「rag」の検索結果

Use when working with physics bodies, collision shapes, raycasting, areas, rigid bodies, ragdolls, soft bodies, Jolt physics, and physics interpolation in Godot 4.3+

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Post-earnings quarterly update reports for A-share companies under coverage. Analyzes 业绩快报/正式财报, generates variance tables (actual vs 一致预期 vs prior), flags key drivers, and drafts structured earnings notes in Chinese sell-side format. Use instead of the original earnings-analysis skill for Chinese equities. Triggers on "A股财报分析", "季度业绩点评", "年报/中报点评", "earnings review", or "[company] earnings".

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。

Pre-earnings analysis for A-share stocks. Builds scenario frameworks (actual vs consensus, beat/miss cases), identifies key metrics to watch, and prepares positioning notes before Chinese companies report quarterly results. Use instead of the original earnings-preview skill for A-share coverage. Triggers on "A股财报前瞻", "季报前瞻", "业绩前瞻", "earnings preview", "what to watch for [company] earnings", or "pre-earnings setup".

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Track upcoming catalysts for A-share coverage universe — earnings dates, regulatory announcements, sector conferences, product launches, and policy events relevant to Chinese equities. Adapted from the original catalyst-calendar skill for A-share market conventions. Triggers on "A股催化剂日历", "事件日历", "财报日历", "earnings calendar A-share", "upcoming catalysts China", or "what's coming up for [company]".

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Maps intelligence for local SEO — geo-grid rank tracking, GBP profile auditing via API, review intelligence across Google/Tripadvisor/Trustpilot, cross-platform NAP verification (Google/Bing/Apple/OSM), competitor radius mapping, and LocalBusiness schema generation from API data. Three-tier capability: free (Overpass + Geoapify), DataForSEO (full intelligence), DataForSEO + Google (maximum coverage). Use when user says "maps", "geo-grid", "rank tracking", "GBP audit", "review velocity", "competitor radius", "maps analysis", "local rank tracking", "Share of Local Voice", or "SoLV".

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Implement persistent memory patterns for AI agents using AgentDB. Includes session memory, long-term storage, pattern learning, and context management. Use when building stateful agents, chat systems, or intelligent assistants.

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Implement semantic vector search with AgentDB for intelligent document retrieval, similarity matching, and context-aware querying. Use when building RAG systems, semantic search engines, or intelligent knowledge bases.

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Survey the codebase, pick ONE high-leverage deepening opportunity (filtering out anything already proposed), and publish it as a PRD-shaped GitHub issue via /to-prd-project. Designed to run unattended in the daily architecture-review workflow.

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Pre-refactor safety checklist. Verifies test coverage exists before AI modifies existing code. Use before asking AI to refactor anything.

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。

iPadOS-specific patterns including Stage Manager, multi-window, drag and drop, keyboard shortcuts, pointer interactions, and Apple Pencil support. Use when building iPad-optimized features.

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Generates authentication infrastructure with Sign in with Apple, biometrics, and Keychain storage. Use when user wants to add authentication, login, or Sign in with Apple.

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。

Generates SwiftData or CoreData persistence layer with optional iCloud sync. Use when user wants to add local storage, data persistence, or cloud sync.

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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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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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Security category index for Apple platforms. Routes to the privacy-manifests skill. General secure-storage/biometrics/ATS guidance was retired in the 2026 blind-test audit — current models cover it natively.

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Survey any codebase as a senior advisor and produce prioritized, self-contained implementation plans for OTHER models/agents to execute. Strictly read-only on source code — never implements, fixes, or refactors anything itself. Use when asked to audit a codebase, find improvement opportunities (bugs, security, performance, test coverage, tech debt, migrations, DX), suggest features or where to take the project next (roadmap, product direction), or generate handoff plans for another agent to implement.

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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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Provides large-scale single-cell omics data manipulation using Genomic Data Structure (GDS) files. It combines dense and sparse matrices stored in GDS files and the Bioconductor infrastructure framework (SingleCellExperiment and DelayedArray) to provide out-of-memory data storage and large-scale manipulation using the R programming language.

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The analysis and visualization of alternative splicing (AS) events from RNA sequencing data remains challenging. SpliceWiz is a user-friendly and performance-optimized R package for AS analysis, by processing alignment BAM files to quantify read counts across splice junctions, IRFinder-based intron retention quantitation, and supports novel splicing event identification. We introduce a novel visualization for AS using normalized coverage, thereby allowing visualization of differential AS across

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SGC is a semi-supervised pipeline for gene clustering in gene co-expression networks. SGC consists of multiple novel steps that enable the computation of highly enriched modules in an unsupervised manner. But unlike all existing frameworks, it further incorporates a novel step that leverages Gene Ontology information in a semi-supervised clustering method that further improves the quality of the computed modules.

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Defines an S4 class for storing data from spatial -omics experiments. The class extends SingleCellExperiment to support storage and retrieval of additional information from spot-based and molecule-based platforms, including spatial coordina

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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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The creation of effective visualizations is a fundamental component of data analysis. In biomedical research, new challenges are emerging to visualize multi-dimensional data in a 2D space, but current data visualization tools have limited capabilities. To address this problem, we leverage Gestalt principles to improve the design and interpretability of multi-dimensional data in 2D data visualizations, layering aesthetics to display multiple variables. The proposed visualization can be applied to

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phyloseq provides a set of classes and tools to facilitate the import, storage, analysis, and graphical display of microbiome census data.

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。