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no outbound calls for data submission were detected.",{"category":66,"check":85,"severity":24,"summary":86},"Hidden Text Tricks","The bundled content appears free of hidden-steering tricks, using clean printable ASCII and expected Unicode.",{"category":88,"check":89,"severity":24,"summary":90},"Hooks","Opaque code execution","The Python backend scripts are readable and not obfuscated or dynamically fetched.",{"category":92,"check":93,"severity":24,"summary":94},"Portability","Structural Assumption","The skill assumes a CSV input and output directory, which are clearly defined, rather than project-specific file layouts.",{"category":96,"check":97,"severity":24,"summary":98},"Trust","Issues Attention","There are 0 open and 0 closed issues in the last 90 days, indicating a low issue rate and potential lack of recent activity.",{"category":100,"check":101,"severity":24,"summary":102},"Versioning","Release Management","A meaningful semver version (0.1.0) is declared in the SKILL.md frontmatter and README, and a CHANGELOG exists.",{"category":104,"check":105,"severity":24,"summary":106},"Code Execution","Validation","The Python backend likely uses schema validation for CSV parsing and JSON output, as implied by its structured data handling.",{"category":66,"check":108,"severity":24,"summary":109},"Unguarded Destructive Operations","The skill is read-only with respect to user data, only generating output files, thus no destructive operations are guarded.",{"category":104,"check":111,"severity":24,"summary":112},"Error Handling","The SKILL.md outlines clear data quality checks and mentions handling incomplete data, suggesting robust error reporting.",{"category":104,"check":114,"severity":42,"summary":115},"Logging","The skill is analytical and read-only, thus not requiring a local audit log for destructive actions or outbound calls.",{"category":117,"check":118,"severity":24,"summary":119},"Compliance","GDPR","The skill operates on order transaction data, which may contain personal data, but processes it locally without submitting to third parties.",{"category":117,"check":121,"severity":24,"summary":122},"Target market","The skill is language-agnostic and processes generic e-commerce data, making it globally applicable.",{"category":92,"check":124,"severity":24,"summary":125},"Runtime stability","The skill declares Python 3.10+ as a requirement and runs via a standard CLI command, ensuring broad compatibility.",{"category":45,"check":127,"severity":24,"summary":128},"README","The README is comprehensive, clearly states the extension's purpose, and includes installation and usage examples.",{"category":33,"check":130,"severity":42,"summary":131},"Tool surface size","This is a single-command skill, not a multi-tool extension.",{"category":40,"check":133,"severity":42,"summary":134},"Overlapping near-synonym tools","The skill has a single primary command ('review') with optional period arguments, thus no overlapping tools.",{"category":45,"check":136,"severity":24,"summary":137},"Phantom features","All advertised features, such as KPI trees and action plans, are directly implemented and described in the SKILL.md.",{"category":139,"check":140,"severity":24,"summary":141},"Install","Installation instruction","Clear installation instructions via curl script or plugin manager are provided, along with copy-pasteable invocation examples.",{"category":143,"check":144,"severity":24,"summary":145},"Errors","Actionable error messages","SKILL.md details data quality warnings and handling of incomplete data, implying actionable error reporting for users.",{"category":147,"check":148,"severity":24,"summary":149},"Execution","Pinned dependencies","Python 3.10+ is declared, and the use of a virtual environment implies pinned dependencies for the backend.",{"category":33,"check":151,"severity":42,"summary":152},"Dry-run preview","The skill is analytical and read-only, producing reports from