362 skills · sorted by relevance
Explain a trading model's prediction by ranking the input features that contributed to its signal. Returns a Markdown table and saves an attribution record with calculation settings, adding a digital signature when a signing key is available.
Set up and troubleshoot website conversion tracking for leads and purchases. Check that events represent confirmed success, prevent duplicate counts, and verify that conversions actually reach advertising or analytics platforms.
Plan and validate tracking for marketing and product decisions. Define events, configure GA4 and Google Tag Manager, standardize campaign link labels, and calculate metrics using matching time periods to produce dependable measurement plans and findings.
Explain how input features contribute to machine-learning predictions using SHAP. Select an explanation method and reference data, validate contributions against model outputs, and create charts for individual predictions or patterns across samples, including models with multiple outputs.
Track when assets begin moving together, assess the resulting loss of diversification, and examine which assets moved first during a crisis. Rank changes in asset relationships and report uncertainty explicitly for risk monitoring and retrospective analysis.
Connect security incidents across organizations by comparing attack indicators, techniques, and timelines. Build relationship graphs and campaign reports that document shared evidence, attribution confidence, and indicators useful for detection.
Compare multiple NemoClaw pull requests addressing the same issue. It checks merge eligibility, correctness, quality, and attribution, then produces an evidence-based recommendation for merging or choosing a candidate for further repair.
Merge GitHub pull requests while preserving credit for the original contributors. Covers straightforward merges, conflict resolution, selective file inclusion, duplicate PR closure, and checks that confirm both attribution and working code after integration.
Audit Apple Ads measurement, campaign structure, keywords, placements, bids, and budgets. Organize evidence, identify gaps and conflicting data, and produce prioritized recommendations while keeping proposed account changes in draft form.
Create a landscape card for an X post, featuring a short quote, insight, or data point. The layout combines prominent text with attribution, a handle, a category label, and a brand watermark.
Choose metrics for AI product revenue, sales efficiency, retention, and computing costs. Plan dashboards and weekly reviews, assess customer data quality, and decide how to credit marketing and sales interactions for completed deals.
Edit English and Chinese prose to reduce formulaic AI writing patterns, including filler, inflated claims, and vague attribution. Preserves the original meaning and intended tone while improving sentence variety, directness, and the writer’s voice.
Create a short animated quote or mission statement in a single HTML file. White and electric-blue panels meet at the center, a black accent bar grows, and text appears line by line with attribution and brand marks.
Edit English and Chinese prose to reduce formulaic wording, inflated claims, vague attributions, and repetitive sentence patterns. It preserves the core meaning and intended tone while improving rhythm, directness, and the writer’s voice.
Review session changes, group related files into focused Git commits, and draft messages explaining their purpose. Presents the plan for approval before committing, omits Claude attribution, and records development reasoning through a project script.
Route requests to commit, push, or save Git changes through a dedicated /commit skill. The workflow removes Claude attribution, records attempted approaches in reasoning.md, clears build attempts, and pushes changes when requested.
Sets up, audits, and reports on marketing measurement — tracking plans, event schemas, attribution models, and the dashboards built on them. Use this to instrument a site or product, audit tracking nobody trusts, choose or interpret an attribution model, build reporting that answers a specific question, or reconcile numbers that disagree between tools.
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Infers person-to-person transmission from pathogen genomes using outbreaker2, TransPhylo, phybreak, BadTrIP, SCOTTI, BEASTLIER, and SNP-distance / cluster-picker approaches (HIV-TRACE for HIV; transcluster). Defines outbreak clusters using pathogen-specific SNP thresholds (NOT a universal cutoff -- TB <=12 SNPs; MRSA <=15; C. difficile <=2; Klebsiella <=21), models within-host diversity and transmission bottlenecks, integrates contact-tracing data, distinguishes generation from serial interval, and attributes source via Bayesian source attribution (islandR). Use when investigating outbreaks for who-infected-whom, defining SNP-cluster outbreak definitions, accounting for unsampled intermediates, choosing between outbreaker2 (rich epi data) and TransPhylo (genomic-only after a dated phylogeny), running source attribution between host populations, calling HIV-TRACE thresholds appropriate to the local subtype, or distinguishing recent transmission from reactivation in TB or chronic HIV.
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Trains and applies base-resolution deep learning models on ChIP-seq / ChIP-nexus / CUT&RUN data. Uses BPNet (Avsec 2021 Nat Genet 53:354; soft motif syntax from ChIP-nexus), chromBPNet (Pampari A et al 2024 bioRxiv; bias-factorized base-resolution profiles), EnFormer (Avsec 2021 Nat Methods 18:1196; 196 kb input, ~100 kb effective receptive field), DeepSEA (Zhou 2015; multi-task CNN), and JASPAR 2026 deep-learning collection (1259 BPNet ChIP models). Performs in silico mutagenesis for variant-effect prediction, DeepLIFT/Grad attribution, and TF-MoDISco motif discovery from attribution scores. Use when predicting variant effects on TF binding, discovering soft motif syntax / cooperativity, integrating ChIP-seq with sequence-only predictions, or applying precomputed JASPAR Deep Learning models to new variants.
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Fetch WeatherKit current, minute, hourly, and daily forecasts; weather alerts; iOS 18+ changes, historical comparisons, summaries, and statistics; and required Apple Weather attribution. Use when integrating weather data, showing forecasts or alerts, caching WeatherKit responses, displaying attribution, or reviewing WeatherKit query limits in iOS apps.
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When the user wants to set up, audit, or optimize analytics tracking (GA4, events, conversions). Also use when the user mentions "Google Analytics," "GA4," "event tracking," "conversions," "attribution model," "gtag," "data layer," "GA4 setup," "conversion tracking," "event setup," "User ID tracking," or "CTA attribution." For traffic insights, use traffic-analysis.
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A discipline for running paid media that does not light money on fire. Hypothesis writing for paid spend, channel selection, budget allocation, audience targeting, bid strategy, campaign types, what NOT to spend on, attribution reality, and the failure modes that produce expensive lessons. Triggers on paid media strategy, ad budget allocation, channel selection, paid media plan, audit my Google Ads, audit my Meta Ads, scale paid media, kill underperforming campaign, paid media hypothesis, ad spend strategy, attribution reality, performance marketing strategy. Also triggers when a team is asking how to scale paid media, or whether to add a new channel, or how to reallocate spend across channels.
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Design measurement frameworks including event taxonomy, KPI hierarchy, dashboard architecture, attribution models, and analytics implementation strategy. Use this skill whenever the user wants to plan analytics, design dashboards, build event taxonomies, define KPIs, set up tracking, or audit existing measurement. Triggers on analytics strategy, measurement plan, event taxonomy, tracking plan, KPI framework, dashboard design, north star metric, attribution model, conversion tracking, GA4 setup, Mixpanel setup, analytics audit. Also triggers when the user has data but no clear way to use it, or wants to make decisions but doesn't know what to track.
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Run attribution on real conversion paths, comparing models. "which channels actually drive revenue"
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