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概要と使いどころ
Build and verify Command palette trigger for Documentation and knowledge with Bootstrap v5.3 using a working semantic implementation, responsive RTL/LTR behavior, theme tokens, test plan and design 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。
Build and verify Theme preference switch for Documentation and knowledge with Bootstrap v5.3 using a working semantic implementation, responsive RTL/LTR behavior, theme tokens, test plan and design 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。
Build and verify Expandable filter section for Documentation and knowledge with Bootstrap v5.3 using a working semantic implementation, responsive RTL/LTR behavior, theme tokens, test plan and design 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。
Build and verify Analytics visualization shell for Documentation and knowledge with Bootstrap v5.3 using a working semantic implementation, responsive RTL/LTR behavior, theme tokens, test plan and design 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。
Build and verify Recent activity feed for Documentation and knowledge with Bootstrap v5.3 using a working semantic implementation, responsive RTL/LTR behavior, theme tokens, test plan and design 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。
Build and verify Chart with table fallback for Documentation and knowledge with Bootstrap v5.3 using a working semantic implementation, responsive RTL/LTR behavior, theme tokens, test plan and design 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。
Build and verify Live example and code for Documentation and knowledge with Bootstrap v5.3 using a working semantic implementation, responsive RTL/LTR behavior, theme tokens, test plan and design 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。
Build and verify Adaptive calendar shell for Documentation and knowledge with Bootstrap v5.3 using a working semantic implementation, responsive RTL/LTR behavior, theme tokens, test plan and design 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。
Build and verify Structured breadcrumbs for Documentation and knowledge with Bootstrap v5.3 using a working semantic implementation, responsive RTL/LTR behavior, theme tokens, test plan and design 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。
Build and verify Bento feature grid for Documentation and knowledge with Bootstrap v5.3 using a working semantic implementation, responsive RTL/LTR behavior, theme tokens, test plan and design 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。
Build and verify Audio controls area for Documentation and knowledge with Bootstrap v5.3 using a working semantic implementation, responsive RTL/LTR behavior, theme tokens, test plan and design 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。
Build and verify Accessible checkout form for Documentation and knowledge with Bootstrap v5.3 using a working semantic implementation, responsive RTL/LTR behavior, theme tokens, test plan and design 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。
Build and verify Article teaser for Documentation and knowledge with Bootstrap v5.3 using a working semantic implementation, responsive RTL/LTR behavior, theme tokens, test plan and design 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。
Build and verify Frequently asked questions for Documentation and knowledge with Bootstrap v5.3 using a working semantic implementation, responsive RTL/LTR behavior, theme tokens, test plan and design 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。
Build and verify Three.js product viewer shell for Documentation and knowledge with Bootstrap v5.3 using a working semantic implementation, responsive RTL/LTR behavior, theme tokens, test plan and design 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。
OpenCTI is an open-source platform for managing cyber threat intelligence knowledge, built on STIX 2.1 as its native data model. This skill covers building an automated IOC enrichment pipeline using O
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。
MITRE ATT&CK is a globally-accessible knowledge base of adversary tactics, techniques, and procedures (TTPs) based on real-world observations. This skill covers systematically mapping threat actor beh
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。
Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Claude's capabilities with specialized knowledge, workflows, or tool integrations.
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。
Automated documentation generation, API documentation, code comments, README templates, and knowledge base maintenance. Use when creating documentation, updating READMEs, generating API docs, or maintaining project documentation.
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。
Rebuild the DSH node's persistent knowledge state. Runs register-claude.py to (re)create the dome.db schema and upsert agents/skills/tools/stack rows, then runs ingest.py to re-index kb/, logs/, docs, and agent core source into ChromaDB's dome-kb collection, then runs pre-spore-verify.py to confirm all 7 skill modules load and the akashic write+query roundtrip works. Idempotent — safe to run any time.
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。
Knowledge and utilities for creating animated GIFs optimized for Slack. Provides constraints, validation tools, and animation concepts. Use when users request animated GIFs for Slack like "make me a GIF of X doing Y for Slack."
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。
Automatically persist useful context — research, decisions, learnings, templates — to workspace files so knowledge survives across conversations.
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。
PyTorch-native graph neural networks for molecules and proteins. Use when building custom GNN architectures for drug discovery, protein modeling, or knowledge graph reasoning. Best for custom model development, protein property prediction, retrosynthesis. For pre-trained models and diverse featurizers use deepchem; for benchmark datasets use pytdc.
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 3D conformer ensembles using RDKit ETKDGv3 with knowledge-enhanced distance geometry, MMFF94/UFF force-field optimization, CREST + GFN2-xTB semi-empirical refinement, and macrocycle-aware torsion preferences. Provides explicit decision rules for single vs ensemble conformer use, RMSD pruning, energy windows, conformer count, and force-field choice. Use when preparing 3D ligands for docking, generating descriptor input for 3D QSAR, or sampling macrocycle/peptide conformational ensembles.
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。