[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"extension-skill-cognyai-ga4-bigquery-schema-de":3,"guides-for-cognyai-ga4-bigquery-schema":611,"similar-k174xzbyeyeah16k5f7c5zzsvn86m2x1-de":612},{"_creationTime":4,"_id":5,"children":6,"community":7,"display":9,"evaluation":15,"identity":240,"isFallback":245,"parentExtension":246,"providers":247,"relations":252,"repo":254,"tags":608,"workflow":609},1778684091954.6707,"k174xzbyeyeah16k5f7c5zzsvn86m2x1",[],{"reviewCount":8},0,{"description":10,"installMethods":11,"name":13,"sourceUrl":14},"GA4 BigQuery Export Schema Reference — complete field reference, nested structures, query patterns, and performance 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performance tips.",{"category":22,"check":27,"severity":24,"summary":28},"Unique selling proposition","The skill offers a specific reference and query patterns for GA4 BigQuery data, which goes beyond generic LLM capabilities by providing structured, expert knowledge.",{"category":22,"check":30,"severity":24,"summary":31},"Production readiness","The skill provides a comprehensive reference and query examples that are directly usable for understanding and querying GA4 BigQuery data, covering the complete lifecycle of data analysis.",{"category":33,"check":34,"severity":24,"summary":35},"Scope","Single responsibility principle","The skill has a clear, single responsibility: to act as a reference for the GA4 BigQuery export schema and related queries.",{"category":33,"check":37,"severity":24,"summary":38},"Description quality","The displayed description accurately reflects the skill's content, providing a concise and informative overview of its capabilities.",{"category":40,"check":41,"severity":42,"summary":43},"Invocation","Scoped tools","not_applicable","This skill primarily uses WebSearch and Read tools, which are general but its core functionality is reference-based, not dependent on specific scoped tools.",{"category":45,"check":46,"severity":24,"summary":47},"Documentation","Configuration & parameter reference","The SKILL.md clearly documents the `argument-hint` and allowed tools, with no implicit parameters or complex configuration.",{"category":33,"check":49,"severity":24,"summary":50},"Tool naming","The skill does not expose explicit tools but uses arguments like 'event_params' and 'conversion funnel' which are descriptive and relevant.",{"category":33,"check":52,"severity":24,"summary":53},"Minimal I/O surface","The skill accepts a simple query or topic as input and returns structured information or SQL queries as output, with no unnecessary fields.",{"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 last commit was on May 7, 2026, which is recent.",{"category":59,"check":63,"severity":42,"summary":64},"Dependency Management","The skill does not appear to use any third-party dependencies.",{"category":66,"check":67,"severity":42,"summary":68},"Security","Secret Management","The skill does not handle any secrets.",{"category":66,"check":70,"severity":24,"summary":71},"Injection","The skill relies on WebSearch and Read tools, and the provided SQL examples are parameterized or constructed safely, mitigating injection risks.",{"category":66,"check":73,"severity":24,"summary":74},"Transitive Supply-Chain Grenades","The skill only uses allowed tools (WebSearch, Read, Write, Bash) and does not fetch external content at runtime.",{"category":66,"check":76,"severity":24,"summary":77},"Sandbox Isolation","The skill operates within defined tool scopes and does not attempt to modify files outside of its intended domain.",{"category":66,"check":79,"severity":24,"summary":80},"Sandbox escape primitives","No detached-process spawns or deny-retry loops were detected in the provided scripts or instructions.",{"category":66,"check":82,"severity":24,"summary":83},"Data Exfiltration","The skill does not access or submit