「elo」の検索結果

Swift language patterns and best practices including concurrency, performance, and modern idioms. Use for Swift language-level code review or architecture guidance.

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TDD and testing skills for iOS/macOS apps. Covers characterization tests, TDD workflows, test contracts, snapshot tests, test infrastructure, and deterministic quality gates (fitness functions, coverage ratchet, mutation testing). Use for test-driven development, adding tests to existing code, or building test infrastructure.

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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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Legal document generation and compliance guidance for indie Apple developers. Covers privacy policies, terms of service, EULAs, GDPR/CCPA/DPDP compliance, and Apple App Store legal requirements. Use when user needs legal documents or compliance guidance.

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Senior developer-level release review for macOS/iOS apps. Identifies security, privacy, UX, and distribution issues with actionable fixes. Use when preparing an app for release, want a critical review, or before App Store submission.

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Growth skills for indie Apple developers — user acquisition, analytics interpretation, press/media outreach, community building, and indie business operations. Also covers the stage-by-stage store-growth audit and the post-launch store-signals loop. Use when user asks about growing their app, auditing growth levers, understanding metrics, getting press coverage, or running an indie dev business.

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Write B2B cold emails and follow-up sequences that get replies. Use when the user wants to write cold outreach emails, prospecting emails, cold email campaigns, sales development emails, or SDR emails. Covers subject lines, opening lines, body copy, CTAs, personalization, and multi-touch follow-up sequences.

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treekoR is a novel framework that aims to utilise the hierarchical nature of single cell cytometry data to find robust and interpretable associations between cell subsets and patient clinical end points. These associations are aimed to recapitulate the nested proportions prevalent in workflows inovlving manual gating, which are often overlooked in workflows using automatic clustering to identify cell populations. We developed treekoR to: Derive a hierarchical tree structure of cell clusters; qua

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Provides basic utility functions for performing single-cell analyses, focusing on simple normalization, quality control and data transformations. Also provides some helper functions to assist development of other packages.

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Implements a variety of methods for batch correction of single-cell (RNA sequencing) data. This includes methods based on detecting mutually nearest neighbors, as well as several efficient variants of linear regression of the log-expression

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Gene Expression Omnibus(GEO) and The Cancer Genome Atlas (TCGA) provide us with a wealth of data, such as RNA-seq, DNA Methylation, SNP and Copy number variation data. It's easy to download data from TCGA using the gdc tool, but processing these data into a format suitable for bioinformatics analysis requires more work. This R package was developed to handle these data.

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This package provides a workflow for the use of EaSIeR tool, developed to assess patients' likelihood to respond to ICB therapies providing just the patients' RNA-seq data as input. We integrate RNA-seq data with different types of prior knowledge to extract quantitative descriptors of the tumor microenvironment from several points of view, including composition of the immune repertoire, and activity of intra- and extra-cellular communications. Then, we use multi-task machine learning trained in

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mastR is an R package designed for automated screening of signatures of interest for specific research questions. The package is developed for generating refined lists of signature genes from multiple group comparisons based on the results from edgeR and limma differential expression (DE) analysis workflow. It also takes into account the background noise of tissue-specificity, which is often ignored by other marker generation tools. This package is particularly useful for the identification of g

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A package that provides a client interface to the Kyoto Encyclopedia of Genes and Genomes (KEGG) REST API. Only for academic use by academic users belonging to academic institutions (see <https://www.kegg.jp/kegg/rest/>). Note that KEGGREST

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the R package BioNAR, developed to step by step analysis of PPI network. The aim is to quantify and rank each protein’s simultaneous impact into multiple complexes based on network topology and clustering. Package also enables estimating of co-occurrence of diseases across the network and specific clusters pointing towards shared/common mechanisms.

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The biovizBase package is designed to provide a set of utilities, color schemes and conventions for genomic data. It serves as the base for various high-level packages for biological data visualization. This saves development effort and enc

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Expert guidance for designing, assessing, and optimizing Azure workloads using Azure Well Architected. Covers design review checklists, recommendations, design principles, tradeoffs, service guides, workload patterns, and assessment questions. Use when designing AI, HPC, SaaS, AVD/AVS workloads, choosing regions/AZs, or configuring core Azure services, and other Azure Well Architected related development tasks.

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Expert guidance for designing Azure solutions using Azure Architecture. Covers reference architectures, solution ideas, design patterns, technology choices, architecture styles, best practices, anti-patterns, example workloads, and migration guides. Use when designing AKS/microservices, hybrid/Arc, SAP or mainframe migrations, IoT/Edge, or mission-critical BCDR, and other Azure Architecture related development tasks.

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Expert guidance for planning and executing cloud adoption using Azure Cloud Adoption Framework. Covers strategy, planning, readiness & landing zones, adoption patterns, governance, security, operations & management, organization & teams, and adoption scenarios. Use when planning AVD, SAP, Oracle, VMware, AI/ML workloads, or designing Azure landing zones and governance, and other Azure Cloud Adoption Framework related development tasks.

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Track rising, peaking, and fading crypto/tech narratives with quantitative mindshare + velocity signals and explicit positioning calls

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Business-development radar across your product family - find who's building, forking, integrating, and mentioning your products, ranked into a who-to-talk-to-this-week lead list.

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Amazon keyword rank tracking and performance analysis. Comprehensive ranking factor analysis, change diagnosis, improvement strategy development, and competitive position monitoring. Use when the user asks about keyword rankings, position tracking, ranking changes, or competitive analysis.

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Deep Amazon review analysis for competitive intelligence and product improvement. Extract sentiment patterns, recurring complaints, feature requests, and competitive insights from customer feedback. Turn reviews into actionable product development and marketing strategies. Use when the user asks about review analysis, customer feedback, product complaints, sentiment analysis, or what customers think about products.

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Update developer-facing documentation to reflect code changes on the current branch. Runs as an inline skill inside backend-agent and frontend-agent (step 2.5 of the internal sequence) after implementation and before DOD. Receives the explicit list of changed files from the implementation agent. No-op if no public API changes occurred.

日本語の概要は準備中です。原文の説明を表示しています。