"targetMarket":227,"tier":228},99,[224,787,788,223,789],"skill-extraction","automation","code-generation",{"commitSha":269,"license":254},{"parentExtensionId":792,"repoId":793},"k17brg5egdw1jbncj1j4wfv3fh86n639","kd74zv63fryf9prygtq7gf4es986n22y",[223,788,789,224,787],{"evaluatedAt":796,"extractAt":797,"updatedAt":796},1778699479176,1778699234184,{"_creationTime":799,"_id":800,"community":801,"display":802,"identity":808,"providers":812,"relations":819,"tags":821,"workflow":822},1778696691708.2983,"k17c6tkghtgnr7jnsh6gf5mf9h86nk00",{"reviewCount":8},{"description":803,"installMethods":804,"name":806,"sourceUrl":807},"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":805},"ruvnet/ruflo","agentdb-memory-patterns","https://github.com/ruvnet/ruflo",{"basePath":809,"githubOwner":810,"githubRepo":811,"locale":18,"slug":806,"type":263},".claude/skills/agentdb-memory-patterns","ruvnet","ruflo",{"evaluate":813,"extract":818},{"promptVersionExtension":215,"promptVersionScoring":216,"score":785,"tags":814,"targetMarket":227,"tier":228},[755,223,222,815,816,817],"database","typescript","nodejs",{"commitSha":269},{"repoId":820},"kd7ed28gj8n0y3msk5dzrp05zs86nqtc",[223,755,815,222,817,816],{"evaluatedAt":823,"extractAt":824,"updatedAt":823},1778698807267,1778696691708]