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Assemble the final `.ppmplugin` binary bundle for a PAM native extension and verify its contents. First **reconciles** the manifest's declared `entrypoints` against the binaries actually staged — if the manifest declares a platform with no built binary it gates (build it / ship without it / stop) rather than shipping a broken bundle. Then re-runs the plugin's upload-compatibility checks on the reconciled manifest, zips the manifest plus whichever of `android/<PascalName>Plugin.dex` and `ios/<PascalName>Plugin.framework/` are present into `ppmplugin/<name>.ppmplugin`, and verifies the archive layout with `jar tf` (exactly the manifest + the shipped binaries — nothing missing, nothing extra). Output: a statically verified `.ppmplugin` file on disk. Prereqs: `jar` (JDK). Run after /generate-ppmplugin-manifest and the build skill(s).

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Expert CSRD (Corporate Sustainability Reporting Directive, EU 2022/2464) compliance advisor. Use this skill whenever a user asks about CSRD, European Sustainability Reporting Standards (ESRS), double materiality assessment, sustainability reporting obligations, ESG disclosure, CSRD scope and thresholds, value chain reporting, XBRL digital tagging, third-party assurance, CSRD gap assessments, CSRD implementation timelines, ESRS E1–E5 environmental standards, ESRS S1–S4 social standards, ESRS G1 governance, the 2026 Omnibus scope change (Directive (EU) 2026/470, 1,000+ employees) and revised/simplified ESRS (July 2026), CSRD vs GRI/TCFD/SASB alignment, or any EU corporate sustainability reporting question. Trigger even if the user only mentions "ESG reporting Europe", "sustainability disclosure EU", or "non-financial reporting".

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Calendar litigation and arbitration deadlines from a scheduling order. Parses a PDF scheduling order, identifies key dates, computes backward deadlines using the applicable rules (Colorado CRCP, Federal FRCP, or arbitration forum rules for AAA/JAMS), and generates an .ics calendar file for Outlook or Google Calendar import. Use this skill whenever the user mentions: litigation deadlines, scheduling order, case management order, deadline calendaring, discovery deadlines, trial preparation deadlines, arbitration scheduling, or anything related to computing or tracking court or arbitration deadlines. Also trigger when the user uploads a PDF that appears to be a court scheduling order or arbitration scheduling order.

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Expert CSRD (Corporate Sustainability Reporting Directive, EU 2022/2464) compliance advisor. Use this skill whenever a user asks about CSRD, European Sustainability Reporting Standards (ESRS), double materiality assessment, sustainability reporting obligations, ESG disclosure, CSRD scope and thresholds, value chain reporting, XBRL digital tagging, third-party assurance, CSRD gap assessments, CSRD implementation timelines, ESRS E1–E5 environmental standards, ESRS S1–S4 social standards, ESRS G1 governance, CSRD vs GRI/TCFD/SASB alignment, or any EU corporate sustainability reporting question. Trigger even if the user only mentions "ESG reporting Europe", "sustainability disclosure EU", or "non-financial reporting".

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Adversarially stress-tests a legal text — a contract, statute, regulation, or judicial opinion — for interpretive ambiguity: it finds the seams where the people governed by it will later disagree about what it means and turns each into a concrete dispute scenario with both sides' arguments, the likely outcome, and a fix. Use it whenever someone wants to pressure-test, red-team, audit, or find weak spots, loopholes, gaps, ambiguities, or drafting problems in a legal document; whenever a drafter wants to tighten a contract, statute, regulation, or opinion before it issues; whenever a litigator wants to mine an opinion or contract for arguments; or whenever someone hands over a legal text and asks where it will be fought over or for issue-spotting. Trigger it for contract review, statutory-ambiguity analysis, judicial-opinion scope analysis, and drafting QA — even if the user never says "stress-test" or "ambiguity."

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When you want to brainstorm and check available .com domains for a new project — brand naming, aftermarket pricing (HugeDomains / Afternic / Sedo / Dan), USPTO trademark screening, and social handle availability. Built on Laura Roeder's "work backwards from availability" method. Combines Vercel CLI, whois, Domainr, Namecheap, and agent-browser, each for what it reliably does. Workflow: budget → brainstorm → availability check → whois cross-check → price → aftermarket sweep (plus liveness probe and drop-watch) → bucket → negotiate → trademark + socials → buy. Triggers on "/domain," "find a domain," "check domain availability," "brainstorm a domain," "what .com is available for X," "domain hunt," "name my project," "is X.com available," "aftermarket price on X.com," "trademark check for X."