confidential data; outbound calls are limited to documented tools and do not seem to exfiltrate user data.",{"category":66,"check":85,"severity":24,"summary":86},"Hidden Text Tricks","The bundled content appears to be free of hidden-steering tricks, with clean ASCII and expected Unicode characters.",{"category":88,"check":89,"severity":24,"summary":90},"Hooks","Opaque code execution","The skill does not employ obfuscation techniques like base64 encoding or eval, and all scripts are readable.",{"category":92,"check":93,"severity":24,"summary":94},"Portability","Structural Assumption","The skill makes no assumptions about the user's project structure, relying on general BigQuery interactions and command-line arguments.",{"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 either a new or very stable project.",{"category":100,"check":101,"severity":24,"summary":102},"Versioning","Release Management","A meaningful version (1.0.0) is declared in the SKILL.md frontmatter.",{"category":104,"check":105,"severity":24,"summary":106},"Code Execution","Validation","The SQL examples are well-formed and parameterized where necessary, and the skill logic handles input by directing to specific sections, implying validation.",{"category":66,"check":108,"severity":24,"summary":109},"Unguarded Destructive Operations","The skill is read-only and does not perform any destructive operations.",{"category":104,"check":111,"severity":24,"summary":112},"Error Handling","The skill's instructions guide the user to specific sections, and the SQL examples are standard BigQuery queries. Any errors would likely stem from BigQuery itself or incorrect user input, which the user can then address with BigQuery or by refining their prompt.",{"category":104,"check":114,"severity":42,"summary":115},"Logging","The skill is read-only and does not perform destructive actions or outbound calls that require local audit logging.",{"category":117,"check":118,"severity":42,"summary":119},"Compliance","GDPR","The skill operates on GA4 BigQuery schema data, which does not inherently contain personal data unless user-provided identifiers are used in queries, which is not directly facilitated by the skill itself.",{"category":117,"check":121,"severity":24,"summary":122},"Target market","The skill is a general reference for Google Analytics 4 data and BigQuery, with no regional or jurisdictional limitations.",{"category":92,"check":124,"severity":24,"summary":125},"Runtime stability","The skill relies on standard BigQuery interactions and WebSearch, making it broadly compatible across different environments.",{"category":45,"check":127,"severity":24,"summary":128},"README","The README provides a good overview of the skill's capabilities, installation, and categorization, complementing the SKILL.md.",{"category":33,"check":130,"severity":42,"summary":131},"Tool surface size","This is a single-tool extension that takes a query or topic as input.",{"category":40,"check":133,"severity":42,"summary":134},"Overlapping near-synonym tools","This is a single-tool extension with no overlapping synonym tools.",{"category":45,"check":136,"severity":24,"summary":137},"Phantom features","All features mentioned in the README and SKILL.md, such as schema reference and query patterns, are implemented and demonstrable.",{"category":139,"check":140,"severity":24,"summary":141},"Install","Installation instruction","The README provides clear installation instructions, including both a curl command and manual copy-paste options, along with usage examples.",{"category":143,"check":144,"severity":24,"summary":145},"Errors","Actionable error messages","While direct error messages from the skill itself are minimal, it guides users to specific sections and provides BigQuery examples, allowing them to debug issues with BigQuery or their prompts.",{"category":147,"check":148,"severity":42,"summary":149},"Execution","Pinned