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fireworks-tech-graph

Stop drawing diagrams by hand. Describe your system in English or Chinese — get publication-ready SVG + PNG technical diagrams in seconds.

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Overview

fireworks-tech-graph turns natural language descriptions into polished SVG diagrams, then exports them as high-resolution PNG via cairosvg (recommended), with rsvg-convert and puppeteer available as alternatives. It ships with 7 template styles and 1 AI-authored style (Dark Luxury) and deep knowledge of AI/Agent domain patterns (RAG, Agentic Search, Mem0, Multi-Agent, Tool Call flows), plus full support for all 14 UML diagram types.

User: "Generate a Mem0 memory architecture diagram, dark style"
  → Skill classifies: Memory Architecture Diagram, Style 2
  → Generates SVG with swim lanes, cylinders, semantic arrows
  → Exports 1920px PNG
  → Reports: mem0-architecture.svg / mem0-architecture.png

Work With the Builder

This project is also a proof surface for a broader capability: turning vague AI/devtool workflows into constrained, reusable systems with validation, documentation, export paths, and product-facing polish.

If you are building agent infrastructure, AI IDEs, internal copilots, developer tools, technical documentation systems, or applied AI workflow products, I am open to scoped paid sprints, design-partner work, and founding engineer conversations.

• Founder-facing profile: https://bradzhang.dev/en
• Commercial case study: https://bradzhang.dev/en/case-studies/fireworks-tech-graph
• Work with me: https://bradzhang.dev/en/work-with-me

Showcase

All samples exported at 1920px width (2× retina) via cairosvg. PNG is lossless and the right choice for technical diagrams — sharp edges, no JPEG compression artifacts on text/lines.

Style 1 — Flat Icon (default)

Mem0 Memory Architecture — white background, semantic arrows, layered memory system

Style 2 — Dark Terminal

Tool Call Flow — dark background, neon accents, monospace font

Style 3 — Blueprint

Microservices Architecture — deep blue background, grid lines, cyan strokes

Style 4 — Notion Clean

Agent Memory Types — minimal white, single accent color

Style 5 — Glassmorphism

Multi-Agent Collaboration — dark gradient background, frosted glass cards

Style 6 — Claude Official

System Architecture — warm cream background (#f8f6f3), Anthropic brand colors, clean professional aesthetic

Style 7 — OpenAI Official

API Integration Flow — pure white background, OpenAI brand palette, modern minimalist design

Style 8 — Dark Luxury (AI-authored)

Sopify Adaptive Workflow Engine — deep black background, champagne gold accents, serif titles, six-bucket color wheel

Stable Prompt Recipes

Use prompts like these when you want the model to stay close to the repo's strongest regression-tested outputs:

Style 1 — Flat Icon

Draw a Mem0 memory architecture diagram in style 1 (Flat Icon).
Use four horizontal sections: Input Layer, Memory Manager, Storage Layer, Output / Retrieval.
Include User, AI App / Agent, LLM, mem0 Client, Memory Manager, Vector Store, Graph DB, Key-Value Store, History Store, Context Builder, Ranked Results, Personalized Response.
Use semantic arrows for read, write, control, and data flow. Keep the layout clean and product-doc friendly.

Style 2 — Dark Terminal

Draw a tool call flow diagram in style 2 (Dark Terminal).
Show User query, Retrieve chunks, Generate answer, Knowledge base, Agent, Terminal, Source documents, and Grounded answer.
Use terminal chrome, neon accents, monospace typography, and semantic arrows for retrieval, synthesis, and embedding update.

Style 3 — Blueprint

Draw a microservices architecture diagram in style 3 (Blueprint).
Create numbered engineering sections like 01 // EDGE, 02 // APPLICATION SERVICES, 03 // DATA + EVENT INFRA, 04 // OBSERVABILITY.
Include Client Apps, API Gateway, Auth / Policy, three services, Event Router, Postgres, Redis Cache, Warehouse, and Metrics / Traces.
Use blueprint grid, cyan strokes, and a bottom-right title block.