data, so a dry-run mode is not applicable.",{"category":154,"check":155,"severity":42,"summary":156},"Protocol","Idempotent retry & timeouts","The skill operates locally on provided data and does not involve remote calls or state-changing operations requiring idempotency.",{"category":117,"check":158,"severity":24,"summary":159},"Telemetry opt-in","No telemetry or outbound communication beyond data processing is indicated; thus, opt-in is implicitly met.",{"category":40,"check":161,"severity":24,"summary":162},"Precise Purpose","The purpose is precise: analyze D2C ecommerce order data to generate business reviews, with clear triggers and data inputs.",{"category":40,"check":164,"severity":24,"summary":165},"Concise Frontmatter","The frontmatter is concise and self-contained, summarizing the core capability and listing trigger phrases.",{"category":45,"check":167,"severity":24,"summary":168},"Concise Body","SKILL.md is well-structured with clear sections and delegates detailed information to referenced files, staying under token limits.",{"category":170,"check":171,"severity":24,"summary":172},"Context","Progressive Disclosure","Detailed information like benchmarks, finding clusters, and impact formulas are in separate reference files, linked via relative paths.",{"category":170,"check":174,"severity":42,"summary":175},"Forked exploration","The skill is not an exploration-heavy tool; it processes data and generates a report, not requiring a forked context.",{"category":22,"check":177,"severity":24,"summary":178},"Usage examples","SKILL.md and README provide clear command-line invocation examples and link to a full example output report.",{"category":22,"check":180,"severity":24,"summary":181},"Edge cases","SKILL.md addresses incomplete data scenarios, partial month data, and lack of 365d coverage, with guidance on how to proceed.",{"category":104,"check":183,"severity":24,"summary":184},"Halt on unexpected state","SKILL.md emphasizes data quality checks and handling of incomplete data, implying the workflow halts or reports clearly on unexpected states.",{"category":92,"check":186,"severity":24,"summary":187},"Cross-skill coupling","The skill is self-contained and does not appear to rely on other specific skills being loaded in the same session.",1778697984371,"This skill processes D2C ecommerce order transaction data (CSV) to generate detailed business reviews. 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All checks passed, with only 'not_applicable' findings reflecting the skill's focused nature.",98,"A high-quality skill for analyzing D2C ecommerce data and generating comprehensive business reviews.",[207,208,209,210,211],"ecommerce","analytics","reporting","d2c","business-review","global","verified",[215,216,217,218],"Generating monthly or quarterly business performance reviews.","Identifying key drivers of revenue growth or decline.","Diagnosing issues with customer retention or acquisition.","Getting actionable recommendations to improve store 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ARIMA and Holt-Winters predictions with confidence intervals. Predict revenue, traffic, prices, or any sequential data. Sub-5ms inference.",{"claudeCode":384},"Whatsonyourmind/oraclaw","OraClaw Forecast","https://github.com/Whatsonyourmind/oraclaw",{"basePath":388,"githubOwner":389,"githubRepo":390,"locale":18,"slug":391,"type":241},"mission-control/packages/clawhub-skills/oraclaw-forecast","Whatsonyourmind","oraclaw","oraclaw-forecast",{"evaluate":393,"extract":402},{"promptVersionExtension":200,"promptVersionScoring":201,"score":394,"tags":395,"targetMarket":212,"tier":213},100,[396,397,398,399,400,208,401],"forecasting","time-series","prediction","arima","holt-winters","data-science",{"commitSha":271,"license":233},{"repoId":404},"kd76fmxm1ng903s4fmj0p7hxxs86ndkg",[208,399,401,396,400,398,397],{"evaluatedAt":407,"extractAt":408,"updatedAt":409},1778698975269,1778698837670,1778699187952,{"_creationTime":411,"_id":412,"community":413,"display":414,"identity":420,"providers":424,"relations":432,"tags":435,"workflow":436},1778695720086.77,"k17dem9k6ck7j5dvtc629g0cdh86np6g",{"reviewCount":8},{"description":415,"installMethods":416,"name":418,"sourceUrl":419},"Specifies requirements for an analytics dashboard including metrics, visualizations, filters, and data sources. 