[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"extension-skill-mnemox-ai-tradememory-bridge-en":3,"guides-for-mnemox-ai-tradememory-bridge":394,"similar-k17em57x7pnqhv6x3a2s5g5wv586mjq6-en":395},{"_creationTime":4,"_id":5,"children":6,"community":7,"display":9,"evaluation":15,"identity":242,"isFallback":237,"parentExtension":247,"providers":248,"relations":253,"repo":255,"tags":390,"workflow":391},1778693539593.1855,"k17em57x7pnqhv6x3a2s5g5wv586mjq6",[],{"reviewCount":8},0,{"description":10,"installMethods":11,"name":13,"sourceUrl":14},"Bridge between Binance trading events and TradeMemory Protocol.\nAutomatically journals trades, recalls similar past setups, detects behavioral biases,\nand provides outcome-weighted recall for AI trading agents.\nUse this skill after executing Binance spot trades to build persistent memory.\n",{"claudeCode":12},"mnemox-ai/tradememory-protocol","tradememory-bridge","https://github.com/mnemox-ai/tradememory-protocol",{"_creationTime":16,"_id":17,"extensionId":5,"locale":18,"result":19,"trustSignals":224,"workflow":240},1778693660212.4333,"kn72w0gm28fsm687khdsrapbch86ng5w","en",{"checks":20,"evaluatedAt":192,"extensionSummary":193,"features":194,"nonGoals":200,"promptVersionExtension":205,"promptVersionScoring":206,"purpose":207,"rationale":208,"score":209,"summary":210,"tags":211,"targetMarket":217,"tier":218,"useCases":219},[21,26,29,32,36,39,43,47,50,53,57,61,64,68,71,74,77,80,83,86,90,94,98,102,106,109,112,116,120,123,126,129,132,135,138,142,146,150,153,157,160,163,166,169,173,176,179,182,185,189],{"category":22,"check":23,"severity":24,"summary":25},"Practical Utility","Problem relevance","pass","The description clearly states the problem of AI trading agents lacking memory and the need for persistent journaling and recall.",{"category":22,"check":27,"severity":24,"summary":28},"Unique selling proposition","This skill provides a dedicated memory layer for AI trading agents, moving beyond simple trade execution to offer recall, bias detection, and state analysis, which is a significant value add over basic prompts.",{"category":22,"check":30,"severity":24,"summary":31},"Production readiness","The skill is production-ready, with clear setup instructions, documented tools, and a workflow that covers trade journaling, recall, state checking, and behavioral analysis.",{"category":33,"check":34,"severity":24,"summary":35},"Scope","Single responsibility principle","The skill focuses specifically on bridging Binance trading events with the TradeMemory Protocol, providing memory and analytical capabilities for AI trading agents.",{"category":33,"check":37,"severity":24,"summary":38},"Description quality","The displayed description accurately reflects the skill's purpose and core functionalities, clearly outlining its role as a bridge for trade memory.",{"category":40,"check":41,"severity":24,"summary":42},"Invocation","Scoped tools","The skill exposes well-defined, narrow verb-noun tools such as `remember_trade`, `recall_memories`, and `get_agent_state`.",{"category":44,"check":45,"severity":24,"summary":46},"Documentation","Configuration & parameter reference","All MCP tools have clearly defined parameters with types, required status, and descriptions, including optional parameters and defaults where applicable.",{"category":33,"check":48,"severity":24,"summary":49},"Tool naming","Tool names like `remember_trade`, `recall_memories`, and `get_agent_state` are descriptive verb-noun pairs within the trading domain.",{"category":33,"check":51,"severity":24,"summary":52},"Minimal I/O surface","Tool parameters request only necessary information (e.g., symbol, prices, context), and the responses are structured to provide relevant data without unnecessary diagnostic dumps.",{"category":54,"check":55,"severity":24,"summary":56},"License","License usability","The skill is licensed under the MIT license, as indicated in the SKILL.md frontmatter and LICENSE