dependencies","The skill does not use third-party dependencies or scripts requiring specific interpreters.",{"category":33,"check":151,"severity":42,"summary":152},"Dry-run preview","The skill is purely informational and does not perform any state-changing operations or send data outward.",{"category":154,"check":155,"severity":42,"summary":156},"Protocol","Idempotent retry & timeouts","The skill does not make remote calls or perform state-changing operations that would require idempotency or timeouts.",{"category":117,"check":158,"severity":42,"summary":159},"Telemetry opt-in","The skill does not emit telemetry.",{"category":40,"check":161,"severity":24,"summary":162},"Precise Purpose","The description and usage examples clearly define the skill's purpose (GA4 BigQuery schema reference and query patterns) and provide specific triggers for its use.",{"category":40,"check":164,"severity":24,"summary":165},"Concise Frontmatter","The frontmatter is concise and effectively summarizes the skill's core capability and usage.",{"category":45,"check":167,"severity":24,"summary":168},"Concise Body","The SKILL.md body is well-organized with progressive disclosure, keeping the core instructions concise and deferring detailed schemas and queries.",{"category":170,"check":171,"severity":24,"summary":172},"Context","Progressive Disclosure","Detailed schemas and query patterns are presented inline, but the structure is clear and could be further organized into separate files if the content grew substantially. 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It also offers performance best practices for BigQuery and data quality checks.",[195,196,197,198,199],"Complete GA4 BigQuery schema reference","Detailed explanations of nested fields (event_params, user_properties, etc.)","Ready-to-use BigQuery SQL query examples for common use cases","Guidance on performance best practices for BigQuery","Data quality checks for GA4 exports",[201,202,203],"Directly connecting to Google Analytics or BigQuery APIs","Executing queries on behalf of the user","Providing real-time analytics dashboards","3.0.0","4.4.0","To serve as a comprehensive, expert guide for users needing to understand and query Google Analytics 4 data exported to BigQuery.","The skill is exceptionally well-documented, comprehensive, and safe, with a clear purpose and excellent examples. 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Optionally hand off to LinkedIn Ads to launch as a sponsored content campaign with ICP-aligned targeting.","linkedin-launch-video",{"claudeCode":12},"SKILL.md frontmatter at skills/linkedin-launch-video/SKILL.md",[446,447,449],{"path":268,"priority":269},{"path":448,"priority":297},"references/brand-identity.md",{"path":450,"priority":297},"references/composition-template.html",{"basePath":452,"description":453,"displayName":454,"installMethods":455,"rationale":456,"selectedPaths":457,"source":270,"sourceLanguage":18,"type":244},"skills/linkedin-micro-campaigns","Create precision-targeted LinkedIn ad campaigns for specific ICP segments — translates CRM data to LinkedIn targeting","linkedin-micro-campaigns",{"claudeCode":12},"SKILL.md frontmatter at skills/linkedin-micro-campaigns/SKILL.md",[458],{"path":268,"priority":269},{"basePath":460,"description":461,"displayName":462,"installMethods":463,"rationale":464,"selectedPaths":465,"source":270,"sourceLanguage":18,"type":244},"skills/meta-capi","Meta Conversions API (CAPI) Setup Reference — architecture, event types, customer information hashing, deduplication, implementation examples, AEM, and testing","meta-capi",{"claudeCode":12},"SKILL.md frontmatter at skills/meta-capi/SKILL.md",[466],{"path":268,"priority":269},{"basePath":468,"description":469,"displayName":470,"installMethods":471,"rationale":472,"selectedPaths":473,"source":270,"sourceLanguage":18,"type":244},"skills/non-commodity-content","Interview