[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"extension-skill-cdeust-cortex-import-zh-CN":3,"guides-for-cdeust-cortex-import":775,"similar-k170pg7b0gzt2k4qjd0gcsqqn586mzf4-zh-CN":776},{"_creationTime":4,"_id":5,"children":6,"community":7,"display":9,"evaluation":15,"identity":243,"isFallback":225,"parentExtension":248,"providers":306,"relations":310,"repo":311,"tags":773,"workflow":774},1778683562157.8765,"k170pg7b0gzt2k4qjd0gcsqqn586mzf4",[],{"reviewCount":8},0,{"description":10,"installMethods":11,"name":13,"sourceUrl":14},"Import memories from other AI memory systems into Cortex. Supports claude-mem (SQLite), Claude Desktop sessions, ChatGPT web export (JSON), Gemini Takeout (JSON), Cursor conversations, and Claude Code JSONL. Use when the user says 'import from claude-mem', 'migrate memories', 'import ChatGPT history', 'import from Gemini', 'transfer memories', or when Cortex detects another memory system is installed.",{"claudeCode":12},"cdeust/Cortex","cortex-import","https://github.com/cdeust/Cortex",{"_creationTime":16,"_id":17,"extensionId":5,"locale":18,"result":19,"trustSignals":223,"workflow":241},1778683713692.2224,"kn74t2f31kjxf95apfjzwmsewh86nvyc","en",{"checks":20,"evaluatedAt":193,"extensionSummary":194,"features":195,"nonGoals":200,"promptVersionExtension":204,"promptVersionScoring":205,"purpose":206,"rationale":207,"score":208,"summary":209,"tags":210,"targetMarket":216,"tier":217,"useCases":218},[21,26,29,32,36,39,43,48,51,54,58,62,65,69,72,75,78,81,84,87,91,95,99,103,107,110,114,117,121,124,127,130,134,137,140,144,148,152,155,159,162,165,168,171,175,178,181,184,187,190],{"category":22,"check":23,"severity":24,"summary":25},"Practical Utility","Problem relevance","pass","The description clearly states the problem of importing memories from various AI systems into Cortex and names specific triggers for its use.",{"category":22,"check":27,"severity":24,"summary":28},"Unique selling proposition","The skill provides a comprehensive, automated import process for multiple memory systems, going beyond a simple wrapper by orchestrating detection, extraction, and consolidation.",{"category":22,"check":30,"severity":24,"summary":31},"Production readiness","The extension appears to cover the complete lifecycle for memory import from various sources, with detailed instructions and scripts.",{"category":33,"check":34,"severity":24,"summary":35},"Scope","Single responsibility principle","The extension focuses solely on importing memories from different AI systems into Cortex, adhering to a single responsibility.",{"category":33,"check":37,"severity":24,"summary":38},"Description quality","The description accurately reflects the skill's functionality, listing supported systems, use cases, and triggers.",{"category":40,"check":41,"severity":24,"summary":42},"Invocation","Scoped tools","The skill primarily uses specific `cortex:backfill_memories` and `mcp_server.handlers.remember` calls, which are scoped actions, rather than a single generalist tool.",{"category":44,"check":45,"severity":46,"summary":47},"Documentation","Configuration & parameter reference","info","While many commands and Python scripts are provided, explicit documentation of all parameters, defaults, and precedence orders for environment variables is not fully detailed.",{"category":33,"check":49,"severity":24,"summary":50},"Tool naming","The exposed tools and commands like `cortex:backfill_memories` and `cortex:consolidate` are descriptive and domain-specific.",{"category":33,"check":52,"severity":24,"summary":53},"Minimal I/O surface","The provided commands and scripts appear to request only necessary data and return specific results, such as import counts.",{"category":55,"check":56,"severity":24,"summary":57},"License","License usability","The extension is licensed under MIT, which is a permissive open-source license.",{"category":59,"check":60,"severity":24,"summary":61},"Maintenance","Commit recency","The repository shows recent commits, indicating active maintenance.",{"category":59,"check":63,"severity":24,"summary":64},"Dependency Management","The project utilizes Python's package management and includes setup scripts, implying a managed dependency approach.",{"category":66,"check":67,"severity":24,"summary":68},"Security","Secret Management","The extension runs locally and processes user data on the machine, with no indication of secrets being echoed or mishandled.",{"category":66,"check":70,"severity":24,"summary":71},"Injection","The scripts process data from known sources and use Python's JSON/SQLite libraries, indicating that external data is treated as data, not instructions.",{"category":66,"check":73,"severity":24,"summary":74},"Transitive