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cccskills

「layers」の検索結果

415 件 ・ 関連度順

概要と使いどころ

Use the DeepGCNs PyTorch operating guide for graph convolution layers, dynamic and dilated KNN blocks, point-cloud classification or segmentation, PPI, OGB/DeeperGCN, and reversible memory-efficient GNN workflows.

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。

VectorSpaceLab/AREX-Skill3332026年9月3日 更新

Use bitsandbytes for k-bit PyTorch quantization, Hugging Face quantized model loading, 8-bit and paged optimizers, direct quantized layers/functions, and backend installation diagnostics.

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。

VectorSpaceLab/AREX-Skill3332026年9月3日 更新

Research why neural architectures and training methods work through forward computation, geometry, gradients, optimization dynamics, historical experiments, and competing explanations. Use for deep mechanism questions about neural networks, AI models, layers, representations, or training; explain the meaning in plain language with evidence and explicit limits.

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。

shareAI-lab/lab-skills3152026年9月16日 更新

Use when packaging Spring Boot 4 as an OCI image, JVM container, AOT application, or GraalVM native executable. Covers buildpacks, layers, runtime hints, probes, security, and verification.

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。

rrezartprebreza/spring-boot-skills3052026年9月21日 更新

Play board games on ShellGames.ai — Chess, Poker, Ludo, Tycoon, Memory, and Spymaster. Use when the agent wants to play games against humans or other AI agents, join tournaments, chat with players, check leaderboards, or manage a ShellGames account. Triggers on "play chess/poker/ludo/memory", "shellgames", "join game", "tournament", "play against", "board game", "tycoon", "spymaster".

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。

MemTensor/skills-vote3042026年10月1日 更新

Diagram design reference library (14 types — architecture, flowchart, sequence, state, ER, timeline, swimlane, quadrant, nested, tree, org chart, layers, venn, pyramid). In ppt-master this is consumed by the Executor when hand-authoring diagram-type SVG pages — it is NOT a standalone HTML generator here. Read for deep per-type layout conventions.

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。

byungjunjang/slide-master2862026年9月30日 更新

The only memory skill that watches on its own. No database. No vectors. No manual saves. Just an LLM observer that compresses your conversations into prioritised notes, consolidates when they grow, and recovers anything missed. Five layers of redundancy, zero maintenance. ~$0.00/month (using free-tier models). While other memory skills ask you to remember to remember, this one just pays attention.

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。

gavdalf/total-recall2752026年4月1日 更新

plan

無料

Investigate a GitHub issue and produce a structured implementation plan. Fetches issue details, explores the codebase, identifies affected layers (UI, BLoC, Repository, Client), and outputs a step-by-step plan with files to modify, testing strategy, and risk assessment. Works for bugs, features, and tasks. Invoke with /plan.

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。

divinevideo/divine-mobile2662026年10月14日 更新

holo-card

無料

Create interactive holographic cards from supplied images with colored layers, repaired scenery, signed parallax and contour glow. Use Codex native image tools with local assembly, or an explicitly selected independent API 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。

LerSent001/holo-card2602026年9月8日 更新

Generates complete modules and components from interface contracts and specifications. Use when Claude needs to build larger software components, implement interfaces, create service layers, or generate complete modules with multiple related classes. Supports Python (with type hints and protocols) and Java (with interfaces and abstract classes). Trigger when users request "implement this interface", "generate a module for", "create a service layer", "build a component that implements", or provide interface definitions that need implementation.

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。

ArabelaTso/Skills-4-SE2532026年8月21日 更新

Define production-ready visual intent for Blender scenes and standalone assets, including focal hierarchy, depth layers, visual flow, scale and repetition rhythm, camera mobility, representation fidelity, and performance budgets. Use for original or reference-guided Blender work before construction choices are executed, especially environments, architecture, products, hero assets, or scenes whose modeling quality depends on coordinated spatial design rather than isolated objects.

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。

XliuXjianX/blender-production-skills2522026年8月15日 更新

Review code changes adversarially using parallel review layers (Blind Hunter, Edge Case Hunter, Acceptance Auditor) with structured triage into actionable categories. Use when the user says "run code review" or "review this code"

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。

bmad-code-org/bmad-module-game-dev-studio2512026年9月25日 更新

Social Media Manager role skill. Orchestrates the full SMB social media workflow across three layers — Foundation (brand setup + calendar), Content Creation (captions, platform-specialist posts, visuals), and Distribution (scheduling via Blotato + performance review). Coordinates all 9 component skills as a sequential, human-reviewed pipeline. Run this skill instead of invoking component skills individually.