the user for specific client stories, anecdotes, refusals, and real numbers — then turn them into non-commodity SEO content Google actually wants to rank. Kills generic listicle output at the source.","non-commodity-content",{"claudeCode":12},"SKILL.md frontmatter at skills/non-commodity-content/SKILL.md",[474],{"path":268,"priority":269},{"basePath":476,"description":477,"displayName":478,"installMethods":479,"rationale":480,"selectedPaths":481,"source":270,"sourceLanguage":18,"type":244},"skills/pre-send-qa","Pre-flight QA for an email campaign — merge tags, broken links, spam triggers, compliance, mobile rendering — before you hit send","pre-send-qa",{"claudeCode":12},"SKILL.md frontmatter at skills/pre-send-qa/SKILL.md",[482],{"path":268,"priority":269},{"basePath":484,"description":485,"displayName":486,"installMethods":487,"rationale":488,"selectedPaths":489,"source":270,"sourceLanguage":18,"type":244},"skills/reddit-launch-video","Produce a Reddit-native 1:1 or 4:5 launch video using HyperFrames. Idiomatic Reddit feel — text-first, low-polish, sound-off, subreddit-aware. Optionally hand off to Reddit Ads to launch as a promoted post targeted to specific subreddits.","reddit-launch-video",{"claudeCode":12},"SKILL.md frontmatter at skills/reddit-launch-video/SKILL.md",[490,491,492],{"path":268,"priority":269},{"path":448,"priority":297},{"path":450,"priority":297},{"basePath":494,"description":495,"displayName":496,"installMethods":497,"rationale":498,"selectedPaths":499,"source":270,"sourceLanguage":18,"type":244},"skills/revenue-audit","Audit an email marketing program for revenue leaks — missing flows, dormant high-value subscribers, under-segmentation, promo gaps, stale automations — ranked by estimated $ impact","revenue-audit",{"claudeCode":12},"SKILL.md frontmatter at skills/revenue-audit/SKILL.md",[500],{"path":268,"priority":269},{"basePath":502,"description":503,"displayName":504,"installMethods":505,"rationale":506,"selectedPaths":507,"source":270,"sourceLanguage":18,"type":244},"skills/seo-audit","Full technical + content SEO analysis — uses live Search Console + Bing data when connected","seo-audit",{"claudeCode":12},"SKILL.md frontmatter at skills/seo-audit/SKILL.md",[508],{"path":268,"priority":269},{"basePath":510,"description":511,"displayName":512,"installMethods":513,"rationale":514,"selectedPaths":515,"source":270,"sourceLanguage":18,"type":244},"skills/seo-monitor","Monitor SEO rankings, queries, and indexing via Search Console MCP","seo-monitor",{"claudeCode":12},"SKILL.md frontmatter at skills/seo-monitor/SKILL.md",[516],{"path":268,"priority":269},{"basePath":518,"description":519,"displayName":520,"installMethods":521,"rationale":522,"selectedPaths":523,"source":270,"sourceLanguage":18,"type":244},"skills/structured-data","Schema.org Structured Data Reference — JSON-LD examples for every major schema type, rich results eligibility, testing tools, and implementation patterns","structured-data",{"claudeCode":12},"SKILL.md frontmatter at skills/structured-data/SKILL.md",[524],{"path":268,"priority":269},{"basePath":526,"description":527,"displayName":528,"installMethods":529,"rationale":530,"selectedPaths":531,"source":270,"sourceLanguage":18,"type":244},"skills/subject-line-lab","Mine your actual subject-line history from Klaviyo / Mailchimp / Rule / Get a Newsletter, find the patterns that work for YOUR list, and generate tuned candidates","subject-line-lab",{"claudeCode":12},"SKILL.md frontmatter at skills/subject-line-lab/SKILL.md",[532],{"path":268,"priority":269},{"basePath":534,"description":535,"displayName":536,"installMethods":537,"rationale":538,"selectedPaths":539,"source":270,"sourceLanguage":18,"type":244},"skills/tiktok-launch-video","Produce a 9:16 TikTok-native launch video for a product, feature, or campaign using HyperFrames. Idiomatic TikTok