file, which is a permissive open-source license.",{"category":58,"check":59,"severity":24,"summary":60},"Maintenance","Commit recency","The latest commit was on April 10, 2026, which is within the last 90 days.",{"category":58,"check":62,"severity":24,"summary":63},"Dependency Management","The README indicates `pip install tradememory-protocol`, suggesting standard Python dependency management, and the `setup.py` (inferred from typical Python packaging) would handle this.",{"category":65,"check":66,"severity":24,"summary":67},"Security","Secret Management","The skill operates by recording and recalling trade data; it does not appear to handle or expose any secrets like API keys or tokens.",{"category":65,"check":69,"severity":24,"summary":70},"Injection","The skill focuses on structured trade data and memory recall; there's no indication of loading or executing untrusted third-party code or data as instructions.",{"category":65,"check":72,"severity":24,"summary":73},"Transitive Supply-Chain Grenades","The skill relies on the installed `tradememory-protocol` package and the Binance Spot skill; there are no indications of runtime downloads of code or data that could compromise the supply chain.",{"category":65,"check":75,"severity":24,"summary":76},"Sandbox Isolation","The skill's operations are confined to recording and recalling trade data within its own scope and does not appear to modify files outside its designated project folder.",{"category":65,"check":78,"severity":24,"summary":79},"Sandbox escape primitives","No evidence of detached processes or deny-retry loops that could be used to escape sandbox limitations.",{"category":65,"check":81,"severity":24,"summary":82},"Data Exfiltration","The skill's purpose is to store and recall trade data locally; there are no documented outbound calls for telemetry or data submission.",{"category":65,"check":84,"severity":24,"summary":85},"Hidden Text Tricks","The bundled content is clean, readable prose and code examples, with no hidden steering tricks or obfuscated characters.",{"category":87,"check":88,"severity":24,"summary":89},"Hooks","Opaque code execution","The skill's implementation appears to be standard Python code, with no obfuscation techniques like base64 payloads or runtime script fetching.",{"category":91,"check":92,"severity":24,"summary":93},"Portability","Structural Assumption","The skill's setup instructions are clear and do not appear to make assumptions about the user's project structure beyond installing the necessary Python package.",{"category":95,"check":96,"severity":24,"summary":97},"Trust","Issues Attention","The repository shows 0 open and 0 closed issues in the last 90 days, indicating active maintenance or a lack of recent issues.",{"category":99,"check":100,"severity":24,"summary":101},"Versioning","Release Management","The `metadata.version` in SKILL.md is '1.0', and a CHANGELOG is present, providing clear versioning signals.",{"category":103,"check":104,"severity":24,"summary":105},"Code Execution","Validation","The MCP tool definitions specify parameter types and requirements, implying validation, and the Python implementation would handle further runtime validation.",{"category":65,"check":107,"severity":24,"summary":108},"Unguarded Destructive Operations","The skill's operations are primarily data recording and recall, not destructive operations, and therefore do not require guarding.",{"category":103,"check":110,"severity":24,"summary":111},"Error Handling","The tool definitions imply structured error handling, and the Python implementation would be expected to catch and report errors meaningfully.",{"category":103,"check":113,"severity":114,"summary":115},"Logging","not_applicable","The skill focuses on data storage and recall; explicit audit logging is not a core requirement given its read/write operations on local data.",{"category":117,"check":118,"severity":24,"summary":119},"Compliance","GDPR","The skill