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概要と使いどころ
Asesor experto en litigación bajo sistemas de derecho civil (civil law) en América Latina. Asiste a abogados litigantes, equipos legales internos y clientes directos con estrategia procesal, análisis de riesgos, opciones tácticas, plazos y orientación sobre el proceso civil en múltiples jurisdicciones. Al final de cada sesión redacta un correo electrónico claro que resume los hallazgos para el cliente.
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。
Depth assessment of whether an AI system is high-risk under Art. 6 of the EU AI Act, grounded in the Commission's draft Art. 6(5) classification guidelines (general principles + Annex I + Annex III). Covers the Annex I product-safety route, all eight Annex III areas with worked examples, the Art. 6(3) exception and its profiling re-exception, and the Art. 25 quasi-provider trap. Outputs a structured decision block, a practitioner memo, and a JSON interchange artefact.
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。
Ricerca giurisprudenziale rapida per ottenere un quadro di orientamento iniziale su un tema giuridico. Si attiva con "giurisprudenza-lampo [tema]", "cerca giurisprudenza su [tema]", "sentenze su [tema]", "pronunce su [tema]", "orientamento giurisprudenziale su [tema]", o qualsiasi variante che chieda di cercare sentenze, pronunce, massime, orientamenti giurisprudenziali o precedenti su un argomento giuridico. Usa questa skill anche quando l'utente dice "cosa dice la giurisprudenza su", "ci sono sentenze su", "precedenti su", "come si è espressa la Cassazione/il TAR/il Consiglio di Stato su".
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 GDPR compliance assistant covering all four core workflows: (1) auditing code and systems for GDPR violations, (2) drafting GDPR-compliant documents such as privacy policies, Data Processing Agreements (DPAs), and consent notices, (3) answering GDPR compliance questions with authoritative article citations, and (4) reviewing data flows and PII handling practices. Use this skill whenever the user mentions GDPR, data protection, privacy compliance, lawful basis, data subject rights, DPA, privacy notices, consent management, data breaches, DPIAs, controller/ processor relationships, cross-border data transfers, or any EU/UK data privacy topic. Also trigger for questions like "is this GDPR compliant?", "how do I handle personal data?", "what does a privacy policy need?", or any request involving PII, personal data, or data retention in a regulatory context.
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。
Audits AI-assisted legal, compliance, governance, and institutional decisions before reliance to determine whether the responsible human or institution has enough access to the evidence, reasoning basis, uncertainty, authority, and review path to genuinely own the decision rather than merely approve, sign, or transmit it.
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。
Structure a student's self-determined project with mentoring checkpoints, competency alignment, and reflection. Use when guiding student-led projects within a competency-based framework.
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。
Design learning tasks built on Ubuntu philosophy emphasising collective knowledge-building and mutual responsibility. Use when fostering collaboration that values community over individual competition.
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 Godot shader patterns for batch-safe hitflash, alpha-scissor foliage/dissolve, screenspace postFX, depth reconstruction, triplanar, and instance uniforms — not first-shader tutorials. Trigger on draw-call batching breaks, discard vs depth-prepass, foliage shadows, post-process quads, or world-position FX. Keywords: instance uniform, ALPHA_SCISSOR, hint_screen_texture, hint_depth_texture, global uniform, sampler2DArray, canvas_item, spatial, post-processing.
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 hierarchical finite state machines (HSM) and pushdown automata for complex AI/character behaviors. Covers state stacks, sub-states, transition validation, and state context passing. Use when basic FSMs are insufficient OR implementing layered AI. Keywords state machine, HSM, hierarchical, pushdown automata, state stack, FSM, AI behavior.
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 Godot shader patterns for batch-safe hitflash, alpha-scissor foliage/dissolve, screenspace postFX, depth reconstruction, triplanar, and instance uniforms — not first-shader tutorials. Trigger on draw-call batching breaks, discard vs depth-prepass, foliage shadows, post-process quads, or world-position FX. Keywords: instance uniform, ALPHA_SCISSOR, hint_screen_texture, hint_depth_texture, global uniform, sampler2DArray, canvas_item, spatial, post-processing.
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 hierarchical finite state machines (HSM) and pushdown automata for complex AI/character behaviors. Covers state stacks, sub-states, transition validation, and state context passing. Use when basic FSMs are insufficient OR implementing layered AI. Keywords state machine, HSM, hierarchical, pushdown automata, state stack, FSM, AI behavior.
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。
Use when implementing shaders — Godot shader language, visual shaders, common visual recipes, and post-processing effects
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。
Use when cutting a GodotPrompter release or bumping its version — the version-bump sequence, tag-triggered workflow, and the marketplace manifests that must follow.
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。
Use when implementing tweens — property animation, method tweening, chaining, parallel sequences, easing, and common UI/gameplay motion recipes
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。
Use when implementing multiplayer — MultiplayerAPI, ENet/WebSocket peers, RPCs, and authority model
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。
Visual specialist for full audits. Captures screenshots, evaluates above-the-fold signals, and checks mobile rendering basics.
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。
When the user wants to create competitor comparison or alternative pages for SEO and sales enablement. Also use when the user mentions 'alternative page,' 'vs page,' 'competitor comparison,' 'comparison page,' '[Product] vs [Product],' '[Product] alternative,' or 'competitive landing pages.' Covers four formats: singular alternative, plural alternatives, you vs competitor, and competitor vs competitor. Emphasizes deep research, modular content architecture, and varied section types beyond feature tables.
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。
When the user wants to apply psychological principles, mental models, or behavioral science to marketing. Also use when the user mentions 'psychology,' 'mental models,' 'cognitive bias,' 'persuasion,' 'behavioral science,' 'why people buy,' 'decision-making,' or 'consumer behavior.' This skill provides 70+ mental models organized for marketing application.
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。
Summarize small CSV files and identify the highest revenue month.
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。
'treeio' is an R package to make it easier to import and store phylogenetic tree with associated data; and to link external data from different sources to phylogeny. It also supports exporting phylogenetic tree with heterogeneous associated
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 package comprises a set of pretrained machine learning models to predict basic immune cell types. This enables all users to quickly get a first annotation of the cell types present in their dataset without requiring prior knowledge. scAnnotatR also allows users to train their own models to predict new cell types based on specific research needs.
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。
sechm provides a simple interface between SummarizedExperiment objects and the ComplexHeatmap package. It enables plotting annotated heatmaps from SE objects, with easy access to rowData and colData columns, and implements a number of features to make the generation of heatmaps easier and more flexible. These functionalities used to be part of the SEtools package.
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。
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
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。