markdown-viewer/archimate
Create ArchiMate enterprise architecture diagrams using PlantUML stdlib macros. Best for TOGAF viewpoints, layered EA modeling (Business/Application/Technology), motivation analysis, and migration planning.
Create ArchiMate enterprise architecture diagrams using PlantUML stdlib macros. Best for TOGAF viewpoints, layered EA modeling (Business/Application/Technology), motivation analysis, and migration planning.
npx skills add https://github.com/markdown-viewer/skills/tree/main/skills/archimateCreate ArchiMate enterprise architecture diagrams using PlantUML stdlib macros. Best for TOGAF viewpoints, layered EA modeling (Business/Application/Technology), motivation analysis, and migration planning.
This repo contains 13 individual skills — each has its own dedicated page.
Create layered system architecture diagrams using HTML/CSS templates with color-coded tiers and grid layouts. Best for technology stacks, microservices topology, and multi-tier application design.
Create business process diagrams using PlantUML syntax with BPMN, EIP, and Lean Mapping stencil icons. Best for workflow automation, approval chains, message-based integration patterns, and value stream mapping.
Create spatial diagrams with free-positioned nodes using JSON format. Best for concept maps, knowledge graphs, and planning boards requiring precise x/y coordinate control.
Create cloud provider architecture diagrams using PlantUML syntax with official AWS, Azure, GCP, and Alibaba Cloud service icons. Best for multi-service cloud topologies and migration blueprints.
Create data pipeline and analytics architecture diagrams using PlantUML syntax with database/analytics stencil icons. Best for ETL pipelines, data lakes, real-time streaming, data warehousing, and BI dashboard design.
Create directed/undirected graphs using DOT language with automatic layout. Best for dependency trees, call graphs, package hierarchies, and module relationships requiring fine-grained edge routing.
Create editorial-style information cards using HTML/CSS in Markdown. Best for knowledge summaries, data highlights, event announcements, and single-topic content cards with magazine-quality typography.
Create IoT architecture diagrams using PlantUML syntax with device and sensor stencil icons. Best for smart home, industrial IoT (IIoT), fleet management, edge computing, and sensor network layouts.
Create hierarchical mind maps using PlantUML @startmindmap syntax. Best for brainstorming, topic decomposition, study notes, and decision trees with automatic radial layout, left/right branches, and per-node styling.
Create network topology diagrams using PlantUML syntax with mxgraph device icons (Cisco, Citrix, etc.). Best for LAN/WAN layouts, datacenter interconnects, and physical/logical network design.
Create security architecture diagrams using PlantUML syntax with identity, encryption, firewall, and compliance stencil icons. Best for IAM flows, zero-trust models, encryption pipelines, and threat detection architectures.
Create UML diagrams using PlantUML syntax. Best for software modeling — Class, Sequence, Activity, State Machine, Component, Use Case, and Deployment diagrams with concise text-based notation and auto-layout.
Create data-driven charts with Vega-Lite (declarative) and Vega (programmatic). Best for statistical visualization of numeric data — bar, line, scatter, heatmap, area, radar charts, and word clouds.
Automatically detect and disable irrelevant Claude Code skills per project to save tokens and streamline your tech workflow.
GitHub repository for iRyantik/buy-side-research-skills updated in the agent skills ecosystem.
🤖 Explore Python AI from machine learning basics to advanced models with hands-on tutorials and practical examples for all skill levels.
The validation layer for solo founders. Research, strategy, and validation on Claude Code - decide before you build. 3 agents, 29 skills. MIT.
Automate experimental code changes with Claude Code by running goal-driven loops that test, measure, and optimize code continuously without extra servers.
Full-stack hackathon prototype for a Grab-style A-Player Identification Tool. The app turns high-volume candidate vetting into an auditable agent workflow with mock data, local state, vector-memory retrieval, and optional OpenAI reasoning.