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fireworks-tech-graph

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Generate production-quality SVG+PNG technical diagrams from natural language. 7 styles, UML support, and AI/Agent workflow patterns.

Tools9.5k estrellas797 forksPythonMITActualizado 11d ago
Nota editorial

Fireworks-tech-graph is a Claude Code skill that converts natural language descriptions, in English or Chinese, into publication-ready SVG diagrams and exports them as high-resolution PNG files at 1920px width using cairosvg, with rsvg-convert and puppeteer as alternatives. The tool covers 14 diagram types across 8 visual styles, including Flat Icon, Dark Terminal, Blueprint, Glassmorphism, a Claude-branded style, and an AI-authored Dark Luxury style featuring champagne gold accents on a deep black background. It carries built-in knowledge of AI and agent architecture patterns such as RAG pipelines, Mem0 memory systems, Multi-Agent coordination, and Tool Call flows, alongside full support for all UML diagram types. Users describe their system in plain text, and the skill classifies the diagram type, selects a style, generates the SVG with appropriate layout elements like swim lanes and semantic arrows, and reports both output files. The primary audience is developers, technical writers, and AI infrastructure teams who need accurate architecture diagrams without manual drawing tools.

ClaudeWave Trust Score
100/100
Verified
Passed
  • Open-source license (MIT)
  • Actively maintained (<30d)
  • Healthy fork ratio
  • Clear description
  • Topics declared
  • Documented (README)
Last scanned: 6/11/2026
Get started
Method: Clone
Terminal
git clone https://github.com/yizhiyanhua-ai/fireworks-tech-graph
1. Clone the repository.
2. Follow the README for installation and usage instructions.
Casos de uso

Resumen de Tools

[English](README.md) | [中文](README.zh.md)

[Release history](docs/releases/README.md) · [Changelog](CHANGELOG.md)

# fireworks-tech-graph

> **Stop drawing diagrams by hand.** Describe your system in English or Chinese — get geometry-safe SVG, PNG, focused SVG-to-GIF motion, and offline interactive technical diagrams.

[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](LICENSE)
[![GitHub Release](https://img.shields.io/github/v/release/yizhiyanhua-ai/fireworks-tech-graph)](https://github.com/yizhiyanhua-ai/fireworks-tech-graph/releases)
[![Codex Skill](https://img.shields.io/badge/Codex-Skill-10a37f)](https://learn.chatgpt.com/docs/build-skills)
[![Claude Code Skill](https://img.shields.io/badge/Claude%20Code-Skill-d97757)](https://code.claude.com/docs/en/skills)
[![12 Visual Styles](https://img.shields.io/badge/Styles-12-purple)]()
[![14 Diagram Types](https://img.shields.io/badge/Diagram%20Types-14-green)]()
[![UML Support](https://img.shields.io/badge/UML-Full%20Support-orange)]()

---

## Overview

`fireworks-tech-graph` is one Agent Skill that works unchanged in **Codex and Claude Code**. It turns natural language descriptions into polished, geometry-checked SVG diagrams, high-resolution PNGs, validated SVG-to-GIF semantic motion, and offline interactive HTML. The focused animation path accepts a generated semantic SVG and emits one compact, probed GIF. It ships with **11 generator-backed styles** and **1 AI-authored style (Dark Luxury)**. Four engineering-first styles add executable contracts for C4 reviews, cloud deployments, event streams, and reliability investigations, alongside deep AI/Agent domain patterns and 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

> The animated previews use the user-approved 5.75-second settled-flow timeline: routes draw in first, then the final topology keeps live data moving for two additional seconds. Each full-size GIF is 960px wide at 20fps / 115 frames; the 3×4 overview is an optimized 1200px preview. Lossless 1920px PNGs remain in `assets/samples/` as static regression baselines.

![Animated 12-style showcase — one distinct engineering scenario per style](assets/samples/showcase-12-styles.gif)

The v1.2.0 overview above and every full-size animated sample below come from the approved regression set. Each style keeps a distinct scenario while sharing the same geometry, text-fit, wire-routing, and semantic-motion quality gates.

### Style 1 — Flat Icon (default)
*Mem0 Memory Architecture — personal-memory extraction, conflict resolution, storage, and retrieval*
![Style 1 — Flat Icon](assets/samples/sample-style1-flat.gif)

### Style 2 — Dark Terminal
*Tool Call Flow — dark terminal execution, source grounding, retrieval, and answer synthesis*
![Style 2 — Dark Terminal](assets/samples/sample-style2-dark.gif)

### Style 3 — Blueprint
*Microservices Architecture — engineering grid, domain services, data stores, events, and telemetry*
![Style 3 — Blueprint](assets/samples/sample-style3-blueprint.gif)

### Style 4 — Notion Clean
*Agent Memory Types — minimal hierarchy from sensory and working context to durable memory*
![Style 4 — Notion Clean](assets/samples/sample-style4-notion.gif)

### Style 5 — Glassmorphism
*Multi-Agent Collaboration — coordinator, specialists, shared state, review, and synthesis*
![Style 5 — Glassmorphism](assets/samples/sample-style5-glass.gif)

### Style 6 — Claude Official
*System Architecture — warm interface, runtime, safety, memory, tools, and operations layers*
![Style 6 — Claude Official](assets/samples/sample-style6-claude.gif)

### Style 7 — OpenAI Official
*API Integration Flow — clean SDK, prompt, model, tool, delivery, and release stages*
![Style 7 — OpenAI Official](assets/samples/sample-style7-openai.gif)

### Style 8 — Dark Luxury *(AI-authored)*
*Agent Runtime Architecture — control plane, execution and state layers, champagne-gold structure, semantic color buckets*
![Style 8 — Dark Luxury](assets/samples/sample-style8-dark-luxury.gif)

