[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"extension-marketplace-vectorize-io-hindsight-integrations-en":3,"guides-for-vectorize-io-hindsight-integrations":636,"similar-k178tthvkav2341vt1q8d8j8yn86ncbf-en":637},{"_creationTime":4,"_id":5,"children":6,"community":48,"display":49,"evaluation":54,"identity":250,"isFallback":246,"parentExtension":253,"providers":254,"relations":260,"repo":261,"tags":634,"workflow":635},1778698371743.703,"k178tthvkav2341vt1q8d8j8yn86ncbf",[7],{"_creationTime":8,"_id":9,"community":10,"display":12,"identity":17,"providers":24,"relations":42,"tags":44,"workflow":45},1778698371743.7026,"k175pn6bnbbfyybfj0c7g5xm8h86nc75",{"reviewCount":11},0,{"description":13,"installMethods":14,"name":15,"sourceUrl":16},"Automatic long-term memory for Claude Code via Hindsight. Recalls relevant memories before each prompt, retains conversation transcripts, and provides knowledge page tools.",{"claudeCode":15},"hindsight-memory","https://github.com/vectorize-io/hindsight",{"basePath":18,"githubOwner":19,"githubRepo":20,"locale":21,"slug":22,"type":23},"hindsight-integrations/claude-code","vectorize-io","hindsight","en","claude-code","plugin",{"evaluate":25,"extract":36},{"promptVersionExtension":26,"promptVersionScoring":27,"score":28,"tags":29,"targetMarket":34,"tier":35},"3.0.0","4.4.0",99,[30,20,31,32,22,33],"memory","llm","long-term-memory","agent","global","verified",{"commitSha":37,"license":38,"plugin":39},"HEAD","MIT",{"mcpCount":11,"provider":40,"skillCount":41},"classify",1,{"parentExtensionId":5,"repoId":43},"kd7etqyey7pjacrkp7wzfh4vts86nq1z",[33,22,20,31,32,30],{"evaluatedAt":46,"extractAt":47,"updatedAt":46},1778698417908,1778698371743,{"reviewCount":11},{"description":50,"installMethods":51,"name":53,"sourceUrl":16},"Hindsight: Agent Memory That  Learns",{"claudeCode":52},"vectorize-io/hindsight","hindsight-local",{"_creationTime":55,"_id":56,"extensionId":5,"locale":21,"result":57,"trustSignals":232,"workflow":248},1778698434665.2317,"kn7axc6py8cbdw8wyccspm697x86n992",{"checks":58,"evaluatedAt":207,"extensionSummary":208,"features":209,"nonGoals":214,"promptVersionExtension":218,"promptVersionScoring":27,"purpose":219,"rationale":220,"score":221,"summary":222,"tags":223,"targetMarket":34,"tier":227,"useCases":228},[59,64,67,70,74,77,82,87,90,93,97,101,104,108,111,114,117,120,123,126,130,134,139,143,148,151,154,157,161,164,167,170,173,176,179,183,187,191,194,198,201,204],{"category":60,"check":61,"severity":62,"summary":63},"Practical Utility","Problem relevance","pass","The description explicitly names \"agent memory that learns\" and contrasts it with systems that \"focus on recalling conversation history\", directly addressing a perceived shortcoming in existing solutions.",{"category":60,"check":65,"severity":62,"summary":66},"Unique selling proposition","Hindsight offers a novel approach to agent memory by focusing on learning over simple recall, utilizing biomimetic data structures and achieving state-of-the-art performance on memory benchmarks, which goes beyond simple prompt engineering or basic RAG.",{"category":60,"check":68,"severity":62,"summary":69},"Production readiness","The extension is documented as being used in production at Fortune 500 enterprises and by AI startups, with multiple installation methods (Docker, SDKs, embedded Python) and clear API documentation, indicating it is production-ready.",{"category":71,"check":72,"severity":62,"summary":73},"Scope","Single responsibility principle","The extension focuses on providing advanced agent memory capabilities, learning, and recall, aligning with its described purpose without introducing unrelated functionalities.",{"category":71,"check":75,"severity":62,"summary":76},"Description quality","The displayed description \"Hindsight: Agent Memory That Learns\" is concise, accurate, and aligns well with the core functionality described in the README.",{"category":78,"check":79,"severity":80,"summary":81},"Invocation","Scoped tools","not_applicable","This is a marketplace extension and does not expose tools directly. The underlying implementation details of hosted plugins were not evaluated.",{"category":83,"check":84,"severity":85,"summary":86},"Documentation","Configuration & parameter reference","info","While the README provides installation and basic usage examples, a detailed reference for all configuration parameters and their defaults across different LLM providers and storage options is not explicitly documented.",{"category":71,"check":88,"severity":80,"summary":89},"Tool naming","As a marketplace extension, it does not have user-facing tools to evaluate.",{"category":71,"check":91,"severity":80,"summary":92},"Minimal I/O surface","As a marketplace extension, it does not expose tools with parameter schemas or response shapes.",{"category":94,"check":95,"severity":62,"summary":96},"License","License usability","The project is licensed under the MIT License, as indicated by the LICENSE file and badges, which is a permissive open-source license.",{"category":98,"check":99,"severity":62,"summary":100},"Maintenance","Commit recency","The repository shows recent commits, with the last commit date being May 13, 2026, indicating active maintenance.",{"category":98,"check":102,"severity":62,"summary":103},"Dependency Management","The