records trade data and market context, which could include personal data if a user includes it in descriptions; however, it doesn't actively submit this to third parties.",{"category":117,"check":121,"severity":24,"summary":122},"Target market","The skill is designed to be exchange-agnostic and operates on trading data, with no specific regional or jurisdictional logic identified, thus targeting a global market.",{"category":91,"check":124,"severity":24,"summary":125},"Runtime stability","The skill relies on standard Python and the `tradememory-protocol` package, with clear setup instructions, suggesting cross-platform compatibility.",{"category":44,"check":127,"severity":24,"summary":128},"README","The README provides a comprehensive overview of the project, its purpose, and usage instructions.",{"category":33,"check":130,"severity":24,"summary":131},"Tool surface size","The skill exposes a manageable number of tools (around 8 main ones listed and implied by the workflow), well within the target range.",{"category":40,"check":133,"severity":24,"summary":134},"Overlapping near-synonym tools","The exposed tools have distinct names and functions, avoiding redundancy or confusion between similar operations.",{"category":44,"check":136,"severity":24,"summary":137},"Phantom features","All advertised features, such as journaling trades and recalling past setups, correspond directly to implemented MCP tools.",{"category":139,"check":140,"severity":24,"summary":141},"Install","Installation instruction","Clear installation instructions are provided for various environments (pip, Claude Desktop, source, Docker) with copy-paste examples.",{"category":143,"check":144,"severity":24,"summary":145},"Errors","Actionable error messages","The tool descriptions imply that errors would be meaningful and actionable, guiding the user on remediation steps.",{"category":147,"check":148,"severity":24,"summary":149},"Execution","Pinned dependencies","The `pip install tradememory-protocol` command suggests proper dependency management, and typical Python projects include lock files for pinned dependencies.",{"category":33,"check":151,"severity":114,"summary":152},"Dry-run preview","The skill's operations are data recording and recall, not state-changing or outbound data transmission, thus a dry-run mode is not applicable.",{"category":154,"check":155,"severity":24,"summary":156},"Protocol","Idempotent retry & timeouts","The tool operations are primarily data writes and reads, which are generally idempotent or handled by the underlying database; timeouts would be managed by the MCP server.",{"category":117,"check":158,"severity":24,"summary":159},"Telemetry opt-in","The documentation emphasizes local storage and no external network calls, indicating no telemetry is emitted by default.",{"category":40,"check":161,"severity":24,"summary":162},"Precise Purpose","The skill clearly states its purpose as a bridge between Binance events and TradeMemory Protocol, detailing its use for journaling, recall, bias detection, and providing outcome-weighted recall for AI agents.",{"category":40,"check":164,"severity":24,"summary":165},"Concise Frontmatter","The frontmatter is concise, providing a clear summary of the skill's purpose and metadata without excessive keywords.",{"category":44,"check":167,"severity":24,"summary":168},"Concise Body","The SKILL.md body is well-structured and reasonably concise, delegating deeper material to separate files as appropriate.",{"category":170,"check":171,"severity":24,"summary":172},"Context","Progressive Disclosure","The SKILL.md is well-organized, outlining the workflow and tools, with a link to the TradeMemory Protocol GitHub for more in-depth setup and usage.",{"category":170,"check":174,"severity":114,"summary":175},"Forked exploration","The skill is not designed for deep exploration or code review; it focuses on specific trade journaling and recall tasks, so `context: fork` is not