### Style 9 — C4 Review Canvas
*Checkout Container Review — one abstraction level, explicit responsibilities, technologies, and protocols*
![Style 9 — C4 Review Canvas](assets/samples/sample-style9-c4-review-canvas.gif)

### Style 10 — Cloud Fabric
*Active–Active Checkout Deployment — global ingress, regions, VPC ownership, and cross-region replication*
![Style 10 — Cloud Fabric](assets/samples/sample-style10-cloud-fabric.gif)

### Style 11 — Event Transit
*Checkout Event Line — topics as rails, processors as stations, a declared junction, DLQ, and state projection*
![Style 11 — Event Transit](assets/samples/sample-style11-event-transit.gif)

### Style 12 — Ops Pulse
*Checkout Reliability Pulse — golden signals, one critical path, OTel export, and a correlated trace*
![Style 12 — Ops Pulse](assets/samples/sample-style12-ops-pulse.gif)

---

## Stable Prompt Recipe

The public showcase keeps a distinct domain scene for every style. They remain comparable because every fixture passes the same executable composition contract. A same-topology regression set remains internal under `fixtures/quality-baseline/`.

```text
Draw the scenario assigned to style N:
1 Mem0 Memory Architecture; 2 Tool Call Flow; 3 Microservices Architecture;
4 Agent Memory Types; 5 Multi-Agent Collaboration; 6 System Architecture;
7 API Integration Flow; 8 Agent Runtime Architecture; 9 C4 Checkout Review;
10 Active–Active Cloud Deployment; 11 Checkout Event Line; 12 Checkout Reliability Pulse.
Preserve the scenario-specific nodes, sections, and reading direction.
Apply the showcase composition contract: zero crossings, zero bridge jumps, at most two bends per edge,
at most eight bends overall, at least 40px between nodes, at least 20px container gutter,
short orthogonal segments, and labels kept clear of nodes, routes, and section headers.
Preserve the selected style's typography, palette, card material, and brand details.
```

For the four engineering-first styles, use one of these prompt fingerprints so
the router selects the domain contract as well as the visual theme:

```text
Style 9 · C4 review board: show one C4 level, responsibilities, technologies, review state, and relationship protocols.
Style 10 · Multi-region deployment map: show global ingress, Region/VPC ownership, neutral cloud glyphs, deployment mode, and named boundary mechanisms.
Style 11 · Event metro map: show thin topic rails, numbered processor stations, declared junctions, consumer groups, DLQ, and state projections.
Style 12 · Reliability pulse: show one observation window, four golden signals per service, numbered critical hops, telemetry export, and one correlated trace.
```

Replace `N` with `1`–`12`. Style 8 remains AI-authored and loads `references/style-8-dark-luxury.md`; Styles 9–12 also enforce their engineering semantic contract. All styles load `references/composition-quality-contract.md`.

---

## Features

- **12 visual styles** — 11 generator-backed profiles + 1 AI-authored style (Dark Luxury)
- **Engineering semantic contracts** — C4 abstraction levels, deployment ownership, event-rail topology, and exact golden signals fail closed before rendering
- **Executable style system** — style guides are encoded into the generator, not only documented in markdown
- **Shared composition-quality contract** — every official style enforces zero crossings/bridges, ≤2 bends per edge, route-stretch, spacing, gutter, micro-segment, and label-clearance budgets
- **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)
- **Geometry-safe routing** — deterministic orthogonal routes, exact waypoints, distinct ports, automatic legend relocation, labels kept inside the canvas, and verified bridge jumps for unavoidable crossings
- **Versioned diagram IR** — legacy JSON normalizes to schema v1; duplicate IDs, dangling references, malformed waypoints, and non-finite geometry fail before rendering
- **Structured SVG validation** — XML and marker integrity plus semantic node, reserved-region, label, canvas, edge-overlap, and edge-crossing checks
- **Unified CLI + interactive export** — render, validate, inspect, and export one offline HTML file with pan/zoom, themes, copy, and SVG/PNG/JPEG/WebP output up to 4×
- **Focused semantic GIF motion** — generated SVG in, validated GIF out; connectors begin absent and draw in semantic order. All twelve style contracts are user-approved. The shared `+2s-settled-flow` timing revision is also user-approved, so the default 5.75s/115-frame loop holds full settled flow on frames 38–109, then resets on
agent-workflowsaiclaude-codedeveloper-toolsdiagramssvg

Lo que la gente pregunta sobre fireworks-tech-graph

¿Qué es yizhiyanhua-ai/fireworks-tech-graph?

+

yizhiyanhua-ai/fireworks-tech-graph es tools para el ecosistema de Claude AI. Generate production-quality SVG+PNG technical diagrams from natural language. 7 styles, UML support, and AI/Agent workflow patterns. Tiene 9.5k estrellas en GitHub y se actualizó por última vez 11d ago.

¿Cómo se instala fireworks-tech-graph?

+

Puedes instalar fireworks-tech-graph clonando el repositorio (https://github.com/yizhiyanhua-ai/fireworks-tech-graph) o siguiendo las instrucciones del README en GitHub. ClaudeWave también te ofrece bloques de instalación rápida en esta misma página.

¿Es seguro usar yizhiyanhua-ai/fireworks-tech-graph?

+

Nuestro agente de seguridad ha analizado yizhiyanhua-ai/fireworks-tech-graph y le ha asignado un Trust Score de 100/100 (tier: Verified). Revisa el desglose completo de comprobaciones superadas y flags en esta página.

¿Quién mantiene yizhiyanhua-ai/fireworks-tech-graph?

+

yizhiyanhua-ai/fireworks-tech-graph es mantenido por yizhiyanhua-ai. La última actividad registrada en GitHub es de 11d ago, con 0 issues abiertos.

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