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概要と使いどころ
Automated coordination, formatting, and learning from Claude Code operations using intelligent hooks with MCP integration. Includes pre/post task hooks, session management, Git integration, memory coordination, and neural pattern training for enhanced development workflows.
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AI-assisted pair programming with multiple modes (driver/navigator/switch), real-time verification, quality monitoring, and comprehensive testing. Supports TDD, debugging, refactoring, and learning sessions. Features automatic role switching, continuous code review, security scanning, and performance optimization with truth-score 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。
Quantum-resistant, self-learning version control for AI agents with ReasoningBank intelligence and multi-agent coordination
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Analyzes your recent Claude Code chat history to identify coding patterns, development gaps, and areas for improvement, curates relevant learning resources from HackerNews, and automatically sends a personalized growth report to your Slack DMs.
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 this skill when working with scientific research tools and workflows across bioinformatics, cheminformatics, genomics, structural biology, proteomics, and drug discovery. This skill provides access to 600+ scientific tools including machine learning models, datasets, APIs, and analysis packages. Use when searching for scientific tools, executing computational biology workflows, composing multi-step research pipelines, accessing databases like OpenTargets/PubChem/UniProt/PDB/ChEMBL, performing tool discovery for research tasks, or integrating scientific computational resources into LLM workflows.
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Work with state-of-the-art machine learning models for NLP, computer vision, audio, and multimodal tasks using HuggingFace Transformers. This skill should be used when fine-tuning pre-trained models, performing inference with pipelines, generating text, training sequence models, or working with BERT, GPT, T5, ViT, and other transformer architectures. Covers model loading, tokenization, training with Trainer API, text generation strategies, and task-specific patterns for classification, NER, QA, summarization, translation, and image tasks. (plugin:scientific-packages@claude-scientific-skills)
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。
Automatic architecture video editing workflow with self-learning preferences
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。
Maxim 2D cartoon explainer video — engineered for learning retention and friendly brand affinity. Uses Dual Coding Theory + Cognitive Load Reduction + Ekman Universal Emotion to make complex ideas memorable and brands feel trustworthy-approachable.
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Launch new products from idea to first customers. Use when launching products, finding early adopters, building launch week playbooks, diagnosing why adoption stalls, or learning that press coverage does not equal growth. Includes the three-layer diagnosis, the 2-week experiment cycle, and the launch that got 50K impressions and 12 signups.
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Prepare for tomorrow's meetings and tasks. Pulls calendar from Outlook via WorkIQ, cross-references open tasks and workspace context, classifies meetings, detects conflicts and day-fit issues, finds learning and deep-work slots, and generates a structured HTML prep file with productivity recommendations.
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。
Provides guidance for LLM post-training with RL using slime, a Megatron+SGLang framework. Use when training GLM models, implementing custom data generation workflows, or needing tight Megatron-LM integration for RL 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。
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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。
把公众号文章、Markdown、笔记、文档或长文本拆成适合小红书/小绿书的完整发布包。先分析全文、论证关系和模块覆盖，输出含完整逐卡文案、布局 ID、3～5 个标题建议与发布正文的确认方案；确认后生成可逐元素编辑、移动、缩放、切换整套或单卡主题、编辑发布文案并导出 1080x1440 PNG 的独立 HTML。也适用于复用已有拆分方案或 v1/v2 卡片 JSON。
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Creates step-by-step tutorials and educational content from code. Transforms complex concepts into progressive learning experiences with hands-on examples. Use PROACTIVELY for onboarding guides, feature tutorials, or concept explanations.
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You are an **expert onboarding specialist and knowledge transfer architect** with deep experience in remote-first organizations, technical team integration, and accelerated learning methodologies. Your role is to ensure smooth, comprehensive onboarding that transforms new team members into productive contributors while preserving institutional knowledge.
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Orchestrate multi-agent incident response with modern SRE practices for rapid resolution and learning:
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Expert data scientist for advanced analytics, machine learning, and statistical modeling. Handles complex data analysis, predictive modeling, and business intelligence. Use PROACTIVELY for data analysis tasks, ML modeling, statistical analysis, and data-driven insights.
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.NET unit test fundamentals and FIRST principles specialized skill. Used when creating unit tests, understanding testing basics, learning 3A Pattern, and mastering testing best practices. Covers FIRST principles, AAA Pattern, Fact/Theory, testing pyramid, etc. Keywords: unit test, unit test, unit testing, test fundamentals, testing fundamentals, FIRST principle, FIRST principle, 3A pattern, AAA pattern, Arrange Act Assert, Fact, Theory, InlineData, how to write tests, testing best practices, create unit 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。
Use when user requests research requiring multiple sources, comprehensive analysis, or synthesis across topics - technical research, domain knowledge gathering, market analysis, or learning about complex subjects
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Extract decisions, lessons, patterns, and surprises from completed phase artifacts
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Implement User and Entity Behavior Analytics using Elasticsearch/OpenSearch to build behavioral baselines, calculate anomaly scores, perform peer group analysis, and detect insider threat indicators such as data exfiltration, privilege abuse, and unauthorized access patterns.
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Detect anomalies in DNP3 (Distributed Network Protocol 3) communications used in SCADA systems by monitoring for unauthorized control commands, firmware update attempts, protocol violations, and deviations from baseline traffic patterns using deep packet inspection and machine learning approaches.
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Detects AI-generated deepfake audio used in voice phishing (vishing) attacks by extracting spectral features (MFCC, spectral centroid, spectral contrast, zero-crossing rate) and classifying samples with machine learning models. Supports batch analysis of audio files, generates confidence scores, and produces forensic reports. Activates for requests involving deepfake voice detection, vishing investigation, AI-generated speech analysis, voice cloning detection, or audio authenticity verification.
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Detects anomalous authentication patterns using UEBA analytics, statistical baselines, and machine learning models to identify impossible travel, credential stuffing, brute force, password spraying, and compromised account behaviors across authentication logs. Activates for requests involving authentication anomaly detection, login behavior analysis, UEBA implementation, or suspicious sign-in investigation.
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。