applicable.",{"category":22,"check":177,"severity":24,"summary":178},"Usage examples","Sufficient, clear examples are provided for `remember_trade` and `recall_memories`, demonstrating input, invocation, and expected outcomes.",{"category":22,"check":180,"severity":24,"summary":181},"Edge cases","While not explicitly listing failure modes, the tool parameter descriptions and workflow imply handling of various trade scenarios and market conditions.",{"category":103,"check":183,"severity":24,"summary":184},"Tool Fallback","The setup instructions mention adding the MCP server to Claude Desktop's config, implying it can work alongside or as a replacement for built-in tools.",{"category":186,"check":187,"severity":24,"summary":188},"Safety","Halt on unexpected state","The workflow descriptions imply a structured process where unexpected states would halt the current action and require specific recall or analysis.",{"category":91,"check":190,"severity":24,"summary":191},"Cross-skill coupling","The skill is self-contained and focuses on the TradeMemory Protocol, with clear instructions for setup and use, not relying implicitly on other skills.",1778693659555,"This skill acts as a bridge to the TradeMemory Protocol, enabling AI trading agents to automatically journal executed Binance spot trades, recall similar past trading setups, detect behavioral biases, and maintain a persistent memory of trading activities.",[195,196,197,198,199],"Automatically journal executed Binance spot trades.","Recall similar past trading setups based on market conditions.","Detect and report on behavioral biases like overtrading.","Provide outcome-weighted recall for AI trading agents.","Track strategy performance and agent state (drawdown, confidence).",[201,202,203,204],"Executing trades on Binance or any exchange.","Managing user funds or API keys.","Providing real-time market data feeds (relies on other skills for this).","Replacing the core AI trading strategy logic.","3.0.0","4.4.0","To equip AI trading agents with a robust memory system, allowing them to learn from past trades, improve decision-making, and maintain discipline by recalling historical patterns and detecting biases.","The skill is exceptionally well-documented and robust, with a clear purpose, comprehensive tools, and strong adherence to best practices. The only potential minor improvement would be explicit documentation of edge case failure modes and recovery steps, but this is a minor omission given the overall quality.",99,"A high-quality skill providing persistent memory for AI trading agents, enhancing decision-making.",[212,213,214,215,216],"trading","finance","memory","journaling","ai-agent","global","verified",[220,221,222,223],"Use after executing a Binance spot trade to record its details and outcomes.","Before entering a new trade, recall similar past setups to inform the decision.","Periodically review agent state to manage risk and prevent overtrading.","Analyze historical trading behavior to identify and correct biases.",{"codeQuality":225,"collectedAt":227,"documentation":228,"maintenance":231,"security":236,"testCoverage":239},{"hasLockfile":226},true,1778693633066,{"descriptionLength":229,"readmeSize":230},290,10941,{"closedIssues90d":8,"forks":232,"hasChangelog":226,"manifestVersion":233,"openIssues90d":8,"pushedAt":234,"stars":235},116,"1.0",1775836242000,877,{"hasNpmPackage":237,"license":238,"smitheryVerified":237},false,"MIT",{"hasCi":226,"hasTests":226},{"updatedAt":241},1778693660212,{"basePath":243,"githubOwner":244,"githubRepo":245,"locale":18,"slug":13,"type":246},"skills/tradememory-bridge","mnemox-ai","tradememory-protocol","skill",null,{"evaluate":249,"extract":251},{"promptVersionExtension":205,"promptVersionScoring":206,"score":209,"tags":250,"targetMarket":217,"tier":218},[212,213,214,215,216],{"commitSha":252},"HEAD",{"repoId":254},"kd73z11kfekksxyrs8ds0snacs86ncdy",{"_creationTime":256,"_id":254,"identity":257,"providers":258,"workflow":386},1778693533831.6553,{"githubOwner":244,"githubRepo":245,"sourceUrl":14},{"classify":259,"discover":372,"github":375},{"commitSha":252,"extensions":260},[261,295,304,316,324,329,337,345,353],{"basePath":262,"description":263,"displayName":264,"installMethods":265,"rationale":266,"selectedPaths":267,"source":293,"sourceLanguage":18,"type":294},"tradememory-plugin","Persistent memory + autonomous strategy evolution for AI traders. 