Supply-Chain Grenades","The extension relies on bundled scripts and local Python execution, with no runtime downloads or remote code execution patterns detected.",{"category":66,"check":76,"severity":24,"summary":77},"Sandbox Isolation","The scripts operate within the user's home directory and local file system, with no indications of attempting to modify files outside the project or user-specific scopes.",{"category":66,"check":79,"severity":24,"summary":80},"Sandbox escape primitives","No detached process spawns or retry loops around denied tool calls were found in the provided scripts.",{"category":66,"check":82,"severity":24,"summary":83},"Data Exfiltration","The extension processes local data and has no outbound network calls documented or implied, thus preventing data exfiltration.",{"category":66,"check":85,"severity":24,"summary":86},"Hidden Text Tricks","The bundled content and descriptions appear to be free of hidden steering tricks or malicious Unicode characters.",{"category":88,"check":89,"severity":24,"summary":90},"Hooks","Opaque code execution","The provided scripts are in plain Python and Bash, with no signs of obfuscation, base64 payloads, or runtime code fetching.",{"category":92,"check":93,"severity":24,"summary":94},"Portability","Structural Assumption","The scripts use standard user home directory paths (`~/.claude`, `~/Library`, `~/Downloads`) and make reasonable assumptions about file system structure.",{"category":96,"check":97,"severity":24,"summary":98},"Trust","Issues Attention","With 0 open issues and 16 closed in the last 90 days, maintainer engagement appears high.",{"category":100,"check":101,"severity":24,"summary":102},"Versioning","Release Management","The extension declares a version in its README and has a history of meaningful version updates.",{"category":104,"check":105,"severity":46,"summary":106},"Code Execution","Validation","While the scripts handle file paths and JSON data, explicit schema validation libraries like Zod or Pydantic are not apparent for all inputs.",{"category":66,"check":108,"severity":24,"summary":109},"Unguarded Destructive Operations","The operations performed are data import and consolidation, which are not destructive in nature and do not require guards.",{"category":104,"check":111,"severity":112,"summary":113},"Error Handling","warning","The Python scripts use basic try-except blocks, but error reporting is not consistently structured with codes and retry hints, potentially stalling the agent.",{"category":104,"check":115,"severity":24,"summary":116},"Logging","The scripts provide output indicating progress and counts, serving as a form of audit log for the import process.",{"category":118,"check":119,"severity":24,"summary":120},"Compliance","GDPR","The extension operates on local memory files and does not interact with third parties or submit personal data.",{"category":118,"check":122,"severity":24,"summary":123},"Target market","The extension operates on local files and has no regional restrictions, making it globally applicable.",{"category":92,"check":125,"severity":24,"summary":126},"Runtime stability","The scripts use standard bash and Python 3, which are widely available, and rely on common file system paths.",{"category":44,"check":128,"severity":24,"summary":129},"README","The README provides a comprehensive overview of the project, its science, architecture, and usage.",{"category":33,"check":131,"severity":132,"summary":133},"Tool surface size","not_applicable","This is a skill, not a toolset with multiple exposed commands.",{"category":40,"check":135,"severity":132,"summary":136},"Overlapping near-synonym tools","The skill uses specific MCP commands and shell scripts, not a list of near-synonym tools.",{"category":44,"check":138,"severity":24,"summary":139},"Phantom features","All advertised features, such as importing from various memory systems, are implemented and described in the SKILL.md and README.",{"category":141,"check":142,"severity":24,"summary":143},"Install","Installation instruction","The README provides clear installation instructions, including marketplace commands and verification steps.",{"category":145,"check":146,"severity":112,"summary":147},"Errors","Actionable error messages","While scripts may exit with errors, the messages are not consistently framed with what failed, why, and a remediation step, potentially hindering agent troubleshooting.",{"category":149,"check":150,"severity":46,"summary":151},"Execution","Pinned dependencies","Python scripts are present, but explicit pinning of interpreter versions and side-effect declarations via shebang headers are not consistently