Generate a clean morning brief in Claude Code — pulls today's priorities, unposted content, and weather from your vault.
Skills（SKILL.md）は、AIエージェント（Claude Code、Cursor、Codexなど）に特定の能力を追加するための設定ファイルです。
詳しく見る →Generate a clean morning brief in Claude Code — pulls today's priorities, unposted content, and weather from your vault.
Remove AI-generated jargon and restore human voice to text. Built from analyzing 1,000+ AI vs human content pieces.
Generate a meeting prep brief from your Obsidian vault. Researches participants, surfaces vault history, builds a prioritized agenda, and generates sharp questions. No autonomy — you run it, you get y
Industry-adaptive B2B newsletter creation with stage, role, and geography-aware workflows
Generate an energy-optimized, time-blocked daily plan based on circadian rhythm research and GTD principles
Regenerate the AGENTS.md file with a compressed documentation index.
基于佛教经典文献，生成特定高僧大德的 AI 教学角色
> 本内容依据历史佛教文献生成，仅供学习参考。对比旨在展现多元视角，不评判优劣。
> 本内容依据历史佛教文献生成，仅供学习参考。所有教义断言附 CBETA 经证。如需正式修行指导，请亲近善知识。
> 本内容依据历史佛教文献生成，仅供学习参考。所有教义断言附 CBETA 经证。如需正式修行指导，请亲近善知识。
> 本内容依据历史佛教文献生成，仅供学习参考。所有教义断言附 CBETA 经证。如需正式修行指导，请亲近善知识。
> 本内容依据历史佛教文献生成，仅供学习参考。所有教义断言附 CBETA 经证。如需正式修行指导，请亲近善知识。
> 本内容依据历史佛教文献生成，仅供学习参考。所有教义断言附 CBETA 经证。如需正式修行指导，请亲近善知识。
> 本内容依据历史佛教文献生成，仅供学习参考。所有教义断言附 CBETA 经证。如需正式修行指导，请亲近善知识。
> 本内容依据历史佛教文献生成，仅供学习参考。所有教义断言附 CBETA 经证。如需正式修行指导，请亲近善知识。
> 本内容依据历史佛教文献生成，仅供学习参考。所有教义断言附 CBETA 经证。如需正式修行指导，请亲近善知识。
OpenClaw documentation expert with decision tree navigation, search scripts, doc fetching, version tracking, and config snippets for all OpenClaw features
Generate beautifully designed PDF reports with a Nordic/Scandinavian aesthetic. Use when creating polished executive briefings, analysis reports, or presentation-style PDF outputs from markdown and HTML via Nutrient DWS.
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Generate a concise list of REST API endpoints inferred from file names or project structures. Output is intentionally minimal: one line per endpoint — the method + path + a single-sentence description
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Generate complete, copy-paste-ready CI/CD pipeline configs that install Newman and run Postman collections as part of automated builds.
Generate complete, ready-to-run Newman CLI commands tailored to the user's collection, environment, and reporting needs.
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BOM data lives in **KiCad schematic symbol properties** as the single source of truth. This skill orchestrates the full lifecycle: analyze the schematic, search distributors, validate parts, write pro
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Type Thought-template (instantiate before use) - Trigger Pattern Always (Aptos Move) -- ConstructorRef/TransferRef/MintRef/BurnRef lifecycle
Type Thought-template (instantiate before use) - Research basis Donation attacks via unsolicited token transfers
Provides chunking strategies for RAG systems. Generates chunk size recommendations (256-1024 tokens), overlap percentages (10-20%), and semantic boundary detection methods. Validates semantic coherence and evaluates retrieval precision/recall metrics. Use when building retrieval-augmented generation systems, vector databases, or processing large documents.
Provides AWS CloudFormation patterns for Auto Scaling including EC2, ECS, and Lambda. Use when creating Auto Scaling groups, launch configurations, launch templates, scaling policies, lifecycle hooks, and predictive scaling. Covers template structure with Parameters, Outputs, Mappings, Conditions, cross-stack references, and best practices for high availability and cost optimization.
Provides AWS CloudFormation patterns for Amazon Bedrock resources including agents, knowledge bases, data sources, guardrails, prompts, flows, and inference profiles. Use when creating Bedrock agents with action groups, implementing RAG with knowledge bases, configuring vector stores, setting up content moderation guardrails, managing prompts, orchestrating workflows with flows, and configuring inference profiles for model optimization.
Provides AWS CloudFormation patterns for CloudFront distributions, origins (ALB, S3, Lambda@Edge, VPC Origins), CacheBehaviors, Functions, SecurityHeaders, parameters, Outputs and cross-stack references. Use when creating CloudFront distributions with CloudFormation, configuring multiple origins, implementing caching strategies, managing custom domains with ACM, configuring WAF, and optimizing performance.
Provides AWS CloudFormation patterns for CloudWatch monitoring, metrics, alarms, dashboards, logs, and observability. Use when creating CloudWatch metrics, alarms, dashboards, log groups, log subscriptions, anomaly detection, synthesized canaries, Application Signals, and implementing template structure with Parameters, Outputs, Mappings, Conditions, cross-stack references, and CloudWatch best practices for monitoring production infrastructure.