Style 4 — Notion Clean

Draw an agent memory types diagram in style 4 (Notion Clean).
Compare Sensory Memory, Working Memory, Episodic Memory, Semantic Memory, and Procedural Memory around a central Agent core.
Use a minimal white layout, neutral borders, one accent color for arrows, and short storage tags for each memory type.

Style 5 — Glassmorphism

Draw a multi-agent collaboration diagram in style 5 (Glassmorphism).
Use three sections: Mission Control, Specialist Agents, and Synthesis.
Include User brief, Coordinator Agent, Research Agent, Coding Agent, Review Agent, Shared Memory, Synthesis Engine, and Final response.
Use frosted cards, soft glow, and semantic arrows for delegation, shared memory writes, and synthesis output.

Style 6 — Claude Official

Draw a system architecture diagram in style 6 (Claude Official).
Use left-side layer labels: Interface Layer, Core Layer, Foundation Layer.
Include Client Surface, Gateway, Task Planner, Model Runtime, Policy Guardrails, Memory Store, Tool Runtime, Observability, and Registry.
Use warm cream background, restrained brand-like palette, generous whitespace, and a bottom-right legend.

Style 7 — OpenAI Official

Draw an API integration flow diagram in style 7 (OpenAI Official).
Use three sections: Entry, Model + Tools, and Delivery.
Include Application, OpenAI SDK Layer, Prompt Builder, Model Runtime, Tool Calls, Response Formatter, Observability, and Release Control.
Keep the look minimal, white, precise, and modern with clean green-accented arrows.

Style 8 — Dark Luxury (AI-authored)

Style 8 is not a template-driven style. The AI reads references/style-8-dark-luxury.md and hand-crafts the SVG directly.

Draw a system architecture diagram in style 8 (Dark Luxury).
Use a deep black background (#0a0a0a), champagne gold (#d4a574) for titles and cluster labels,
and spread node colors across the full color wheel: emerald, violet, sky blue, rose, amber, cool-gray.
Apply Georgia serif only for the main title and section labels (≥11px); use sans-serif for all node text and arrow labels.

Features

• 8 visual styles — 7 template-driven (Flat Icon to OpenAI Official) + 1 AI-authored (Dark Luxury)
• Executable style system — style guides are encoded into the generator, not only documented in markdown
• 14 diagram types — Full UML support (Class, Component, Deployment, Package, Composite Structure, Object, Use Case, Activity, State Machine, Sequence, Communication, Timing, Interaction Overview, ER Diagram) plus AI/Agent domain diagrams
• AI/Agent domain patterns — RAG, Agentic Search, Mem0, Multi-Agent, Tool Call, and more built-in
• Semantic shape vocabulary — LLM = double-border rect, Agent = hexagon, Vector Store = ringed cylinder
• Semantic arrow system — color + dash pattern encode meaning (write vs read vs async vs loop)
• Product icons — 40+ products with brand colors: OpenAI, Anthropic, Pinecone, Weaviate, Kafka, PostgreSQL…
• Swim lane grouping — automatic layer labeling for complex architectures
• SVG + PNG output — SVG for editing, 1920px PNG for embedding
• Renderer-friendly — pure inline SVG, no external font fetching; renders cleanly in cairosvg, rsvg-convert, and headless Chrome

Installation

[!WARNING] npx skills add (v1.5.15) only copies SKILL.md — subdirectories like references/, scripts/, templates/ are silently dropped. Use git clone for a complete installation.

git clone https://github.com/yizhiyanhua-ai/fireworks-tech-graph.git ~/.claude/skills/fireworks-tech-graph

Or use npx skills add (subdirectories may be missing):

npx skills add yizhiyanhua-ai/fireworks-tech-graph

This skill is installed from the GitHub repository. The npm package page is the public package/distribution page:

https://www.npmjs.com/package/@yizhiyanhua-ai/fireworks-tech-graph

Do not use the npm package name with skills add, because the CLI resolves install sources as GitHub/local paths.