applied.",{"category":33,"check":153,"severity":132,"summary":154},"Dry-run preview","The extension's primary function is data import and consolidation, which is not a state-changing operation requiring a dry-run mode.",{"category":156,"check":157,"severity":132,"summary":158},"Protocol","Idempotent retry & timeouts","The extension performs local file operations and database inserts; there are no remote calls or state-changing operations requiring specific retry or timeout handling.",{"category":118,"check":160,"severity":24,"summary":161},"Telemetry opt-in","The extension operates locally and does not emit any telemetry.",{"category":40,"check":163,"severity":24,"summary":164},"Precise Purpose","The description and SKILL.md clearly state the purpose of importing memories and specify the supported systems and triggers.",{"category":40,"check":166,"severity":24,"summary":167},"Concise Frontmatter","The frontmatter in SKILL.md is concise, self-contained, and includes trigger phrases.",{"category":44,"check":169,"severity":24,"summary":170},"Concise Body","The SKILL.md is well-structured and under the ~500-line limit, delegating detailed content to other files.",{"category":172,"check":173,"severity":24,"summary":174},"Context","Progressive Disclosure","Detailed procedures and scientific explanations are either in separate files or well-sectioned within the README and SKILL.md, enabling progressive disclosure.",{"category":172,"check":176,"severity":132,"summary":177},"Forked exploration","This skill performs a discrete import task and does not engage in deep exploration requiring a forked context.",{"category":22,"check":179,"severity":24,"summary":180},"Usage examples","The SKILL.md and README provide clear, runnable examples for different import scenarios, including fallback instructions.",{"category":22,"check":182,"severity":112,"summary":183},"Edge cases","While various import scenarios are covered, the documentation does not explicitly list failure modes (e.g., malformed JSON, database errors) with corresponding recovery steps.",{"category":104,"check":185,"severity":132,"summary":186},"Tool Fallback","The skill primarily uses local scripts and internal MCP commands; it does not rely on external, optional tools like a custom MCP server.",{"category":92,"check":188,"severity":24,"summary":189},"Halt on unexpected state","The scripts and Python code include checks for file existence and basic conditions, and are expected to exit non-zero on failure, halting the workflow.",{"category":92,"check":191,"severity":24,"summary":192},"Cross-skill coupling","The skill is self-contained and focuses solely on memory import; it does not implicitly rely on or explicitly cross-reference other skills.",1778683713572,"This skill imports memories from various AI systems (claude-mem, Claude Desktop, ChatGPT, Gemini, Cursor) into Cortex using local scripts and MCP calls. It handles detection, import, and consolidation.",[196,197,198,199],"Automated detection of multiple memory sources","Import from SQLite, JSON, JSONL, and binary formats","Consolidation of imported memories","Local execution with no data leaving the user's machine",[201,202,203],"Exporting memories from Cortex.","Real-time synchronization with other memory systems.","Cloud-based memory storage or processing.","3.0.0","4.4.0","Seamlessly migrate and consolidate AI memories from diverse sources into Cortex for a unified and persistent knowledge base.","The extension is well-documented, production-ready, and adheres to good security practices. The primary areas for improvement are more detailed parameter documentation and more actionable error messages.",75,"A robust skill for importing AI memories, offering comprehensive functionality and good documentation.",[211,212,213,214,215],"memory","import","migration","data","claude","global","community",[219,220,221,222],"Migrate memories from claude-mem to Cortex.","Transfer ChatGPT conversation history into Cortex.","Consolidate Gemini memories after using Takeout.","Import memories from Claude Code sessions.",{"codeQuality":224,"collectedAt":226,"documentation":227,"maintenance":230,"popularity":235,"security":237,"testCoverage":240},{"hasLockfile":225},true,1778683687022,{"descriptionLength":228,"readmeSize":229},404,36381,{"closedIssues90d":231,"forks":232,"hasChangelog":225,"openIssues90d":8,"pushedAt":233,"stars":234},16,8,1778675198000,33,{"npmDownloads":236},14,{"hasNpmPackage":225,"license":238,"smitheryVerified":239},"NOASSERTION",false,{"hasCi":225,"hasTests":225},{"updatedAt":242},1778683713692,{"basePath":244,"githubOwner":245,"githubRepo":246,"locale":18,"slug":13,"type":247},"skills/cortex-import","cdeust","Cortex","skill",{"_creationTime":249,"_id":250,"community":251,"display":252,"identity":255,"parentExtension":258,"providers":293,"relations":302,"tags":303,"workflow":304},1778683562157.8752,"k1739s9t9kj9bmjq1z4byk17g986mv7x",{"reviewCount":8},{"description":253,"installMethods":254,"name":246,"sourceUrl":14},"Persistent memory and cognitive profiling for Claude Code — thermodynamic memory with heat/decay, intent-aware retrieval, biological plasticity, codebase intelligence, and cognitive profiling. 