learning & documentation向けのClaudeスキルを発見してください。86個のスキルを閲覧し、AIワークフローに最適な機能を見つけましょう。
Analyzes codebase structure and automatically generates token-lean architecture documentation in Japanese.
Quizzes you on recently read Readwise documents to enhance understanding and long-term retention through active recall.
Guides developers through the AI-Driven Development Lifecycle (AI-DLC) methodology and plugin ecosystem for AI-native software engineering.
Navigates and explores Meldoc documentation using advanced search, tree visualization, and link relationship mapping.
Identifies over 24 writing patterns that diminish scholarly quality and detects AI-generated linguistic markers in academic drafts.
Identifies optimal target journals for research papers using real-time data from OpenAlex and Crossref APIs to build data-driven submission strategies.
Develops comprehensive academic search strategies and evidence synthesis frameworks using the 5-phase VS-Research methodology.
Manages long-term research context and decision history through automated checkpoints and multi-layer persistence.
Guides researchers in establishing and justifying the philosophical foundations of their studies, ensuring alignment between ontology, epistemology, and methodology.
Transforms AI-generated academic drafts into authentic, scholarly prose by refining language patterns while preserving technical integrity.
Transforms vague research ideas into differentiated, high-impact research questions using structured academic frameworks and typicality analysis.
Standardizes Markdown formatting and documentation structure to ensure consistent, readable, and lint-compliant content.
Standardizes project documentation through automated README structures, Architecture Decision Records (ADRs), and Keep a Changelog formatting.
Accesses comprehensive documentation and troubleshooting guides for the Quoth AI Memory plugin within Claude Code.
Implements the Diátaxis framework to structure and write high-quality technical documentation across four distinct quadrants.
Standardizes the creation and maintenance of human-readable changelogs following professional software documentation best practices.
Synchronizes project documentation with codebase changes to maintain accurate READMEs, API specs, and technical guides.
Generates agent-optimized changelogs to help AI coding assistants understand architectural evolution and avoid deprecated patterns.
Provides expert Nablarch 5 framework guidance and automated code analysis based on curated knowledge bases.
Traces the historical evolution of architectural decisions and code patterns to prevent repeating past failures and rediscover lost solutions.
Analyzes your coding sessions to identify skill gaps, provide personalized growth reports, and deliver curated learning resources via Slack.
Analyzes the evolution of technical decisions and historical context to prevent repeating past mistakes and rediscover proven solutions.
Structures winning hackathon presentations and demo scripts designed for maximum judge impact.
Analyzes your coding history to identify skill gaps and provides curated learning resources via Slack.
Provides a standardized framework for building, testing, and packaging specialized Claude Code skills with domain expertise and tool integrations.
Automates Learning Management System tasks in D2L Brightspace using Rube MCP and Composio integrations.
Automates Google Classroom administrative tasks, assignment management, and student communication via the Rube MCP server.
Applies Test-Driven Development principles to process documentation to ensure Claude instances discover and follow proven technical patterns.
Applies Test-Driven Development principles to documentation and skills to ensure reliable AI agent compliance.
Automates word lookups, definitions, and linguistic data retrieval using the Rube MCP and Composio integration.
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