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概要と使いどころ

Write Unreal Engine 5 C++ gameplay code: the UCLASS/UPROPERTY/UFUNCTION reflection macros, the Gameplay Framework (GameMode, Pawn, Character, PlayerController, Actor components), and the module Build.cs. Use when writing or debugging UE C++, deriving from AActor/ACharacter/ AGameModeBase, exposing properties to the editor or Blueprints, or when the user mentions Unreal C++, UCLASS, GENERATED_BODY, GameMode, ACharacter, or .Build.cs.

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。

gamedev-skills/awesome-gamedev-agent-skills1,5182026年10月9日 更新

Load glTF/GLB models in three.js with GLTFLoader and play their skinned animations with AnimationMixer, including DRACO/Meshopt-compressed meshes and KTX2 textures. Use when importing 3D models into three.js — when the user mentions glTF, GLB, GLTFLoader, AnimationMixer, animation clips, DRACOLoader, or "load a 3D model". For scene/camera/renderer setup use threejs-scene-setup; for materials and lights use threejs-materials-lighting.

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。

gamedev-skills/awesome-gamedev-agent-skills1,5182026年10月9日 更新

openai

無料

Check OpenAI API access and list the models your key can use. Read-only. Trigger phrases: openai, openai models, what models do I have access to.

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。

Anil-matcha/awesome-muse-connectors1,3602026年10月14日 更新

Verify your Hugging Face account and search the model hub. Read-only. Trigger phrases: hugging face, huggingface, hf model, search models.

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。

Anil-matcha/awesome-muse-connectors1,3602026年10月14日 更新

Evaluates LLMs across 60+ academic benchmarks (MMLU, HumanEval, GSM8K, TruthfulQA, HellaSwag). Use when benchmarking model quality, comparing models, reporting academic results, or tracking training progress. Industry standard used by EleutherAI, HuggingFace, and major labs. Supports HuggingFace, vLLM, APIs.

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。

OpenRaiser/NanoResearch1,3412026年10月9日 更新

Look up vehicle data by Year, Make, and Model using the CarsXE YMM API. Use this when a user doesn't have a VIN but knows the year, make, and model of a vehicle and wants specs, trims, or features.

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。

hashgraph-online/awesome-codex-plugins1,3172026年10月14日 更新

Check safety recalls by year, make, and model (no VIN) using the CarsXE Recalls by YMM API. Use this when the user asks about recalls for a model line, or has year/make/model but no VIN.

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。

hashgraph-online/awesome-codex-plugins1,3172026年10月14日 更新

Use when preparing the data, code, and model materials for an Agricultural Systems (AgSy) manuscript. AgSy applies Elsevier's research-data policy, which treats software, code, and models as research data — deposit them in a repository and cite/link them, or state why they cannot be shared. Covers model-description standards and exemptions. Prepares the materials; it does not waive requirements.

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。

brycewang-stanford/Awesome-Journal-Skills1,2572026年9月27日 更新

Use when the model setup, equilibrium concept, or proof architecture is the bottleneck for an American Economic Journal: Microeconomics (AEJ: Micro) manuscript — the central skill for a theory-first paper. Builds the model to the AEJ: Micro bar (clean, general, well-motivated result); it does not check whether your theorem is correct.

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。

brycewang-stanford/Awesome-Journal-Skills1,2572026年9月27日 更新

Render a 'model comparison grid' video from a config — a fal-style "same prompt, N contenders" showcase — a dark real-DOM stage where per beat a monospace prompt fades in centered, docks to a small top strip, then a labeled 2-4 panel grid (static images OR muted video clips, mixable per cell) staggers in and holds for comparison, plus a minimal end card — frame-stepped via Playwright (video cells are frame-seeked deterministically) and encoded with FFmpeg. Deterministic assembly, FREE (cell media comes from create-image-fal / create-video-fal, music from create-music-elevenlabs), text stays pixel-crisp. Use for the model-comparison-grid format.

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。

gooseworks-ai/goose-skills1,2522026年10月15日 更新

Manages Power BI semantic models, including tables, columns, measures, relationships, field parameters, DAX, Import, DirectQuery and Direct Lake designs, sources, connections, permissions, refresh, and deployment. Load this skill before acting on a semantic model, unless it is part of publishing a PBIP project, which powerbi-report-cli owns. For natural-language data questions use fabriciq; for visuals use powerbi-report-cli.

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。

microsoft/skills-for-fabric1,2502026年10月5日 更新

fabriciq

無料

Answers natural-language business questions over existing Power BI reports and semantic models through the FabricIQ MCP endpoint, discovering artifacts, resolving entities, generating the DAX itself, and returning a plain-language answer. Use when the user asks a data question, including one that says to query the model directly. For DAX the user supplies, or measures to save, use semantic-model-authoring.

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。

microsoft/skills-for-fabric1,2502026年10月5日 更新

Use when you need to verify a Simulink model is compatible with SLCI code inspection, or to apply fixes for identified incompatibilities. Checks model configuration, identifies incompatibilities, and explains why each constraint is required for verification. Also invoked by slci-inspection-incompatibility-analysis to fix constraints and obtain compatibility results. Trigger keywords: checkCompatibility, SLCI compatibility, code inspection readiness, Model Advisor compatibility report.

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。

matlab/simulink-agentic-toolkit1,2272026年10月8日 更新

Common steps for building multi-layer system architecture models using System Composer. Use when implementing architecture models or when interacting with interface dictionaries, allocation sets, stereotypes, and requirements for architecture components.

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。

matlab/simulink-agentic-toolkit1,2272026年10月8日 更新

Linearize Simulink models. Use when obtaining linear time invariant or linear parameter varying models from Simulink models.