47 MCP tools with enriched schemas. PostgreSQL + pgvector in CLI mode; automatic SQLite fallback in Cowork/sandboxed mode. Curated wiki (ADRs, specs, lessons) with audit-artefact filtering. Consolidate is set-based SQL batched — decay/plasticity/pruning run 100-500× faster on large stores. Workflow graph with caller-qualified CALLS chains rendering full method-to-method dependencies (native tree-sitter, no AP required). Side panel humanized for non-technical users. Ingests codebase analysis (ai-automatised-pipeline) and PRDs (prd-spec-generator) into wiki + memory + knowledge graph. Docker image available.",{"claudeCode":246},{"basePath":256,"githubOwner":245,"githubRepo":246,"locale":18,"slug":246,"type":257},"","plugin",{"_creationTime":259,"_id":260,"community":261,"display":262,"identity":266,"providers":268,"relations":287,"tags":289,"workflow":290},1778683562157.875,"k174pnm5ch9ab6fr1etef2f2b586m74b",{"reviewCount":8},{"description":263,"installMethods":264,"name":265,"sourceUrl":14},"Persistent memory and cognitive profiling plugins for Claude Code",{"claudeCode":12},"cortex-plugins",{"basePath":256,"githubOwner":245,"githubRepo":246,"locale":18,"slug":246,"type":267},"marketplace",{"evaluate":269,"extract":281},{"promptVersionExtension":270,"promptVersionScoring":205,"score":271,"tags":272,"targetMarket":216,"tier":280},"3.1.0",100,[211,273,274,275,276,277,278,279],"cognitive-profiling","mcp","claude-code","knowledge-graph","codebase-analysis","postgresql","pgvector","verified",{"commitSha":282,"marketplace":283,"plugin":285},"HEAD",{"name":265,"pluginCount":284},1,{"mcpCount":8,"provider":286,"skillCount":8},"classify",{"repoId":288},"kd79gxpemvkr09a7zsb3h8kmah86nvgf",[275,277,273,276,274,211,279,278],{"evaluatedAt":291,"extractAt":292,"updatedAt":291},1778683583007,1778683562157,{"evaluate":294,"extract":299},{"promptVersionExtension":204,"promptVersionScoring":205,"score":295,"tags":296,"targetMarket":216,"tier":280},99,[211,297,276,273,278,279,298],"persistence","developer-tools",{"commitSha":282,"license":300,"plugin":301},"MIT",{"mcpCount":8,"provider":286,"skillCount":236},{"parentExtensionId":260,"repoId":288},[273,298,276,211,297,279,278],{"evaluatedAt":305,"extractAt":292,"updatedAt":305},1778683602463,{"evaluate":307,"extract":309},{"promptVersionExtension":204,"promptVersionScoring":205,"score":208,"tags":308,"targetMarket":216,"tier":217},[211,212,213,214,215],{"commitSha":282},{"parentExtensionId":250,"repoId":288},{"_creationTime":312,"_id":288,"identity":313,"providers":314,"workflow":768},1778683544930.988,{"githubOwner":245,"githubRepo":246,"sourceUrl":14},{"classify":315,"discover":741,"extract":744,"github":745,"npm":767},{"commitSha":282,"extensions":316},[317,330,343,352,360,368,376,381,389,397,405,413,421,429,437,445,453],{"basePath":256,"description":263,"displayName":265,"installMethods":318,"rationale":319,"selectedPaths":320,"source":329,"sourceLanguage":18,"type":267},{"claudeCode":12},"marketplace.json at .claude-plugin/marketplace.json",[321,324,326],{"path":322,"priority":323},".claude-plugin/marketplace.json","mandatory",{"path":325,"priority":323},"README.md",{"path":327,"priority":328},"LICENSE","high","rule",{"basePath":256,"description":253,"displayName":331,"installMethods":332,"rationale":333,"selectedPaths":334,"source":329,"sourceLanguage":18,"type":257},"cortex",{"claudeCode":246},"inline plugin source from marketplace.json at /",[335,336,337,339,341],{"path":325,"priority":323},{"path":327,"priority":328},{"path":338,"priority":323},".mcp.json",{"path":340,"priority":328},"agents/cortex-wiki-groomer.md",{"path":342,"priority":328},"commands/methodology.md",{"basePath":344,"description":345,"displayName":346,"installMethods":347,"rationale":348,"selectedPaths":349,"source":329,"sourceLanguage":18,"type":247},"skills/cortex-automate","Set up automation — prospective memory triggers, neuro-symbolic rules, and CLAUDE.md sync. Use when the user says 'remind me when', 'trigger when', 'create a rule', 'auto-remember', 'sync to CLAUDE.md', 'push insights', 'set up trigger', 'when I open this file', 'when this keyword appears', or when you want to automate memory behavior based on