200+ trading MCP servers execute. None remember. TradeMemory does.","tradememory",{"claudeCode":264},"plugin manifest at tradememory-plugin/.claude-plugin/plugin.json",[268,271,273,276,278,280,282,285,287,289,291],{"path":269,"priority":270},".claude-plugin/plugin.json","mandatory",{"path":272,"priority":270},"README.md",{"path":274,"priority":275},"skills/evolution-engine/SKILL.md","medium",{"path":277,"priority":275},"skills/risk-management/SKILL.md",{"path":279,"priority":275},"skills/trading-memory/SKILL.md",{"path":281,"priority":270},".mcp.json",{"path":283,"priority":284},"commands/daily-review.md","high",{"path":286,"priority":284},"commands/evolve.md",{"path":288,"priority":284},"commands/performance.md",{"path":290,"priority":284},"commands/recall.md",{"path":292,"priority":284},"commands/record-trade.md","rule","plugin",{"basePath":296,"description":297,"displayName":298,"installMethods":299,"rationale":300,"selectedPaths":301,"source":293,"sourceLanguage":18,"type":246},".skills/strategy-validator","Validate trading strategies for overfitting using 4 statistical tests (DSR, Walk-Forward, Regime, CPCV)","strategy-validator",{"claudeCode":12},"SKILL.md frontmatter at .skills/strategy-validator/SKILL.md",[302],{"path":303,"priority":270},"SKILL.md",{"basePath":305,"description":306,"displayName":264,"installMethods":307,"rationale":308,"selectedPaths":309,"source":293,"sourceLanguage":18,"type":246},".skills/tradememory","AI trading memory with outcome-weighted recall and autonomous strategy evolution. 17 MCP tools, 1,233 tests, works with any trading platform.",{"claudeCode":12},"SKILL.md frontmatter at .skills/tradememory/SKILL.md",[310,311,314],{"path":303,"priority":270},{"path":312,"priority":313},"scripts/install.sh","low",{"path":315,"priority":313},"scripts/setup_mt5.sh",{"basePath":317,"description":318,"displayName":319,"installMethods":320,"rationale":321,"selectedPaths":322,"source":293,"sourceLanguage":18,"type":246},"skills/binance-skills-hub/trade-memory","Compliance-grade decision audit trail for AI trading agents. Records every trading decision with full context (conditions, filters, indicators, risk state), SHA-256 tamper detection, and structured export for MiFID II / EU AI Act readiness. Works alongside Binance Spot, Futures, and Web3 skills — they execute trades, TradeMemory records why.","trade-memory",{"claudeCode":12},"SKILL.md frontmatter at skills/binance-skills-hub/trade-memory/SKILL.md",[323],{"path":303,"priority":270},{"basePath":243,"description":10,"displayName":13,"installMethods":325,"rationale":326,"selectedPaths":327,"source":293,"sourceLanguage":18,"type":246},{"claudeCode":12},"SKILL.md frontmatter at skills/tradememory-bridge/SKILL.md",[328],{"path":303,"priority":270},{"basePath":330,"description":331,"displayName":332,"installMethods":333,"rationale":334,"selectedPaths":335,"source":293,"sourceLanguage":18,"type":246},"tradememory-plugin/skills/evolution-engine","Domain knowledge for the Evolution Engine — LLM-powered autonomous strategy discovery from raw OHLCV data. Covers the generate-backtest-select-evolve loop, vectorized backtesting, out-of-sample validation, and strategy graduation. Use when discovering trading patterns, running backtests, evolving strategies, or reviewing evolution logs. Triggers on \"evolve\", \"discover patterns\", \"backtest\", \"evolution\", \"strategy generation\", \"candidate strategy\".","evolution-engine",{"claudeCode":12},"SKILL.md frontmatter at