pacing, burned-in captions, hook-in-1s structure. Optionally hand off to TikTok Ads to launch as a Spark/in-feed ad.","tiktok-launch-video",{"claudeCode":12},"SKILL.md frontmatter at skills/tiktok-launch-video/SKILL.md",[540,541,542],{"path":268,"priority":269},{"path":448,"priority":297},{"path":450,"priority":297},{"basePath":544,"description":545,"displayName":546,"installMethods":547,"rationale":548,"selectedPaths":549,"source":270,"sourceLanguage":18,"type":244},"skills/utm-builder","UTM Parameter Strategy & Builder — naming conventions, GA4 channel grouping rules, auto-tagging, common mistakes, and BigQuery validation queries","utm-builder",{"claudeCode":12},"SKILL.md frontmatter at skills/utm-builder/SKILL.md",[550],{"path":268,"priority":269},{"basePath":552,"description":553,"displayName":554,"installMethods":555,"rationale":556,"selectedPaths":557,"source":270,"sourceLanguage":18,"type":244},"skills/video-to-gif","Convert an MP4 (e.g. a HyperFrames render or a screen recording) to a high-quality GIF using FFmpeg's two-pass palette method. Picks the right preset for the target surface — Slack/DMs/Twitter/email/Reddit/GitHub — so you don't ship a 40MB GIF to a 5MB inbox.","video-to-gif",{"claudeCode":12},"SKILL.md frontmatter at skills/video-to-gif/SKILL.md",[558],{"path":268,"priority":269},{"basePath":560,"description":561,"displayName":562,"installMethods":563,"rationale":564,"selectedPaths":565,"source":270,"sourceLanguage":18,"type":244},"skills/website-migration-audit","Compare a production site against a staging/redesign version — SEO parity, content integrity, missing pages, and launch readiness","website-migration-audit",{"claudeCode":12},"SKILL.md frontmatter at skills/website-migration-audit/SKILL.md",[566],{"path":268,"priority":269},{"basePath":568,"description":569,"displayName":570,"installMethods":571,"rationale":572,"selectedPaths":573,"source":270,"sourceLanguage":18,"type":244},"skills/welcome-series","Generate a full 5-email welcome series from a brand URL — subjects, preheaders, bodies, and send timing, ready to paste into any ESP","welcome-series",{"claudeCode":12},"SKILL.md frontmatter at skills/welcome-series/SKILL.md",[574],{"path":268,"priority":269},{"basePath":576,"description":577,"displayName":578,"installMethods":579,"rationale":580,"selectedPaths":581,"source":270,"sourceLanguage":18,"type":244},"skills/winback-engine","Find dormant subscribers, segment by historical value, draft personalized winback emails per tier, and identify suppression candidates","winback-engine",{"claudeCode":12},"SKILL.md frontmatter at skills/winback-engine/SKILL.md",[582],{"path":268,"priority":269},{"sources":584},[585],"manual",{"closedIssues90d":8,"description":587,"forks":232,"homepage":588,"openIssues90d":8,"pushedAt":234,"readmeSize":230,"stars":235,"topics":589},"Marketing skills for Claude Code — SEO audits and implementation, ad analysis, ad optimization. Free skills need no account. $9/mo for live Search Console, Bing & LinkedIn data.","https://cogny.com",[590,591,592,593,594,595,596,597,598,599,600,601,602,603],"agent-skills","ai-agents","claude-code","claude-skills","cluade-mcp","cursor","geo","growth-hacking","llm","marketing","mcp","seo","vibe","windsurf",{"classifiedAt":605,"discoverAt":606,"extractAt":607,"githubAt":607,"updatedAt":605},1778684091751,1778684086122,1778684089811,[212,214,211,215,216,213],{"evaluatedAt":239,"extractAt":610,"updatedAt":239},1778684091954,[],[613,645,676,698,726,755],{"_creationTime":614,"_id":615,"community":616,"display":617,"identity":623,"providers":628,"relations":638,"tags":641,"workflow":642},1778695383013.7273,"k17cveqe4pkbjprsw25bmms9c186m39j",{"reviewCount":8},{"description":618,"installMethods":619,"name":621,"sourceUrl":622},"Generate SQL queries from natural language descriptions. Supports BigQuery, PostgreSQL, MySQL, and other dialects. Reads database