conditions.","cortex-automate",{"claudeCode":12},"SKILL.md frontmatter at skills/cortex-automate/SKILL.md",[350],{"path":351,"priority":323},"SKILL.md",{"basePath":353,"description":354,"displayName":355,"installMethods":356,"rationale":357,"selectedPaths":358,"source":329,"sourceLanguage":18,"type":247},"skills/cortex-consolidate","Run memory maintenance — decay old memories, compress stale content, consolidate episodic memories into semantic knowledge, and run sleep-like replay. Use when the user says 'clean up memories', 'consolidate', 'run maintenance', 'compress old memories', 'memory cleanup', or periodically to keep the memory system healthy. Also use after importing many memories or at the end of a long session.","cortex-consolidate",{"claudeCode":12},"SKILL.md frontmatter at skills/cortex-consolidate/SKILL.md",[359],{"path":351,"priority":323},{"basePath":361,"description":362,"displayName":363,"installMethods":364,"rationale":365,"selectedPaths":366,"source":329,"sourceLanguage":18,"type":247},"skills/cortex-debug-memory","Debug and fix memory system issues — validate memories, rate quality, manage protection, forget bad memories, and restore from checkpoints. Use when the user says 'fix memory', 'bad memory', 'wrong memory', 'delete this', 'protect this', 'this memory is wrong', 'memory quality', 'rate this memory', 'restore checkpoint', 'undo', or when memories are returning incorrect or stale results.","cortex-debug-memory",{"claudeCode":12},"SKILL.md frontmatter at skills/cortex-debug-memory/SKILL.md",[367],{"path":351,"priority":323},{"basePath":369,"description":370,"displayName":371,"installMethods":372,"rationale":373,"selectedPaths":374,"source":329,"sourceLanguage":18,"type":247},"skills/cortex-explore-memory","Explore the memory system's state, find gaps in knowledge, assess coverage, and get diagnostic information. Use when the user asks 'what does my memory look like', 'show me memory stats', 'what am I missing', 'how good is my knowledge', 'memory health', 'show coverage', 'find gaps', 'what topics are weak', or when you need to understand the state of stored knowledge before a task.","cortex-explore-memory",{"claudeCode":12},"SKILL.md frontmatter at skills/cortex-explore-memory/SKILL.md",[375],{"path":351,"priority":323},{"basePath":244,"description":10,"displayName":13,"installMethods":377,"rationale":378,"selectedPaths":379,"source":329,"sourceLanguage":18,"type":247},{"claudeCode":12},"SKILL.md frontmatter at skills/cortex-import/SKILL.md",[380],{"path":351,"priority":323},{"basePath":382,"description":383,"displayName":384,"installMethods":385,"rationale":386,"selectedPaths":387,"source":329,"sourceLanguage":18,"type":247},"skills/cortex-navigate-knowledge","Navigate the knowledge graph — trace entity relationships, explore causal chains, drill into memory clusters, and traverse co-access paths. Use when the user asks 'how are these related', 'what connects X to Y', 'show me the knowledge graph', 'trace the relationship', 'what caused X', 'drill down into', 'explore connections', or when you need to understand the web of relationships between concepts, entities, and memories.","cortex-navigate-knowledge",{"claudeCode":12},"SKILL.md frontmatter at skills/cortex-navigate-knowledge/SKILL.md",[388],{"path":351,"priority":323},{"basePath":390,"description":391,"displayName":392,"installMethods":393,"rationale":394,"selectedPaths":395,"source":329,"sourceLanguage":18,"type":247},"skills/cortex-profile","View and manage your cognitive profile — how you think, work patterns, blind spots, and cross-domain connections. Use when the user says 'show my profile', 'how do I work', 'what are my patterns', 'cognitive style', 'blind spots', 'methodology', or at the start of a session to load context. Also use 'rebuild profile' to rescan all session history, or 'list domains' to see all tracked project domains.","cortex-profile",{"claudeCode":12},"SKILL.md frontmatter at skills/cortex-profile/SKILL.md",[396],{"path":351,"priority":323},{"basePath":398,"description":399,"displayName":400,"installMethods":401,"rationale":402,"selectedPaths":403,"source":329,"sourceLanguage":18,"type":247},"skills/cortex-recall","Search and retrieve memories from Cortex persistent memory. Use when the user asks 'what did we decide about X', 'do you remember', 'what was the fix for', 'find that thing about', 'search memories', 'what do we know about', 'have we seen this before', or when you need context about past decisions, patterns, bugs, or architecture choices. Also use proactively when working on something that likely has relevant historical context.","cortex-recall",{"claudeCode":12},"SKILL.md frontmatter at