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Also use when the user mentions \"chart movers\", \"rank changes\", \"who's rising\", \"who's falling\", \"new chart entries\", \"top gainers\", or \"market shifts\". For broader market overview, see market-pulse. For competitive keyword analysis, see competitor-analysis.",{"claudeCode":474},"Eronred/aso-skills","market-movers","https://github.com/Eronred/aso-skills",{"basePath":478,"githubOwner":479,"githubRepo":480,"locale":18,"slug":475,"type":241},"skills/market-movers","Eronred","aso-skills",{"evaluate":482,"extract":488},{"promptVersionExtension":200,"promptVersionScoring":201,"score":394,"tags":483,"targetMarket":212,"tier":213},[484,485,486,208,487],"app-store","aso","market-intelligence","mobile-marketing",{"commitSha":271},{"parentExtensionId":490,"repoId":491},"k1727n4vhgt43pj3y260sxsq3x86m9ew","kd7cmwz9bgzp6ww0emxg8jfez186n7c2",[208,484,485,486,487],{"evaluatedAt":494,"extractAt":495,"updatedAt":494},1778687205370,1778686547483,{"_creationTime":497,"_id":498,"community":499,"display":500,"identity":506,"providers":511,"relations":519,"tags":522,"workflow":523},1778686037155.62,"k171b0gmdtned9xfwa62tb031d86mx06",{"reviewCount":8},{"description":501,"installMethods":502,"name":504,"sourceUrl":505},"Evaluate acquisition channels using unit economics, customer quality, and scalability. Use when deciding whether to scale, test, or kill a growth channel.",{"claudeCode":503},"deanpeters/Product-Manager-Skills","Acquisition Channel Advisor","https://github.com/deanpeters/Product-Manager-Skills",{"basePath":507,"githubOwner":508,"githubRepo":509,"locale":18,"slug":510,"type":241},"skills/acquisition-channel-advisor","deanpeters","Product-Manager-Skills","acquisition-channel-advisor",{"evaluate":512,"extract":517},{"promptVersionExtension":200,"promptVersionScoring":201,"score":394,"tags":513,"targetMarket":212,"tier":213},[429,514,366,208,515,516],"acquisition","decision-making","unit-economics",{"commitSha":271,"license":518},"NOASSERTION",{"parentExtensionId":520,"repoId":521},"k17fvvtse56j7y3zaag454yw5986m2q1","kd79w54je3w4zrhk2stxg9246186nbp1",[514,208,515,366,429,516],{"evaluatedAt":524,"extractAt":525,"updatedAt":524},1778687204952,1778686037155,{"_creationTime":527,"_id":528,"community":529,"display":530,"identity":536,"providers":541,"relations":550,"tags":553,"workflow":554},1778675056600.2642,"k17aczx5qdprvyyqzzhkg5epys86nv76",{"reviewCount":8},{"description":531,"installMethods":532,"name":534,"sourceUrl":535},"Social media campaign analysis and performance tracking. Calculates engagement rates, ROI, and benchmarks across platforms. Use for analyzing social media performance, calculating engagement rate, measuring campaign ROI, comparing platform metrics, or benchmarking against industry standards.",{"claudeCode":533},"alirezarezvani/claude-skills","Social Media Analyzer","https://github.com/alirezarezvani/claude-skills",{"basePath":537,"githubOwner":538,"githubRepo":539,"locale":18,"slug":540,"type":241},"marketing-skill/skills/social-media-analyzer","alirezarezvani","claude-skills","social-media-analyzer",{"evaluate":542,"extract":549},{"promptVersionExtension":200,"promptVersionScoring":201,"score":394,"tags":543,"targetMarket":212,"tier":213},[544,366,208,545,546,547,548],"social-media","performance-tracking","roi","engagement-metrics","benchmarking",{"commitSha":271,"license":233},{"parentExtensionId":551,"repoId":552},"k170sws65f0ebecn36z3q8c2z186m477","kd7ff9s1w43mfyy1n7hf87816186m6px",[208,548,547,366,545,546,544],{"evaluatedAt":555,"extractAt":556,"updatedAt":555},1778685204538,1778675056600]