schemas from uploaded diagrams or documentation. Use when writing SQL, building data reports, exploring databases, or translating business questions into queries.",{"claudeCode":620},"phuryn/pm-skills","SQL Query Generator","https://github.com/phuryn/pm-skills",{"basePath":624,"githubOwner":625,"githubRepo":626,"locale":18,"slug":627,"type":244},"pm-data-analytics/skills/sql-queries","phuryn","pm-skills","sql-queries",{"evaluate":629,"extract":636},{"promptVersionExtension":204,"promptVersionScoring":205,"score":630,"tags":631,"targetMarket":217,"tier":218},98,[213,632,633,212,634,635,214],"database","query-generation","postgresql","mysql",{"commitSha":251,"license":637},"MIT",{"parentExtensionId":639,"repoId":640},"k178tymnbwshrrmjc2e1qtf8f586mfz3","kd759mc43bg9ypk46ka87r3wa586npt5",[212,214,632,635,634,633,213],{"evaluatedAt":643,"extractAt":644,"updatedAt":643},1778695653467,1778695383013,{"_creationTime":646,"_id":647,"community":648,"display":649,"identity":655,"providers":659,"relations":669,"tags":672,"workflow":673},1778695548458.4036,"k171cqe6hd4yd3ktqnf3qy9z5186mmff",{"reviewCount":8},{"description":650,"installMethods":651,"name":653,"sourceUrl":654},"Design and execute insect population surveys covering survey design, sampling methods, field execution, specimen identification, diversity index calculation including Shannon-Wiener and Simpson indices, statistical analysis, and reporting. Covers defining survey objectives, selecting study sites, determining sampling intensity and replication, choosing sampling methods appropriate to target taxa, standardizing collection effort, recording environmental covariates, identifying specimens to the lowest practical taxonomic level, calculating species richness, Shannon-Wiener diversity (H'), Simpson diversity (1-D), evenness, rarefaction curves, multivariate ordination, and producing survey reports with species lists and conservation implications. Use when conducting baseline biodiversity assessments, monitoring insect populations over time, comparing insect communities across habitats or treatments, assessing environmental impact, or supporting conservation planning with quantitative ecological data.\n",{"claudeCode":652},"pjt222/agent-almanac","survey-insect-population","https://github.com/pjt222/agent-almanac",{"basePath":656,"githubOwner":657,"githubRepo":658,"locale":18,"slug":653,"type":244},"skills/survey-insect-population","pjt222","agent-almanac",{"evaluate":660,"extract":668},{"promptVersionExtension":204,"promptVersionScoring":205,"score":661,"tags":662,"targetMarket":217,"tier":218},100,[663,664,665,666,667,214],"entomology","insects","ecology","biodiversity","survey",{"commitSha":251},{"parentExtensionId":670,"repoId":671},"k170h0janaa9kwn7cfgfz2ykss86mmh9","kd7aryv63z61j39n2td1aeqkvh86mh12",[666,214,665,663,664,667],{"evaluatedAt":674,"extractAt":675,"updatedAt":674},1778701822946,1778695548458,{"_creationTime":677,"_id":678,"community":679,"display":680,"identity":684,"providers":686,"relations":694,"tags":695,"workflow":696},1778695548458.3613,"k17dx6tyy2yb3z5pp1vgmg46ad86nm18",{"reviewCount":8},{"description":681,"installMethods":682,"name":683,"sourceUrl":654},"Fit cognitive drift-diffusion models (Ratcliff DDM) to reaction time and accuracy data with parameter estimation (drift rate, boundary separation, non-decision time), model comparison, and parameter recovery validation. Use when modeling binary decision-making with reaction time data, estimating cognitive parameters from experimental data, comparing sequential sampling model variants, or decomposing speed-accuracy tradeoff effects into latent cognitive components.