skills/cortex-recall/SKILL.md",[404],{"path":351,"priority":323},{"basePath":406,"description":407,"displayName":408,"installMethods":409,"rationale":410,"selectedPaths":411,"source":329,"sourceLanguage":18,"type":247},"skills/cortex-recall-global","Search and retrieve global memories — knowledge that applies across all projects. Use when the user asks 'what are our coding standards', 'what conventions do we follow', 'what's our infrastructure setup', 'do we have a rule about', 'what applies to all projects', 'shared knowledge', 'global rules', or when you need cross-project context like architecture decisions, server configs, or team policies.","cortex-recall-global",{"claudeCode":12},"SKILL.md frontmatter at skills/cortex-recall-global/SKILL.md",[412],{"path":351,"priority":323},{"basePath":414,"description":415,"displayName":416,"installMethods":417,"rationale":418,"selectedPaths":419,"source":329,"sourceLanguage":18,"type":247},"skills/cortex-remember","Store important decisions, patterns, errors, lessons, and context into Cortex persistent memory. Use when the user says 'remember this', 'save this', 'store this for later', 'note this down', 'don't forget', 'this is important', 'bookmark this', or when a significant decision, bug fix, architecture choice, or lesson learned occurs during a session. Also use after resolving tricky bugs, making technology choices, or discovering important patterns.","cortex-remember",{"claudeCode":12},"SKILL.md frontmatter at skills/cortex-remember/SKILL.md",[420],{"path":351,"priority":323},{"basePath":422,"description":423,"displayName":424,"installMethods":425,"rationale":426,"selectedPaths":427,"source":329,"sourceLanguage":18,"type":247},"skills/cortex-remember-global","Store a global memory that is visible across all projects. Use when the user shares architecture rules, coding conventions, infrastructure facts, security policies, team agreements, or any knowledge that applies beyond a single project. Triggers on 'remember this everywhere', 'this applies to all projects', 'global rule', 'shared convention', 'infrastructure note', 'cross-project', or when the content is clearly universal (clean architecture, SOLID, deployment configs, server addresses).","cortex-remember-global",{"claudeCode":12},"SKILL.md frontmatter at skills/cortex-remember-global/SKILL.md",[428],{"path":351,"priority":323},{"basePath":430,"description":431,"displayName":432,"installMethods":433,"rationale":434,"selectedPaths":435,"source":329,"sourceLanguage":18,"type":247},"skills/cortex-setup-project","Bootstrap Cortex for a new project or import existing session history. Use when the user says 'set up Cortex', 'seed this project', 'import my history', 'backfill memories', 'bootstrap memory', 'initialize Cortex for this project', or when starting to use Cortex on an existing codebase that already has Claude Code conversation history.","cortex-setup-project",{"claudeCode":12},"SKILL.md frontmatter at skills/cortex-setup-project/SKILL.md",[436],{"path":351,"priority":323},{"basePath":438,"description":439,"displayName":440,"installMethods":441,"rationale":442,"selectedPaths":443,"source":329,"sourceLanguage":18,"type":247},"skills/cortex-visualize","Launch the interactive unified neural graph visualization. Use when the user says 'show visualization', 'show me the graph', 'visualize memories', 'show memory map', 'open neural graph', or when a visual overview of the memory system or cognitive profile would be helpful.","cortex-visualize",{"claudeCode":12},"SKILL.md frontmatter at skills/cortex-visualize/SKILL.md",[444],{"path":351,"priority":323},{"basePath":446,"description":447,"displayName":448,"installMethods":449,"rationale":450,"selectedPaths":451,"source":329,"sourceLanguage":18,"type":247},"skills/cortex-wiki-author","Author first-class wiki pages (ADRs, specs, file docs, notes) that live alongside Cortex memory. Use when the user says 'this is an ADR', 'document this decision', 'write an ADR', 'add a spec', 'spec this out', 'document this file', 'add a note about', 'link these pages', 'bookmark this as a spec', or when finalizing a design decision that should persist as a human-readable document.","cortex-wiki-author",{"claudeCode":12},"SKILL.md frontmatter at skills/cortex-wiki-author/SKILL.md",[452],{"path":351,"priority":323},{"basePath":256,"description":454,"displayName":455,"installMethods":456,"license":300,"rationale":457,"selectedPaths":458,"source":329,"sourceLanguage":18,"type":274},"Persistent memory and cognitive profiling for Claude Code","neuro-cortex-memory",{"pypi":455},"pyproject.toml with mcp/fastmcp dependency + scripts at 