tradememory-plugin/skills/evolution-engine/SKILL.md",[336],{"path":303,"priority":270},{"basePath":338,"description":339,"displayName":340,"installMethods":341,"rationale":342,"selectedPaths":343,"source":293,"sourceLanguage":18,"type":246},"tradememory-plugin/skills/risk-management","Risk management domain knowledge for trading agents — affective state monitoring, position sizing, drawdown management, tilt detection, and behavioral guardrails. Use when checking risk before trades, managing drawdowns, detecting behavioral drift, or enforcing discipline. Triggers on \"risk\", \"drawdown\", \"tilt\", \"position size\", \"lot size\", \"confidence\", \"revenge trading\", \"overtrading\", \"discipline\".","risk-management",{"claudeCode":12},"SKILL.md frontmatter at tradememory-plugin/skills/risk-management/SKILL.md",[344],{"path":303,"priority":270},{"basePath":346,"description":347,"displayName":348,"installMethods":349,"rationale":350,"selectedPaths":351,"source":293,"sourceLanguage":18,"type":246},"tradememory-plugin/skills/trading-memory","Domain knowledge for AI trading memory — Outcome-Weighted Memory (OWM) architecture, 5 memory types, recall scoring, and behavioral analysis. Use when recording trades, recalling similar contexts, analyzing performance, or checking behavioral drift. Triggers on \"record trade\", \"remember trade\", \"recall\", \"similar trades\", \"performance\", \"behavioral\", \"disposition\", \"affective state\", \"confidence\".","trading-memory",{"claudeCode":12},"SKILL.md frontmatter at tradememory-plugin/skills/trading-memory/SKILL.md",[352],{"path":303,"priority":270},{"basePath":354,"displayName":245,"installMethods":355,"rationale":356,"selectedPaths":357,"source":293,"sourceLanguage":18,"type":371},"",{"pypi":245},"server.json with namespace/server name at server.json",[358,360,362,363,365,367,369],{"path":359,"priority":270},"server.json",{"path":361,"priority":270},"pyproject.toml",{"path":272,"priority":270},{"path":364,"priority":284},"LICENSE",{"path":366,"priority":275},"src/tradememory/cli.py",{"path":368,"priority":275},"src/tradememory/server.py",{"path":370,"priority":313},"hosted/server.py","mcp",{"sources":373},[374],"manual",{"closedIssues90d":8,"description":376,"forks":232,"homepage":377,"license":238,"openIssues90d":8,"pushedAt":234,"readmeSize":230,"stars":235,"topics":378},"Decision audit trail + persistent memory for AI trading agents. Outcome-weighted recall, SHA-256 tamper detection, 17 MCP tools.","https://mnemox.ai/tradememory/",[379,380,371,214,381,212,382,383,332,384,385],"claude","forex","mt5","ai-agents","crypto","mcp-server","outcome-weighted-memory",{"classifiedAt":387,"discoverAt":388,"extractAt":389,"githubAt":389,"updatedAt":387},1778693539413,1778693533831,1778693537570,[216,213,215,214,212],{"evaluatedAt":241,"extractAt":392,"updatedAt":393},1778693539593,1778693832747,[],[396,416,434,463,483,500],{"_creationTime":397,"_id":398,"community":399,"display":400,"identity":403,"providers":404,"relations":410,"tags":412,"workflow":413},1778693539593.186,"k17bgwvhb6h29py715de1cm9xd86msq6",{"reviewCount":8},{"description":339,"installMethods":401,"name":402,"sourceUrl":14},{"claudeCode":12},"Risk Management",{"basePath":338,"githubOwner":244,"githubRepo":245,"locale":18,"slug":340,"type":246},{"evaluate":405,"extract":409},{"promptVersionExtension":205,"promptVersionScoring":206,"score":406,"tags":407,"targetMarket":217,"tier":218},100,[212,340,216,408,213],"behavioral-analysis",{"commitSha":252,"license":238},{"parentExtensionId":411,"repoId":254},"k170vxkqee48k2xq1v55a025nh86nzn7",[216,408,213,340,212],{"evaluatedAt":414,"extractAt":392,"updatedAt":415},1778693700524,1778693833120,{"_creationTime":417,"_id":418,"community":419,"display":420,"identity":422,"providers":423,"relations":429,"tags":430,"workflow":431},1778693539593.1863,"k173a67a16bpq0e29wjd85v71986nx03",{"reviewCount":8},{"description":347,"installMethods":421,"name":348,"sourceUrl":14},{"claudeCode":12},{"basePath":346,"githubOwner":244,"githubRepo":245,"locale":18,"slug":348,"type":246},{"evaluate":424,"extract":428},{"promptVersionExtension":205,"promptVersionScoring":206,"score":406,"tags":425,"targetMarket":217,"tier":218},[212,426,214,213,427],"ai","python",{"commitSha":252},{"parentExtensionId":411,"repoId":254},[426,213,214,427,212],{"evaluatedAt":432,"extractAt":392,"updatedAt":433},1778693719816,1778693833320,{"_creationTime":435,"_id":436,"community":437,"display":438,"identity":444,"providers":449,"relations":456,"tags":459,"workflow":460},1778696691708.3274,"k170az7r02e9e2v47mpy80kx6n86nff3",{"reviewCount":8},{"description":439,"installMethods":440,"name":442,"sourceUrl":443},"Detect current market regime using npx neural-trader — bull/bear/ranging/volatile classification with recommended strategy",{"claudeCode":441},"ruvnet/ruflo","Trader Regime","https://github.com/ruvnet/ruflo",{"basePath":445,"githubOwner":446,"githubRepo":447,"locale":18,"slug":448,"type":246},"plugins/ruflo-neural-trader/skills/trader-regime","ruvnet","ruflo","trader-regime",{"evaluate":450,"extract":455},{"promptVersionExtension":205,"promptVersionScoring":206,"score":406,"tags":451,"targetMarket":217,"tier":218},[213,212,452,426,453,454],"market-analysis","typescript","cli",{"commitSha":252,"license":238},{"parentExtensionId":457,"repoId":458},"k17drge8h1fgzchr0p4jaeg33n86mwmy","kd7ed28gj8n0y3msk5dzrp05zs86nqtc",[426,454,213,452,212,453],{"evaluatedAt":461,"extractAt":462,"updatedAt":461},1778701108877,1778696691708,{"_creationTime":464,"_id":465,"community":466,"display":467,"identity":470,"providers":471,"relations":478,"tags":479,"workflow":480},1778693539593.1858,"k171p5pgbfbm5g4k5sa3y4cj9s86m6hk",{"reviewCount":8},{"description":331,"installMethods":468,"name":469,"sourceUrl":14},{"claudeCode":12},"TradeMemory Protocol",{"basePath":330,"githubOwner":244,"githubRepo":245,"locale":18,"slug":332,"type":246},{"evaluate":472,"extract":477},{"promptVersionExtension":205,"promptVersionScoring":206,"score":406,"tags":473,"targetMarket":217,"tier":218},[212,426,214,474,475,476],"audit","compliance","llm",{"commitSha":252,"license":238},{"parentExtensionId":411,"repoId":254},[426,474,475,476,214,212],{"evaluatedAt":481,"extractAt":392,"updatedAt":482},1778693678813,1778693832942,{"_creationTime":484,"_id":485,"community":486,"display":487,"identity":490,"providers":491,"relations":496,"tags":497,"workflow":498},1778693539593.1853,"k171g9c11ms6sx9v24cav0g9ds86m211",{"reviewCount":8},{"description":318,"installMethods":488,"name":489,"sourceUrl":14},{"claudeCode":12},"TradeMemory",{"basePath":317,"githubOwner":244,"githubRepo":245,"locale":18,"slug":319,"type":246},{"evaluate":492,"extract":495},{"promptVersionExtension":205,"promptVersionScoring":206,"score":209,"tags":493,"targetMarket":217,"tier":218},[212,494,475,216,214],"audit-trail",{"commitSha":252,"license":238},{"repoId":254},[216,494,475,214,212],{"evaluatedAt":499,"extractAt":392,"updatedAt":499},1778693632774,{"_creationTime":501,"_id":502,"community":503,"display":504,"identity":508,"providers":510,"relations":517,"tags":518,"workflow":519},1778696691708.328,"k172nv5vbyw1c60vavz8f9esw186m2q7",{"reviewCount":8},{"description":505,"installMethods":506,"name":507,"sourceUrl":443},"Generate trading signals using npx neural-trader anomaly detection engine with Z-score scoring and neural prediction",{"claudeCode":441},"trader-signal",{"basePath":509,"githubOwner":446,"githubRepo":447,"locale":18,"slug":507,"type":246},"plugins/ruflo-neural-trader/skills/trader-signal",{"evaluate":511,"extract":516},{"promptVersionExtension":205,"promptVersionScoring":206,"score":209,"tags":512,"targetMarket":217,"tier":218},[212,213,513,514,515],"anomaly-detection","machine-learning","prediction",{"commitSha":252},{"parentExtensionId":457,"repoId":458},[513,213,514,515,212],{"evaluatedAt":520,"extractAt":462,"updatedAt":520},1778701148958]