Provides AWS CloudFormation patterns for DynamoDB tables, GSIs, LSIs, auto-scaling, and streams. Use when creating DynamoDB tables with CloudFormation, configuring primary keys, local/global secondary indexes, capacity modes (on-demand/provisioned), point-in-time recovery, encryption, TTL, and implementing template structure with Parameters, Outputs, Mappings, Conditions, cross-stack references.
Provides AWS CloudFormation patterns for EC2 instances, Security Groups, IAM roles, and load balancers. Use when creating EC2 instances, SPOT instances, Security Groups, IAM roles for EC2, Application Load Balancers (ALB), Target Groups, and implementing template structure with Parameters, Outputs, Mappings, Conditions, and cross-stack references.
Provides AWS CloudFormation patterns for ECS clusters, task definitions, services, container definitions, auto scaling, blue/green deployments, CodeDeploy integration, ALB integration, service discovery, monitoring, logging, template structure, parameters, outputs, and cross-stack references. Use when creating ECS clusters with CloudFormation, configuring Fargate and EC2 launch types, implementing blue/green deployments, managing auto scaling, integrating with ALB and NLB, and implementing ECS best practices.
Provides AWS CloudFormation patterns for ElastiCache Redis or Memcached infrastructure, including subnet groups, parameter groups, security controls, and cross-stack outputs. Use when designing cache tiers, high-availability replication groups, encryption settings, or reusable CloudFormation templates for application caching.
Provides AWS CloudFormation patterns for IAM roles, policies, managed policies, permission boundaries, and trust relationships. Use when modeling least-privilege access, cross-account assumptions, service roles, or reusable IAM stacks that other CloudFormation templates consume.
Provides AWS CloudFormation patterns for Lambda functions, layers, API Gateway integration, event sources, cold start optimization, monitoring, logging, template validation, and deployment workflows. Use when creating Lambda functions with CloudFormation, configuring event sources, implementing cold start optimization, managing layers, integrating with API Gateway, and deploying Lambda infrastructure.
Provides AWS CloudFormation patterns for Amazon RDS databases. Use when creating RDS instances (MySQL, PostgreSQL, Aurora), DB clusters, multi-AZ deployments, parameter groups, subnet groups, and implementing template structure with Parameters, Outputs, Mappings, Conditions, and cross-stack references.
Provides AWS CloudFormation patterns for Amazon S3. Use when creating S3 buckets, policies, versioning, lifecycle rules, and implementing template structure with Parameters, Outputs, Mappings, Conditions, and cross-stack references.
Provides AWS CloudFormation patterns for security infrastructure including KMS encryption, Secrets Manager, IAM security, VPC security, ACM certificates, parameter security, outputs, and secure cross-stack references. Use when implementing security best practices, encrypting data, managing secrets, applying least privilege IAM policies, securing VPC configurations, managing TLS/SSL certificates, and implementing defense in depth strategies.
Creates professional AWS architecture diagrams in draw.io XML format (.drawio files) using official AWS Architecture Icons (aws4 library). Use when the user asks for AWS diagrams, VPC layouts, multi-tier architectures, serverless designs, network topology, or draw.io exports involving Lambda, EC2, RDS, or other AWS services.
Creates new Architecture Decision Record (ADR) documents for significant architectural changes using a consistent template and repository-aware naming and storage guidance. Use when a user or agent decides on an architectural change, needs to document technical rationale, or wants to add a new ADR to the project history.
Autonomously analyzes a project's codebase to discover development patterns, conventions, and architectural decisions, then generates project rule files in `.claude/rules/` for Claude Code to follow.
Provides patterns to build declarative AI Services with LangChain4j for LLM integration, chatbot development, AI agent implementation, and conversational AI in Java. Generates type-safe AI services using interface-based patterns, annotations, memory management, and tools integration. Use when creating AI-powered Java applications with minimal boilerplate, implementing conversational AI with memory, or building AI agents with function calling.
Provides Retrieval-Augmented Generation (RAG) implementation patterns with LangChain4j for Java. Generates document ingestion pipelines, embedding stores, vector search, and semantic search capabilities. Use when building chat-with-documents systems, document Q&A over PDFs or text files, AI assistants with knowledge bases, semantic search over document repositories, or knowledge-enhanced AI applications with source attribution.
Provides Spring Boot MCP server patterns that create Model Context Protocol servers with Spring AI by defining tool handlers, exposing resources, configuring prompt templates, and setting up transports for AI function calling and tool calling. Use when building MCP servers to extend AI capabilities with Spring's official AI framework, implementing AI tools, custom function calling, or MCP client integration.
Provides and generates complete CRUD workflows for Spring Boot 3 services. Creates feature-focused architecture with Spring Data JPA aggregates, repositories, DTOs, controllers, and REST APIs. Validates domain invariants and transaction boundaries. Use when modeling Java backend services, REST API endpoints, database operations, web service patterns, or JPA entities for Spring Boot applications.