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ndlers/test_seed_project.py",{"path":736,"priority":470},"tests_py/handlers/test_wiki_redirect_handlers.py",{"path":738,"priority":470},"tests_py/handlers/test_wiki_seed_codebase.py",{"path":740,"priority":470},"tests_py/handlers/test_wiki_sync_errors.py",{"sources":742},[743],"manual",{"npmPackage":455},{"closedIssues90d":231,"description":746,"forks":232,"homepage":747,"license":238,"openIssues90d":8,"pushedAt":233,"readmeSize":229,"stars":234,"topics":748},"Persistent memory for Claude Code — 41 neuroscience papers, 26 biological mechanisms with paper-bearing per-mechanism ablation evidence (E1 v3). LongMemEval R@10 98.4% / MRR 0.9124 (n=500). LoCoMo R@10 94.2% / MRR 0.8278 (n=1986). BEAM-10M +33.4% over flat retrieval. PostgreSQL + pgvector. Verified via 31-row two-benchmark ablation campaign.","https://ai-architect.tools",[749,750,751,752,275,753,754,755,756,757,758,759,760,761,762,763,764,765,766,215],"mcp-server","model-context-protocol","agent-memory-system","causal-inference","claude-code-plugin","cognitive-architecture","cognitive-science","neuroscience","persistent-memory","predictive-coding","retrieval-augmented-generation","vector-search","hopfield-network","long-term-memory","episodic-memory","llm-memory","anthropic","artificial-intelligence",{"downloads":236},{"classifiedAt":769,"discoverAt":770,"extractAt":771,"githubAt":771,"npmAt":772,"updatedAt":769},1778683561790,1778683544931,1778683554398,1778683559402,[215,214,212,211,213],{"evaluatedAt":242,"extractAt":292,"updatedAt":242},[],[777,805,833,864,892,922],{"_creationTime":778,"_id":779,"community":780,"display":781,"identity":787,"providers":792,"relations":799,"tags":801,"workflow":802},1778696691708.307,"k176zwpf986zp7jmtfwp20fnfh86mcws",{"reviewCount":8},{"description":782,"installMethods":783,"name":785,"sourceUrl":786},"Unify 6+ memory systems into AgentDB with HNSW indexing for 150x-12,500x search improvements. Implements ADR-006 (Unified Memory Service) and ADR-009 (Hybrid Memory Backend).",{"claudeCode":784},"ruvnet/ruflo","V3 Memory Unification","https://github.com/ruvnet/ruflo",{"basePath":788,"githubOwner":789,"githubRepo":790,"locale":18,"slug":791,"type":247},".claude/skills/v3-memory-unification","ruvnet","ruflo","v3-memory-unification",{"evaluate":793,"extract":798},{"promptVersionExtension":204,"promptVersionScoring":205,"score":295,"tags":794,"targetMarket":216,"tier":280},[211,795,796,797,213,760],"database","agentdb","hnsw",{"commitSha":282,"license":300},{"repoId":800},"kd7ed28gj8n0y3msk5dzrp05zs86nqtc",[796,795,797,211,213,760],{"evaluatedAt":803,"extractAt":804,"updatedAt":803},1778699464598,1778696691708,{"_creationTime":806,"_id":807,"community":808,"display":809,"identity":815,"providers":819,"relations":827,"tags":829,"workflow":830},1778696993586.708,"k17fsfrfvbnsvwkcqp8y85wdad86mmwq",{"reviewCount":8},{"description":810,"installMethods":811,"name":813,"sourceUrl":814},"Stop and consult this skill whenever your response would include specific facts about Anthropic's products. Covers: Claude Code (how to install, Node.js requirements, platform/OS support, MCP server integration, configuration), Claude API (function calling/tool use, batch processing, SDK usage, rate limits, pricing, models, streaming), and Claude.ai (Pro vs Team vs Enterprise plans, feature limits). Trigger this even for coding tasks that use the Anthropic SDK, content creation mentioning Claude capabilities or pricing, or LLM provider comparisons. Any time you would otherwise rely on memory for Anthropic product details, verify here instead — your training data may be outdated or wrong.",{"claudeCode":812},"SeifBenayed/claude-code-sdk","product-self-knowledge","https://github.com/SeifBenayed/claude-code-sdk",{"basePath":816,"githubOwner":817,"githubRepo":818,"locale":18,"slug":813,"type":247},".claude/skills/product-self-knowledge","SeifBenayed","claude-code-sdk",{"evaluate":820,"extract":826},{"promptVersionExtension":204,"promptVersionScoring":205,"score":271,"tags":821,"targetMarket":216,"tier":280},[765,822,215,823,824,825],"documentation","api","sdk","knowledge-base",{"commitSha":282},{"repoId":828},"kd78s53c1852h5p7c3qem663xs86njab",[765,823,215,822,825,824],{"evaluatedAt":831,"extractAt":832,"updatedAt":831},1778697182451,1778696993586,{"_creationTime":834,"_id":835,"community":836,"display":837,"identity":843,"providers":847,"relations":857,"tags":860,"workflow":861},1778694720643.0347,"k1701tz3ryvkv5zkmv8ymbgz2186mweb",{"reviewCount":8},{"description":838,"installMethods":839,"name":841,"sourceUrl":842},"Generative Engine Optimization (GEO) — make content rank in AI search answers from ChatGPT, Claude, Perplexity, Gemini, and Google AI Overviews. Audits existing content, rewrites for AI citation, and produces per-engine strategy. Use when asked to \"optimize for AI search\", \"rank in ChatGPT\", \"GEO audit\", \"improve AI citations\", \"rank in Perplexity\", \"AI Overview optimization\", \"AI Overview ranking\", \"LLM SEO\", \"answer engine optimization\", \"AEO\", \"get cited by AI\", \"GEO\", \"generative engine optimization\", \"show up in ChatGPT\", \"appear in AI answers\", \"be cited by Perplexity\", \"SGE optimization\", \"Search Generative Experience\", or \"make my content show up in AI answers\". Distinct from regular SEO — this targets generative engines, not traditional Google rankings.