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。

matlab/simulink-agentic-toolkit1,2272026年10月8日 更新

Use when writing or editing Simscape Language (.ssc) source files — components, domains, or functions. Triggers include: model a physical component in .ssc; write physical equations for a Simscape block; add or modify physics or parameterization options in a Simscape component; build a composite component. Also use for validating .ssc syntax, fixing Simscape Language errors, or converting governing equations into working Simscape component code. Do NOT use for configuring or connecting existing Simscape blocks in a Simulink model — that is model building, not language authoring.

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。

matlab/simulink-agentic-toolkit1,2272026年10月8日 更新

Optimizes Simulink models for Embedded Coder generated code. Use when asked to optimize or improve generated code, or reduce code metrics for a Simulink model. Targets: execution time, memory footprint (RAM, ROM, stack, data copies), code size, MISRA compliance, or any semantically similar generated-code metric. Works iteratively — measures baseline, suggests changes, applies, and re-measures to confirm improvement. Triggers can be prompts similar to: optimize generated code runtime, reduce runtime, shrink code size, improve code efficiency, reduce memory usage, speed up generated code, follow MISRA compliance and so on. CAUTION: Do NOT attempt to optimize Simulink models for generated code efficiency without following this skill — the iterative measurement, gating, and rollback workflow is essential for safe optimization.

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。

matlab/simulink-agentic-toolkit1,2272026年10月8日 更新

Builds and edits Simulink, System Composer, Stateflow, and Simscape models. Use when modifying model structure, parameters, ports, connections, or Stateflow chart internals.

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。

matlab/simulink-agentic-toolkit1,2272026年10月8日 更新

Use this skill when the user asks to check Simulink model compliance against a standard (MISRA, MAB, JMAAB, ISO, DO, IEC, EN, CERT C/CWE, AUTOSAR, Simulink Code Inspector (SLCI)), wants to run Model Advisor checks, or needs a compliance report with fix suggestions. For JMAAB/MAB, supplement deterministic checks with agentic review of uncheckable guidelines.

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。

matlab/simulink-agentic-toolkit1,2272026年10月8日 更新

Tests Simulink models using either ephemeral Gherkin-based tests (model_test) for quick validation or persistent tests (Simulink Test API) authored from requirements or behavioral specs. Requires Simulink Test.

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。

matlab/simulink-agentic-toolkit1,2272026年10月8日 更新

Calls germline small variants (SNPs and indels) from Oxford Nanopore and PacBio HiFi long reads with Clair3, a two-stage (pileup + full-alignment) deep-learning caller, selecting the chemistry- and basecaller-version-matched model, enabling read-based phasing, and benchmarking against GIAB with stratification. Covers why the model string is the experiment (no auto-detection, silent degradation on mismatch), why ONT homopolymer/STR indels are the residual error whole-genome F1 hides, and the somatic/trio/RNA boundary to the ClairS/Clair3-Trio family. Use when calling germline SNVs/indels from ONT or HiFi BAMs, choosing a Clair3 model, phasing variants, or benchmarking long-read calls.

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。

GPTomics/bioSkills1,2232026年8月15日 更新

Predict B-cell and T-cell epitopes for vaccine antigen design and epitope mapping with BepiPred-3.0, DiscoTope-3.0, the IEDB tools, and EL-mode MHC presentation. Encodes the load-bearing asymmetry that T-cell epitope prediction is mature (it reduces to MHC presentation, AUC>0.9) while B-cell prediction is unreliable (linear predictors ~AUC 0.6 because ~90% of real epitopes are conformational) — so structure-based DiscoTope-3.0 on AlphaFold models is the only defensible B-cell path, propensity scales are obsolete, and NetChop is largely redundant on EL-trained models. Use when mapping epitopes or selecting vaccine antigens. MHC binding lives in mhc-binding-prediction.

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。

GPTomics/bioSkills1,2232026年8月15日 更新

Quantifies CRISPR editing outcomes with CRISPResso2 (Clement 2019 Nat Biotechnol) across Cas9-nuclease (indels, HDR), CBE and ABE base editors (target conversion + bystander), and prime editor (pegRNA-templated) modes. Covers single-amplicon (CRISPResso), multi-sample batch (CRISPRessoBatch), pooled-amplicon (CRISPRessoPooled), WGS off-target (CRISPRessoWGS), and sample-comparison (CRISPRessoCompare) workflows; quantification-window math that controls what is called edited; substitution-vs-indel diagnostic to distinguish BE from Cas9 contamination; MMEJ deletion pattern interpretation; allele-frequency tables; and failure modes from amplicon misalignment or contamination. Use when quantifying editing from amplicon sequencing, choosing CRISPResso mode by design, distinguishing intended edits from bystanders and indel byproducts, debugging low-alignment runs, or generating publication-grade editing reports.

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。

GPTomics/bioSkills1,2232026年8月15日 更新

Detect positive (diversifying / episodic / pervasive) selection using codon dN/dS frameworks. Implements PAML codeml site models (M0/M1a/M2a/M7/M8/M8a), branch models, branch-site model A (Zhang 2005), and HyPhy methods (BUSTED, BUSTED-S, BUSTED-MH, BUSTED-PH, MEME, FEL, FUBAR, aBSREL, SLAC, RELAX, GARD, FUBAR-MH). Includes McDonald-Kreitman framework (asymptotic alpha, impMKT, polyDFE, DFE-alpha, GRAPES) for within-species + divergence inference, RERconverge for trait-correlated rate shifts, CSUBST for convergent substitution, and PhyloAcc for accelerated noncoding evolution. Use when testing adaptive evolution at codons, branches, or full gene; running GARD recombination pre-screen; controlling alignment-error and gBGC false positives; reconciling PAML vs HyPhy results; or performing genome-scale selection scans.

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。

GPTomics/bioSkills1,2232026年8月15日 更新