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。
Standardizes the creation and optimization of Claude Code skills using a Test-Driven Development approach to ensure agent compliance.
Optimizes documentation, skills, and prompt structures to enhance AI assistant performance and token efficiency.
Synchronizes Next.js MDX documentation with recent code changes through automated impact analysis and guided updates.
Validates the structural integrity and formatting of Japanese language learning cards to ensure consistent data quality.
Standardizes Python research project documentation to ensure reproducibility and clarity for contributors.
Translates informal user stories and requirements into precise, testable EARS format for clear and unambiguous system specifications.
Audits and scores Anthropic Cookbook notebooks against standardized style guides and technical rubrics.
Automates the generation of terminal recordings and documentation galleries for Bazzite AI command lifecycles.
Automates terminal recording sessions using asciinema to create high-quality documentation, demos, and tutorial content.
Accelerates codebase onboarding by identifying project types, frameworks, and architectural patterns.
Audits and optimizes CLAUDE.md files to provide Claude Code with superior project context and actionable workflows.
Queries built-in macOS dictionaries to provide instant definitions, readings, and translations for Japanese, Chinese, and English terms.
Evaluates the linguistic and pragmatic depth of Japanese vocabulary cards to identify necessary learning extensions.
Queries native macOS dictionaries to provide precise Japanese, Chinese, and English definitions and translations.
Ensures accurate API implementation by verifying method signatures and patterns against official documentation before writing code.
Automatically synchronizes and updates CLAUDE.md project documentation based on real-time code changes.
Generates structured, blameless root cause analysis documentation to facilitate team learning and prevent incident recurrence.
Generates evidence-based feedback templates for Canvas LMS assignments using the Four Learning Design Pillars framework.
Guides developers through professional requirement clarification and scope definition during live coding interviews.
Guides users through a complete OpenSpec workflow cycle using interactive narration and real-world codebase tasks.
Guides users through a structured three-stage workflow for collaborative documentation creation, covering context gathering, iterative drafting, and reader testing.
Generates concise, technical README documentation specifically designed for experienced engineers.
Enforces a concise, fluff-free writing style for technical README documentation aimed at experienced engineers.
Masters the command line through AI-assisted mnemonics, visual mental models, and interactive practice exercises.
Demonstrates the marketplace plugin system and validates skill loading within the yw-visualizer ecosystem.
Transforms complex information into interactive diagrams and visual knowledge maps automatically.
Automates the creation and management of Architecture Decision Records (ADRs) to maintain project history and technical rationale.
Provides comprehensive guidance, command documentation, and architectural rationale for the Craft-Coder pair programming plugin.
Automates the creation and organization of structured background documentation for academic research and literature reviews.
Generates high-quality technical documentation including READMEs, API references, tutorials, and architecture decision records.
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