\n",{"claudeCode":840},"nowork-studio/toprank","geo-optimizer","https://github.com/nowork-studio/toprank",{"basePath":844,"githubOwner":845,"githubRepo":846,"locale":18,"slug":841,"type":247},"seo/geo-optimizer","nowork-studio","toprank",{"evaluate":848,"extract":856},{"promptVersionExtension":204,"promptVersionScoring":205,"score":271,"tags":849,"targetMarket":216,"tier":280},[850,851,852,853,854,855,215],"seo","content-optimization","ai-search","perplexity","chatgpt","gemini",{"commitSha":282},{"parentExtensionId":858,"repoId":859},"k17dxqwvvhjw9ft30d5zz356z986my6s","kd74wn8s89tp9hrfsmcra492r586nbrv",[852,854,215,851,855,853,850],{"evaluatedAt":862,"extractAt":863,"updatedAt":862},1778695016147,1778694720643,{"_creationTime":865,"_id":866,"community":867,"display":868,"identity":874,"providers":879,"relations":886,"tags":888,"workflow":889},1778688112811.741,"k17fdp3d35dpxhrwm32z7cgzgh86mkc2",{"reviewCount":8},{"description":869,"installMethods":870,"name":872,"sourceUrl":873},"Write search-optimized content that ranks on Google using proven frameworks from Ahrefs, Moz, and Google's E-E-A-T guidelines—create helpful, people-first content that satisfies both search engines and readers. Use when: **Write blog posts** optimized for search engines; **Create pillar content** for topical authority; **Optimize existing content** for better rankings; **Write product or service pages** that rank; **Create how-to guides** and tutorials",{"claudeCode":871},"guia-matthieu/clawfu-skills","SEO Content Writer","https://github.com/guia-matthieu/clawfu-skills",{"basePath":875,"githubOwner":876,"githubRepo":877,"locale":18,"slug":878,"type":247},"skills/content/seo-content-writer","guia-matthieu","clawfu-skills","seo-content-writer",{"evaluate":880,"extract":885},{"promptVersionExtension":204,"promptVersionScoring":205,"score":271,"tags":881,"targetMarket":216,"tier":280},[850,882,883,884,215],"content-writing","marketing","openai",{"commitSha":282,"license":300},{"repoId":887},"kd72qvzyvm658ya7pbyh5ey47h86md53",[215,882,883,884,850],{"evaluatedAt":890,"extractAt":891,"updatedAt":890},1778689448072,1778688112811,{"_creationTime":893,"_id":894,"community":895,"display":896,"identity":902,"providers":907,"relations":915,"tags":918,"workflow":919},1778696595410.5698,"k171sdysmt658g1cdd7hgt8p8h86nms7",{"reviewCount":8},{"description":897,"installMethods":898,"name":900,"sourceUrl":901},"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":899},"rohitg00/pro-workflow","Wrap-Up Ritual","https://github.com/rohitg00/pro-workflow",{"basePath":903,"githubOwner":904,"githubRepo":905,"locale":18,"slug":906,"type":247},"skills/wrap-up","rohitg00","pro-workflow","wrap-up",{"evaluate":908,"extract":914},{"promptVersionExtension":204,"promptVersionScoring":205,"score":271,"tags":909,"targetMarket":216,"tier":280},[910,911,912,211,825,913],"workflow","llm","productivity","code-quality",{"commitSha":282,"license":300},{"parentExtensionId":916,"repoId":917},"k17fxtjcfh5gvxdrhv2dmgn1t986mdhv","kd7am4e918eq98hrd9s31jm4vs86nn0b",[913,825,911,211,912,910],{"evaluatedAt":920,"extractAt":921,"updatedAt":920},1778697164619,1778696595410,{"_creationTime":923,"_id":924,"community":925,"display":926,"identity":930,"providers":932,"relations":939,"tags":940,"workflow":941},1778696595410.5657,"k17bk9m02r7jkbzzqapbzfvq8h86m6qn",{"reviewCount":8},{"description":927,"installMethods":928,"name":929,"sourceUrl":901},"Wire Commands, Agents, and Skills together for complex features. Use when building features that need research, planning, and implementation phases.",{"claudeCode":899},"orchestrate",{"basePath":931,"githubOwner":904,"githubRepo":905,"locale":18,"slug":929,"type":247},"skills/orchestrate",{"evaluate":933,"extract":938},{"promptVersionExtension":204,"promptVersionScoring":205,"score":271,"tags":934,"targetMarket":216,"tier":280},[935,936,910,211,937],"llm-ops","agent","knowledge-management",{"commitSha":282},{"parentExtensionId":916,"repoId":917},[936,937,935,211,910],{"evaluatedAt":942,"extractAt":921,"updatedAt":942},1778696881233]