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Run a structured accessibility audit on an iOS/macOS app — automated XCUITest audits, Accessibility Inspector, manual VoiceOver/Dynamic Type passes, and App Store Accessibility Nutrition Label evaluation. Use before release, when preparing Nutrition Label declarations, or for EU Accessibility Act compliance.

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Generate accessibility infrastructure for VoiceOver, Dynamic Type, and accessibility features. Use when improving app accessibility, adding accessibility labels and hints, or auditing compliance.

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standR is an user-friendly R package providing functions to assist conducting good-practice analysis of Nanostring's GeoMX DSP data. All functions in the package are built based on the SpatialExperiment object, allowing integration into various spatial transcriptomics-related packages from Bioconductor. standR allows data inspection, quality control, normalization, batch correction and evaluation with informative visualizations.

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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 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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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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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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A set of tools for working with miRNA affinity models (KdModels), efficiently scanning for miRNA binding sites, and predicting target repression. It supports scanning using miRNA seeds, full miRNA sequences (enabling 3' alignment) and KdModels, and includes the prediction of slicing and TDMD sites. Finally, it includes utility and plotting functions (e.g. for the visual representation of miRNA-target alignment).

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SpotClean is a computational method to adjust for spot swapping in spatial transcriptomics data. Recent spatial transcriptomics experiments utilize slides containing thousands of spots with spot-specific barcodes that bind mRNA. Ideally, unique molecular identifiers at a spot measure spot-specific expression, but this is often not the case due to bleed from nearby spots, an artifact we refer to as spot swapping. SpotClean is able to estimate the contamination rate in observed data and decontamin

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Performs unbiased cell type recognition from single-cell RNA sequencing data, by leveraging reference transcriptomic datasets of pure cell types to infer the cell of origin of each single cell independently.

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SpatialFeatureExperiment (SFE) is a new S4 class for working with spatial single-cell genomics data. The voyager package implements basic exploratory spatial data analysis (ESDA) methods for SFE. Univariate methods include univariate global spatial ESDA methods such as Moran's I, permutation testing for Moran's I, and correlograms. Bivariate methods include Lee's L and cross variogram. Multivariate methods include MULTISPATI PCA and multivariate local Geary's C recently developed by Anselin. The

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This package performs differential pattern analysis for Ribo-seq data. It identifies genes with significantly different patterns in the ribosome footprint between two conditions. RiboDiPA contains five major components including bam file processing, P-site mapping, data binning, differential pattern analysis and footprint visualization.

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The epistack package main objective is the visualizations of stacks of genomic tracks (such as, but not restricted to, ChIP-seq, ATAC-seq, DNA methyation or genomic conservation data) centered at genomic regions of interest. epistack needs three different inputs: 1) a genomic score objects, such as ChIP-seq coverage or DNA methylation values, provided as a `GRanges` (easily obtained from `bigwig` or `bam` files). 2) a list of feature of interest, such as peaks or transcription start sites, provi

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Provides functionalities to visualize and contextualize CRISPR guide RNAs (gRNAs) on genomic tracks across nucleases and applications. Works in conjunction with the crisprBase and crisprDesign Bioconductor packages. Plots are produced using the Gviz framework.

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Uses DESeq2 to estimate variance-mean dependence in count data from high-throughput sequencing assays and test for differential expression based on a model using the negative binomial distribution.

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Intuitive framework for identifying spatially variable genes (SVGs) via edgeR, a popular method for performing differential expression analyses. Based on pre-annotated spatial clusters as summarized spatial information, DESpace models gene expression using a negative binomial (NB), via edgeR, with spatial clusters as covariates. SVGs are then identified by testing the significance of spatial clusters. The method is flexible and robust, and is faster than the most SV methods. Furthermore, to the

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We propose an Asymmetric Within-Sample Transformation (AWST) to regularize RNA-seq read counts and reduce the effect of noise on the classification of samples. AWST comprises two main steps: standardization and smoothing. These steps transform gene expression data to reduce the noise of the lowly expressed features, which suffer from background effects and low signal-to-noise ratio, and the influence of the highly expressed features, which may be the result of amplification bias and other experi

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