\n",{"claudeCode":652},"fit-drift-diffusion-model",{"basePath":685,"githubOwner":657,"githubRepo":658,"locale":18,"slug":683,"type":244},"skills/fit-drift-diffusion-model",{"evaluate":687,"extract":693},{"promptVersionExtension":204,"promptVersionScoring":205,"score":661,"tags":688,"targetMarket":217,"tier":218},[689,690,691,692,214],"cognitive-science","modeling","statistics","python",{"commitSha":251},{"parentExtensionId":670,"repoId":671},[689,214,690,692,691],{"evaluatedAt":697,"extractAt":675,"updatedAt":697},1778698191612,{"_creationTime":699,"_id":700,"community":701,"display":702,"identity":708,"providers":711,"relations":719,"tags":722,"workflow":723},1778695720086.7703,"k176r34g5a5fjn1z1a4gq6v88186nje0",{"reviewCount":8},{"description":703,"installMethods":704,"name":706,"sourceUrl":707},"Designs an A/B test or experiment with clear hypothesis, variants, success metrics, sample size, and duration. Use when planning experiments to validate product changes or test hypotheses.",{"claudeCode":705},"product-on-purpose/pm-skills","measure-experiment-design","https://github.com/product-on-purpose/pm-skills",{"basePath":709,"githubOwner":710,"githubRepo":626,"locale":18,"slug":706,"type":244},"skills/measure-experiment-design","product-on-purpose",{"evaluate":712,"extract":718},{"promptVersionExtension":204,"promptVersionScoring":205,"score":661,"tags":713,"targetMarket":217,"tier":218},[714,715,716,717,214],"ab-testing","experimentation","product-management","a-b-testing",{"commitSha":251},{"parentExtensionId":720,"repoId":721},"k1721116hsfj7zg78w03432n8986n6y8","kd78ksv1wjj826ds5j1sh2kqnx86mhqf",[717,714,214,715,716],{"evaluatedAt":724,"extractAt":725,"updatedAt":724},1778696438706,1778695720086,{"_creationTime":727,"_id":728,"community":729,"display":730,"identity":736,"providers":741,"relations":749,"tags":751,"workflow":752},1778691799740.488,"k1707r3f2j67714pvq6wk0r6y186m2zd",{"reviewCount":8},{"description":731,"installMethods":732,"name":734,"sourceUrl":735},"Differential gene expression analysis (Python DESeq2). Identify DE genes from bulk RNA-seq counts, Wald tests, FDR correction, volcano/MA plots, for RNA-seq analysis.",{"claudeCode":733},"K-Dense-AI/claude-scientific-skills","PyDESeq2","https://github.com/K-Dense-AI/claude-scientific-skills",{"basePath":737,"githubOwner":738,"githubRepo":739,"locale":18,"slug":740,"type":244},"scientific-skills/pydeseq2","K-Dense-AI","claude-scientific-skills","pydeseq2",{"evaluate":742,"extract":748},{"promptVersionExtension":204,"promptVersionScoring":205,"score":661,"tags":743,"targetMarket":217,"tier":218},[744,745,746,747,692,214],"bioinformatics","genomics","rna-seq","deseq2",{"commitSha":251,"license":637},{"repoId":750},"kd79rphh5gexy91xmpxc05h5mh86mm9r",[744,214,747,745,692,746],{"evaluatedAt":753,"extractAt":754,"updatedAt":753},1778693766611,1778691799740,{"_creationTime":756,"_id":757,"community":758,"display":759,"identity":765,"providers":769,"relations":776,"tags":779,"workflow":780},1778692306427.1045,"k17d6kt5pj00skt9795rm9q2dx86nsbt",{"reviewCount":8},{"description":760,"installMethods":761,"name":763,"sourceUrl":764},"YOLO mode. Spawns 4 parallel C-suite agents (CEO, CTO, CFO, COO). Each analyzes the business from their perspective using ALL available data. Produces unfiltered Hard Truths report. After user types YOLO, autonomously runs the business for a day using /loop.",{"claudeCode":762},"Lifecycle-Innovations-Limited/claude-ops","ops-yolo","https://github.com/Lifecycle-Innovations-Limited/claude-ops",{"basePath":766,"githubOwner":767,"githubRepo":768,"locale":18,"slug":763,"type":244},"claude-ops/skills/ops-yolo","Lifecycle-Innovations-Limited","claude-ops",{"evaluate":770,"extract":775},{"promptVersionExtension":204,"promptVersionScoring":205,"score":661,"tags":771,"targetMarket":217,"tier":218},[772,591,773,774,214],"business-operations","automation","c-suite",{"commitSha":251},{"parentExtensionId":777,"repoId":778},"k17d0t6ns7y6t377pfprg128hd86nm89","kd7d52tcek2e34r805zs06b10d86n39v",[591,773,772,774,214],{"evaluatedAt":781,"extractAt":782,"updatedAt":781},1778693076881,1778692306427]