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Turn research pipelines and system architectures into editable PowerPoint, TikZ, Mermaid, and SVG diagrams from one structured specification.
Free
research diagram architect
Example session with this skill installed
Create an academic diagram illustrating a Hybrid RAG architecture.
Separate the workflow into two phases
- Offline Indexing: Raw Documents → Chunking → Embedding Model → Vector Database.
- Online Retrieval: User Query → Query Embedding → Top-K Retrieval → Context Assembly → LLM → Final Answer.
Connect the Vector Database to Top-K Retrieval with a dashed reference arrow.
Use the academic minimalist theme, emphasize key components, and export editable PowerPoint, TikZ, Mermaid, and SVG files.
Validate the diagram for node collisions and text overflow.
- Read your context and instructions
- Compiled the research diagram architect
Hybrid RAG Architecture — Generated Diagram
Created a structured Hybrid Retrieval-Augmented Generation diagram from a single semantic specification.
Architecture
Offline Indexing
Raw Documents → Chunking → Embedding Model → Vector Database
Online Retrieval
User Query → Query Embedding → Top-K Retrieval → Context Assembly → LLM Generation → Final Answer
A dashed connection links the Vector Database to Top-K Retrieval, representing the cross-phase similarity search operation.
Generated Outputs
PowerPoint (.pptx)
An editable technical diagram using native shapes and connectors, suitable for modifying directly in presentation software.
LaTeX TikZ (.tex)
Diagram source code for integration into research papers and LaTeX projects.
Mermaid (.mmd)
A text-based architecture diagram that can be embedded into GitHub README files or Markdown documentation.
SVG (.svg)
A scalable vector diagram for technical documentation, websites, and research presentations.
Design & Validation
The diagram uses the academic minimalist preset with neutral colors, a consistent layout, and highlighted key components.
The semantic specification defines each node and connection independently of the export format, allowing the same architecture to be reused across multiple targets.
Geometric validation checks node positioning, collisions, and estimated text overflow before delivery.
Result: One reusable architecture specification with four export formats, reducing the need to redraw the same technical figure for different purposes.
Connects securely to your tools. The creator never sees your data.
About this skill
Research Diagram Architect
One specification. Four editable diagram formats.
Research Diagram Architect helps researchers, developers, and students create structured, publication-ready technical diagrams without manually rebuilding the same figure for different platforms.
Whether you're documenting an AI pipeline, designing a system architecture, or preparing a research paper, this skill provides a reusable workflow from semantic specifications to professional diagrams.
What You Can Create
- AI & ML Pipelines: RAG systems, neural networks, retrieval workflows, and inference architectures.
- System Architectures: Cloud services, databases, APIs, and distributed systems.
- Research Workflows: Experiment pipelines, data processing, and methodology diagrams.
- Technical Documentation: Clear, structured diagrams for papers, presentations, and project documentation.
Four Output Formats
- PowerPoint (.pptx): Editable vector shapes for presentations.
- LaTeX TikZ (.tex): Diagram source code for academic papers.
- Mermaid (.mmd): Diagram code for Markdown and GitHub.
- SVG (.svg): Scalable graphics for web and documentation.
Built for Research
- Semantic nodes, containers, and connections.
- Four predefined visual themes.
- Deterministic geometry and text-overflow checks.
- Reusable specifications for consistent exports.
Getting Started
Use the skill to structure your diagram, then render it using the open-source Python package. Natural-language planning requires a configured compatible LLM provider.
Open source: https://github.com/quangnhat1504/research-diagram-architect
Build diagrams once. Refine and export them wherever your research takes you.
How to use
Skills on Agensi run inside your AI agent. Copy the prompt, paste it into your agent, and it connects to Agensi and installs this skill for you. If a payment is needed, your agent shows it to you first.
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Requires
Python