project uses `hindsight-client` and `hindsight-all` packages, and Docker images suggest it manages its dependencies. The presence of a lockfile (`hasLockfile: true`) indicates dependency pinning.",{"category":105,"check":106,"severity":85,"summary":107},"Security","Secret Management","The documentation mentions setting API keys (e.g., `OPENAI_API_KEY`) via environment variables for LLM providers, but there is no indication of secrets being echoed to stdout or committed.",{"category":105,"check":109,"severity":62,"summary":110},"Injection","The README and provided code examples do not suggest any loading or execution of untrusted third-party data as instructions.",{"category":105,"check":112,"severity":62,"summary":113},"Transitive Supply-Chain Grenades","The installation instructions and provided code examples do not involve runtime downloads of code or instructions from remote URLs, and all necessary components appear to be bundled.",{"category":105,"check":115,"severity":62,"summary":116},"Sandbox Isolation","The Docker installation and Python embedded examples do not show any operations that would write to or modify files outside of the expected data or runtime directories.",{"category":105,"check":118,"severity":62,"summary":119},"Sandbox escape primitives","No evidence of detached-process spawns or deny-retry loops was found in the provided code snippets or documentation.",{"category":105,"check":121,"severity":62,"summary":122},"Data Exfiltration","The documentation outlines the use of API keys for LLM providers, which are handled via environment variables. There is no indication of confidential data being submitted to third parties without explicit user action or consent.",{"category":105,"check":124,"severity":62,"summary":125},"Hidden Text Tricks","The bundled files and README content appear to be free of hidden-steering tricks, invisible characters, or obfuscated instructions.",{"category":127,"check":128,"severity":62,"summary":129},"Hooks","Opaque code execution","The provided Python and Node.js client examples, as well as the Docker installation, consist of plain, readable code and configuration, with no evidence of obfuscation or dynamic code fetching.",{"category":131,"check":132,"severity":62,"summary":133},"Portability","Structural Assumption","The extension's core functionality focuses on memory management, and the provided examples do not appear to make rigid assumptions about user project file layouts.",{"category":135,"check":136,"severity":137,"summary":138},"Trust","Issues Attention","warning","The repository has 70 open issues and 233 closed issues in the last 90 days, resulting in a closure rate of approximately 77% (233 / (70 + 233)), which is good. However, the high number of open issues (70) compared to the closure rate suggests maintainer bandwidth might be stretched, warranting a warning for potential slowness in addressing all issues.",{"category":140,"check":141,"severity":62,"summary":142},"Versioning","Release Management","The project has a `CHANGELOG.md` file and uses GitHub release tags, indicating clear versioning. The `pushedAt` date is recent, and a `LICENSE` file with a copyright year implies versioning.",{"category":144,"check":145,"severity":146,"summary":147},"Code Execution","Validation","insufficient_data","The provided README and code snippets do not offer enough detail to evaluate the use of schema validation libraries for input arguments or structured output sanitization.",{"category":105,"check":149,"severity":62,"summary":150},"Unguarded Destructive Operations","The primary operations (retain, recall, reflect) are data manipulation and retrieval, not destructive operations. Installation involves standard package management or Docker, which are typically guarded.",{"category":144,"check":152,"severity":146,"summary":153},"Error Handling","The provided README and code snippets do not detail the error handling mechanisms for the Hindsight client or server operations, making it impossible to assess their structure or meaningfulness.",{"category":144,"check":155,"severity":80,"summary":156},"Logging","As a marketplace extension, it does not have executable code or audit logs to evaluate. The underlying plugins' logging mechanisms were not assessed.",{"category":158,"check":159,"severity":85,"summary":160},"Compliance","GDPR","The extension handles user-provided content for memory storage and recall. While it doesn't explicitly claim to process personal data, its nature suggests personal data might be involved, and there's no explicit mention of GDPR-specific sanitization beyond what the LLM might naturally do.",{"category":158,"check":162,"severity":62,"summary":163},"Target market","The extension's functionality is general-purpose for AI agents and memory management, with no apparent regional or jurisdictional limitations. The `targetMarket` is global.",{"category":131,"check":165,"severity":62,"summary":166},"Runtime stability","The extension provides SDKs for Python and Node.js, and Docker images, suggesting cross-platform compatibility. The embedded Python example also indicates flexibility.",{"category":83,"check":168,"severity":62,"summary":169},"README","The README file is comprehensive, well-structured, and clearly states the extension's purpose and