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。

stevenflanagan1/social-ai-team2462026年10月7日 更新

Validate at every layer data passes through to make bugs impossible. Use when invalid data causes failures deep in execution, requiring validation at multiple system layers.

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。

secondsky/claude-skills2292026年9月28日 更新

Map the big picture around a topic or software repository by identifying its boundaries, layers, actors, components, relationships, flows, history, fault lines, and open questions, then explain how the pieces fit together and where to look next. Use when a user asks to understand a whole field, domain, technology, ecosystem, industry, codebase, architecture, unfamiliar repo, or phrases such as "give me the big picture", "map the landscape", "how does this all fit together?", "help me get oriented", or "what am I missing?"

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。

tamdogood/builder-essential-skills2222026年8月17日 更新

Think and work like an expert Information Retrieval Scientist. Use when a task calls for Information Retrieval Scientist judgment. Reasons from the Probability Ranking Principle, Saracevic's relevance layers, and Cranfield pooling through tuned BM25, SPLADE/ColBERT/dense and LLM reranking, trec_eval/ir_measures with paired topic-level tests, interleaving, and nugget-based RAG evaluation while treating unjudged-as-nonrelevant pools, position-biased clicks, LLM-judge circularity, single-vector embedding limits, and benchmark contamination as first-class failure modes.

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。

K-Dense-AI/scientific-agents2052026年10月3日 更新

Think and work like an expert Computational Linguist. Use when a task calls for Computational Linguist judgment. Reasons from UD/PTB formalisms, validate.py/eval.py (LAS/MLAS/ELAS), and evalb .prm settings through Stanza/UDPipe pipelines, PropBank/FrameNet/AMR/UMR layers, IAA (κ, Krippendorff α), CONDA contamination checks, and ARR reproducibility while treating tokenizer mismatch, oracle inflation, train–test leakage, and guideline drift as first-class failure modes.

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。

K-Dense-AI/scientific-agents2052026年10月3日 更新

Think and work like an expert Applied Mathematician. Use when a task calls for Applied Mathematician judgment. Reasons from formulation-first modeling, Buckingham scaling, and asymptotics (matched expansions, boundary layers) through FEM/FVM numerics (FEniCS, PETSc, LAPACK), Tikhonov inverse problems, and ASME/Sandia V&V while treating ill-posed inversion, stiffness, and numerical diffusion as first-class failure modes.

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。

K-Dense-AI/scientific-agents2052026年10月3日 更新

Map any industry's competitive landscape using company databases, academic research, news coverage, LinkedIn activity, and job market signals. Produces industry overviews with key players, market segments, growth indicators, and emerging disruptors.

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。

sandbaseai/sandbase-skills2042026年9月26日 更新

Produce, direct, generate, QA, and integrate non-speech audio with ElevenLabs Text to Sound Effects / Sound Effects API. Use when an agent needs custom SFX, foley, ambience, loops, stingers, impacts, UI sounds, musical one-shots, trailer braams, or sound-design layers for video, ads, social edits, games, apps, podcasts, audiobooks, or interactive media using ElevenLabs.

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。

calesthio/generative-media-skills2022026年7月14日 更新

Workflow for integrating matched or partially matched omics layers into shared latent structure and cross-modal interpretation.

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。

BioTender-max/awesome-bio-agent-skills2012026年7月2日 更新

Facilitate a structured conversation to define architecture principles for a repository. Supports multiple architecture styles: clean architecture (default), hexagonal / ports & adapters, modular monolith, or custom. Produces a formal architecture document that the corresponding atom will use. Use when setting up a new project, defining architecture standards, or when the user says 'setup architecture', 'define layers', 'architecture principles', 'help me define my architecture', 'hexagonal architecture', 'modular monolith', 'ports and adapters', or 'define my architecture style'.

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。

techygarg/lattice1992026年10月10日 更新

Enforce architectural rules when generating or modifying code, and validate proposed designs before approval (design mode). Defaults to clean architecture; supports any architecture style via the architecture-refiner. Validates layer responsibilities, dependency direction, and structural constraints using the loaded architecture rules. Use when generating code, reviewing architecture, creating new files, or when the user mentions 'architecture', 'layers', 'structure', 'dependency rules', 'hexagonal architecture', 'ports and adapters', 'modular monolith', or 'onion architecture'. Also use when reviewing generated code for structural compliance.

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。

techygarg/lattice1992026年10月10日 更新

The only memory skill that watches on its own. No database. No vectors. No manual saves. Just an LLM observer that compresses your conversations into prioritised notes, consolidates when they grow, and recovers anything missed. Five layers of redundancy, zero maintenance. ~$0.00/month (using free-tier models). While other memory skills ask you to remember to remember, this one just pays attention.

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。

skillmds/skillmd1982026年10月9日 更新