Skills that do not fit the categories above (15K skills)
Generates lapsed user detection and re-engagement screens with personalized return experiences, win-back offers, and inactivity tracking. Use when user wants to re-engage inactive users, detect lapsed users, or build return flows.
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Platform-agnostic skills including skill creation templates and best practices. Use when creating new skills or improving existing ones.
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Handle App Store rejections, prepare submissions to avoid common rejection reasons, write Resolution Center responses, and navigate the appeal process. Use when user's app was rejected, is preparing for submission, or needs help with App Review.
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Guideline-4.3 anti-spam / originality gate — score whether an app (and each portfolio addition) is meaningfully distinct in function, content, and metadata before you invest or submit. Use at validation/new-app time and again before submission. Protects the whole developer account from 4.3 (spam/duplicate) rejections. NOT rejection-handler (that works an existing rejection) and NOT competitive-analysis (that positions in the market).
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Generates an in-app announcement banner system with remote configuration, scheduling, deep link actions, and dismiss tracking. Use when user wants in-app banners, promotional notices, maintenance alerts, or contextual announcements.
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Plan compelling App Store screenshot sequences that showcase your app's value. Use when preparing App Store assets, improving screenshot conversion, or drafting screenshot captions for a launch or major update.
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Integrate your app with iOS Visual Intelligence for camera-based search and object recognition. Use when adding visual search capabilities.
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Apple Intelligence skills for on-device AI features including Foundation Models, Visual Intelligence, App Intents, and intelligent assistants. Use when implementing AI-powered features.
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Generate compelling App Store descriptions that convert browsers into users. Use when writing initial descriptions, improving existing copy, or drafting promotional text and What's New for a major update.
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App Intents for Siri, Shortcuts, Spotlight, and Apple Intelligence integration including intent modes, interactive snippets, visual intelligence, and entity indexing. Use when implementing Siri integration, App Shortcuts, or Spotlight indexing.
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Use the Crabbox wrapper for OpenClaw remote validation across Linux, macOS, Windows, and WSL2, including delegated Blacksmith Testbox proof. Report the actual provider and id.
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Compact the current conversation into a handoff document for another agent to pick up.
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When the user wants to optimize any form that is NOT signup/registration — including lead capture forms, contact forms, demo request forms, application forms, survey forms, or checkout forms. Also use when the user mentions "form optimization," "lead form conversions," "form friction," "form fields," "form completion rate," or "contact form." For signup/registration forms, see signup-flow-cro. For popups containing forms, see popup-cro.
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When the user wants to optimize signup, registration, account creation, or trial activation flows. Also use when the user mentions "signup conversions," "registration friction," "signup form optimization," "free trial signup," "reduce signup dropoff," or "account creation flow." For post-signup onboarding, see onboarding-cro. For lead capture forms (not account creation), see form-cro.
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Teach the user a new skill or concept, within this workspace.
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Summarize small CSV files and identify the highest revenue month.
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Use when optimizing configurable system parameters against a measurable scalar objective.
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Monocle performs differential expression and time-series analysis for single-cell expression experiments. It orders individual cells according to progress through a biological process, without knowing ahead of time which genes define progre
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The 'msa' package provides a unified R/Bioconductor interface to the multiple sequence alignment algorithms ClustalW, ClustalOmega, and Muscle. All three algorithms are integrated in the package, therefore, they do not depend on any externa
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This package provides a client for the Bioconductor AnnotationHub web resource. The AnnotationHub web resource provides a central location where genomic files (e.g., VCF, bed, wig) and other resources from standard locations (e.g., UCSC, En
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This is an advanced version of TDbasedUFE, which is a comprehensive package to perform Tensor decomposition based unsupervised feature extraction. In contrast to TDbasedUFE which can perform simple the feature selection and the multiomics analyses, this package can perform more complicated and advanced features, but they are not so popularly required. Only users who require more specific features can make use of its functionality.
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This package enables the interpretation and analysis of results from a gene set enrichment analysis using network-based and text-mining approaches. Most enrichment analyses result in large lists of significant gene sets that are difficult to interpret. Tools in this package help build a similarity-based network of significant gene sets from a gene set enrichment analysis that can then be investigated for their biological function using text-mining approaches.
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Statial is a suite of functions for identifying changes in cell state. The functionality provided by Statial provides robust quantification of cell type localisation which are invariant to changes in tissue structure. In addition to this Statial uncovers changes in marker expression associated with varying levels of localisation. These features can be used to explore how the structure and function of different cell types may be altered by the agents they are surrounded with.
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Offers functions for plotting split (or implicit) networks (unrooted, undirected) and explicit networks (rooted, directed) with reticulations extending. 'ggtree' and using functions from 'ape' and 'phangorn'. It extends the 'ggtree' package [@Yu2017] to allow the visualization of phylogenetic networks using the 'ggplot2' syntax. It offers an alternative to the plot functions already available in 'ape' Paradis and Schliep (2019) <doi:10.1093/bioinformatics/bty633> and 'phangorn' Schliep (2011) <d
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