capabilities.",{"category":71,"check":171,"severity":80,"summary":172},"Tool surface size","As a marketplace extension, it does not expose a tool surface.",{"category":78,"check":174,"severity":80,"summary":175},"Overlapping near-synonym tools","As a marketplace extension, it does not expose tools with potentially overlapping names.",{"category":83,"check":177,"severity":62,"summary":178},"Phantom features","All features mentioned in the README, such as memory storage, recall, and reflection, are supported by the provided SDKs and API descriptions.",{"category":180,"check":181,"severity":62,"summary":182},"Install","Installation instruction","The README provides clear, copy-pasteable installation instructions for Docker, Python, and Node.js clients, including API key setup.",{"category":184,"check":185,"severity":146,"summary":186},"Errors","Actionable error messages","The README does not provide specific examples or details about the error messages emitted by the Hindsight client or server, making it impossible to assess their actionability.",{"category":188,"check":189,"severity":62,"summary":190},"Execution","Pinned dependencies","The `hasLockfile: true` in trust signals indicates that third-party dependencies are pinned. The Docker images also suggest a managed dependency environment.",{"category":71,"check":192,"severity":80,"summary":193},"Dry-run preview","As a marketplace extension, it does not expose commands with dry-run capabilities. The underlying Hindsight operations are primarily data retention and retrieval, not state-changing operations in the context of an agent executing tasks.",{"category":195,"check":196,"severity":146,"summary":197},"Protocol","Idempotent retry & timeouts","Information regarding the idempotency of mutating operations, per-call timeouts, and statelessness of the server between calls is not detailed in the README or provided code snippets.",{"category":158,"check":199,"severity":85,"summary":200},"Telemetry opt-in","The README mentions a telemetry pixel in the footer for usage tracking, but it's unclear if this is opt-in or opt-out, or if it collects any specific data beyond basic analytics.",{"category":71,"check":202,"severity":62,"summary":203},"Theme declaration","The marketplace description explicitly states the theme: \"Hindsight: Agent Memory That Learns\", and the README further details its focus on learning over simple recall.",{"category":140,"check":205,"severity":80,"summary":206},"Per-entry version metadata","This is a single extension entry for the marketplace, not an index of multiple plugins, so per-entry version metadata is not applicable.",1778698434555,"Hindsight is an agent memory system that goes beyond simple conversation history recall, focusing on enabling AI agents to learn over time. It uses biomimetic data structures for memory organization and provides APIs for retaining, recalling, and reflecting on information, claiming state-of-the-art performance on memory benchmarks.",[210,211,212,213],"Learns over time, not just recalls history","Biomimetic memory organization (World, Experiences, Mental Models)","High-performance memory recall and reflection capabilities","Multiple integration methods (SDKs, Docker, embedded)",[215,216,217],"Simple conversation history recall as the primary function","Basic RAG or knowledge graph limitations","Overkill for simple AI workflows with basic needs","3.1.0","To provide AI agents with a sophisticated memory system that facilitates learning and long-term recall, enhancing their ability to handle complex tasks and approximate human-like intelligence.","High quality documentation and recent commits lead to a verified tier. 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user preferences, learnings from tasks, and procedure outcomes. Use to remember what works and recall context before new tasks. (user)",{"claudeCode":52},"SKILL.md frontmatter at skills/hindsight-local/SKILL.md",[478],{"path":312,"priority":275},{"basePath":480,"description":481,"displayName":482,"installMethods":483,"rationale":484,"selectedPaths":485,"source":281,"sourceLanguage":21,"type":313},"skills/hindsight-self-hosted","Store team knowledge, project conventions, and learnings from tasks. Use to remember what works and recall context before new tasks. Connects to a self-hosted Hindsight server. (user)","hindsight-self-hosted",{"claudeCode":52},"SKILL.md frontmatter at skills/hindsight-self-hosted/SKILL.md",[486],{"path":312,"priority":275},{"basePath":488,"description":489,"displayName":490,"installMethods":491,"license":492,"rationale":493,"selectedPaths":494,"source":281,"sourceLanguage":21,"type":499},"hindsight-control-plane","Control plane for Hindsight - Semantic memory system","@vectorize-io/hindsight-control-plane",{"npm":490},"ISC","cli ecosystem detected at hindsight-control-plane",[495,497],{"path":496,"priority":275},"package.json",{"path":498,"priority":292},"bin/cli.js","cli",{"basePath":501,"description":502,"displayName":503,"installMethods":504,"license":38,"rationale":505,"selectedPaths":506,"source":281,"sourceLanguage":21,"type":499},"hindsight-integrations/nemoclaw","Setup CLI for hindsight-openclaw on NemoClaw sandboxes — installs the plugin, configures external API mode, and applies the OpenShell network 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