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概要と使いどころ
Expert blueprint for inventory systems (Diablo, Resident Evil, Minecraft) covering slot-based containers, stacking logic, weight limits, equipment systems, and drag-drop UI. Use when building RPG inventories, survival item management, or loot systems. Keywords inventory, slot, stack, equipment, crafting, item, Resource, drag-drop.
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。
Expert blueprint for platformer games including precision movement (coyote time, jump buffering, variable jump height), game feel polish (squash/stretch, particle trails, camera shake), level design principles (difficulty curves, checkpoint placement), collectible systems (progression rewards), and accessibility options (assist mode, remappable controls). Based on Celeste/Hollow Knight design research. Trigger keywords: platformer, coyote_time, jump_buffer, game_feel, level_design, precision_movement.
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。
Expert blueprint for inventory systems (Diablo, Resident Evil, Minecraft) covering slot-based containers, stacking logic, weight limits, equipment systems, and drag-drop UI. Use when building RPG inventories, survival item management, or loot systems. Keywords inventory, slot, stack, equipment, crafting, item, Resource, drag-drop.
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。
Expert patterns for CharacterBody2D including platformer movement (coyote time, jump buffering, variable jump height), top-down movement (8-way, tank controls), collision handling, one-way platforms, and state machines. Use for player characters, NPCs, or enemies. Trigger keywords: CharacterBody2D, move_and_slide, is_on_floor, coyote_time, jump_buffer, velocity, get_slide_collision, one_way_platforms, state_machine.
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。
Comprehensive blueprint for Action RPGs including real-time combat (hitbox/hurtbox, stat-based damage), character progression (RPG stats, leveling, skill trees), loot systems (procedural item generation, affixes, rarity tiers), equipment systems (gear slots, stat modifiers), and ability systems (cooldowns, mana cost, AOE). Based on expert ARPG design from Diablo, Path of Exile, Souls-like developers. Trigger keywords: action_rpg, loot_generator, rpg_stats, skill_tree, hitbox_combat, item_affixes, equipment_slots, ability_cooldown, stat_scaling.
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。
Comprehensive truth scoring, code quality verification, and automatic rollback system with 0.95 accuracy threshold for ensuring high-quality agent outputs and codebase reliability.
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。
Localization and internationalization strategy for iOS/macOS apps. Covers market prioritization, language tier recommendations, minimum viable localization levels, translation workflows, cultural adaptation, localized ASO, and testing. Use when planning localization, expanding to new markets, deciding which languages to support, or planning translation workflow.
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。
Code generator skills that produce production-ready Swift code for common app components. Use when user wants to add logging, analytics, onboarding, review prompts, networking, authentication, paywalls, settings, persistence, error monitoring, CI/CD pipelines, localization, push notifications, deep linking, testing, accessibility, widgets, feature flags, app icons, image caching, pagination, HTTP caching, share cards, social export, subscription lifecycle, referral systems, watermarks, streak tracking, milestone celebrations, what's new screens, lapsed user re-engagement, usage insights, variable rewards, consent flows, account deletion, permission priming, force updates, state restoration, debug menus, offline queues, feedback forms, announcement banners, quick win sessions, Spotlight indexing, App Clips, screenshot automation, background processing, app extensions, data export, or SwiftUI preview sample data and variant matrices.
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。
SF Symbols end-to-end — choosing and configuring the 7,000+ system symbols (rendering modes, variable color/draw, gradients), authoring custom symbols that interpolate across weights, and the animation preset vocabulary. Use when picking iconography, building custom symbols, animating symbol state changes, or rendering values as symbols.
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。
Implements miscellaneous functions for interpretation of single-cell RNA-seq data. Methods are provided for assignment of cell cycle phase, detection of highly variable and significantly correlated genes, identification of marker genes, and
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Method for scalable identification of spatially variable genes (SVGs) in spatially-resolved transcriptomics data. The method is based on nearest-neighbor Gaussian processes and uses the BRISC algorithm for model fitting and parameter estimation. Allows identification and ranking of SVGs with flexible length scales across a tissue slide or within spatial domains defined by covariates. Scales linearly with the number of spatial locations and can be applied to datasets containing thousands or more
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。
SpatialDE is a method to find spatially variable genes (SVG) from spatial transcriptomics data. This package provides wrappers to use the Python SpatialDE library in R, using reticulate and basilisk.
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。
The sva package contains functions for removing batch effects and other unwanted variation in high-throughput experiment. Specifically, the sva package contains functions for the identifying and building surrogate variables for high-dimensi
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。
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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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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Multivariate methods are well suited to large omics data sets where the number of variables (e.g. genes, proteins, metabolites) is much larger than the number of samples (patients, cells, mice). They have the appealing properties of reducin
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Dirichlet-multinomial mixture models can be used to describe variability in microbial metagenomic data. This package is an interface to code originally made available by Holmes, Harris, and Quince, 2012, PLoS ONE 7(2): 1-15, as discussed fu
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MHC (major histocompatibility complex) molecules are cell surface complexes that present antigens to T cells. The repertoire of antigens presented in a given genetic background largely depends on the sequence of the encoded MHC molecules, and thus, in humans, on the highly variable HLA (human leukocyte antigen) genes of the hyperpolymorphic HLA locus. More than 28,000 different HLA alleles have been reported, with significant differences in allele frequencies between human populations worldwide
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Installs a self-contained conda instance that is managed by the R/Bioconductor installation machinery. This aims to provide a consistent Python environment that can be used reliably by Bioconductor packages. Functions are also provided to e
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。
Expert knowledge for Azure Service Fabric development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when designing Service Fabric clusters, Reliable Services/Actors, reverse proxy/API gateways, CRP/CRM settings, or sfctl automation, and other Azure Service Fabric related development tasks. Not for Azure Kubernetes Service (AKS) (use azure-kubernetes-service), Azure Container Apps (use azure-container-apps), Azure App Service (use azure-app-service), Azure Virtual Machines (use azure-virtual-machines).
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。
Delegate work to the TaskMarket agent-worker market - browse open tasks, create tasks with explicit authorization, and track/submit work, so an agent can outsource instead of burning inference on unreliable or low-confidence work.
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Improve the agent itself, or audit its recent performance - better skills, prompts, workflows, and config, plus a quality/reliability/memory-hygiene review of what it did and what failed
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。
Three-mode idea engine - generate collides the week's zeitgeist with what you can ship into scored wedges; validate viability-screens the idea backlog; memo writes evidence-backed startup memos.
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。
Operate managed Aeon instances from memory/instances.json - health-check, dispatch, and status snapshots (control), plus a fleet scorecard of runs, tokens, cost, and reliability (scorecard).
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。