Update

cd ~/.claude/skills/fireworks-tech-graph && git pull

Or re-run the CLI installer:

npx skills add yizhiyanhua-ai/fireworks-tech-graph --force -g -y

Requirements

Pick one PNG renderer (cairosvg recommended):

# Recommended: cairosvg (best CSS support)
pip install cairosvg

# Fallback: rsvg-convert (system package; may drop CSS / <foreignObject>)
brew install librsvg                   # macOS
sudo apt install librsvg2-bin          # Ubuntu/Debian

# Highest fidelity: puppeteer (real Chromium; heavy)
npm install puppeteer

# Verify (any one is enough)
python3 -c "import cairosvg; print(cairosvg.__version__)"
rsvg-convert --version

Why Not Mermaid or draw.io?

Mermaid is great for quick inline diagrams in markdown. draw.io is great for manual polishing. fireworks-tech-graph is optimized for describing a system and getting a polished diagram immediately, without writing DSL syntax or clicking around a GUI.

Usage

Trigger phrases

The skill auto-triggers on:

generate diagram / draw diagram / create chart / visualize
architecture diagram / flowchart / sequence diagram / data flow

Basic usage

Draw a RAG pipeline flowchart

Generate an Agentic Search architecture diagram

Specify style

Draw a microservices architecture diagram, style 2 (dark terminal)

Draw a multi-agent collaboration diagram --style glassmorphism

Specify output path

Generate a Mem0 architecture diagram, output to ~/Desktop/

Create a tool call flow diagram --output /tmp/diagrams/

Example Prompts by Scenario

AI/Agent Systems

Compare Agentic RAG vs standard RAG in a feature matrix, Notion clean style

→ Comparison matrix: RAG vs Agentic RAG, covering retrieval strategy, agent loop, tool use

Generate a Mem0 memory architecture diagram with vector store, graph DB, KV store, and memory manager

→ Memory Architecture with swim lanes: Input → Memory Manager → Storage tiers → Retrieval

Draw a Multi-Agent diagram: Orchestrator dispatches 3 SubAgents (search / compute / code execution), results aggregated

→ Agent Architecture with hexagons, tool layers, and result aggregation

Visualize the Tool Call execution flow: LLM → Tool Selector → Execution → Parser → back to LLM

→ Flowchart with decision loop showing tool invocation cycle

Draw the 5 agent memory types: Sensory, Working, Episodic, Semantic, Procedural

→ Mind map or layered architecture showing memory tiers from sensory to procedural

Infrastructure & Cloud

Draw a microservices architecture: Client → API Gateway → [User Service / Order Service / Payment Service] → PostgreSQL + Redis

→ Architecture diagram with horizontal layers, swim lanes per service cluster

Generate a data pipeline diagram: Kafka → Spark processing → write to S3 → Athena query

→ Data flow diagram with labeled arrows (stream / batch / query)

Draw a Kubernetes deployment: Ingress → Service → [Pod × 3] → ConfigMap + PersistentVolume

→ Architecture with dashed containers per namespace, solid arrows for traffic flow

API & Sequence Flows

Draw an OAuth2 authorization code flow sequence diagram: User → Client → Auth Server → Resource Server

→ Sequence diagram with vertical lifelines and activation boxes

Draw the ChatGPT Plugin call sequence diagram

→ Sequence: User → ChatGPT → Plugin Manifest → API → Response chain

Decision & Process Flows

Draw a pre-launch QA flowchart for an AI app: Code Review → Security Scan → Performance Test → Manual Approval → Deploy

→ Flowchart with diamond decision nodes and parallel branches

Generate a feature comparison matrix: RAG vs Fine-tuning vs Prompt Engineering

→ Comparison matrix with checked/unchecked cells across cost, latency, accuracy, flexibility

Concept Maps

Visualize the LLM application tech stack: from foundation model to SDK to app framework to deployment

→ Layered architecture or mind map from model layer to product layer

Draw an AI Agent capability map: Perception / Memory / Reasoning / Action / Learning

→ Mind map with central "AI Agent" node and 5 radial branches

Styles

Each style has a dedicated reference file in `