fireworks-tech-graph

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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.

Output quality

The current checkout adds complete-text reporting and stronger supporting text across the default themes. Add "text_policy": "strict" to reject visible truncation before output is written; reports preserve the full source label and explain how to recover. Chinese descriptions use the available second line. See visual quality for theme-specific guidance and measurement limits.

python3 "$SKILL_ROOT/scripts/fireworks.py" version
python3 "$SKILL_ROOT/scripts/fireworks.py" export-png diagram.svg diagram.png --width 1920

version reports the package, actual Skill root and Git state when available. doctor distinguishes SVG/HTML support from optional PNG/GIF dependencies. PNG export checks the root canvas, bounds image size, writes atomically and reads the resulting pixel dimensions back. The browser PNG exporter remains available for Chromium fidelity. The showcase GIFs below are the published 1.2.0 references; this unreleased upgrade preserves their motion contracts.

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

Sponsors

Thanks to AIGoCode for sponsoring this project! AIGoCode is an all-in-one platform that integrates Claude Code, Codex, and the latest Gemini models, providing you with stable, efficient, and highly cost-effective AI coding services. The sponsor advertises flexible subscriptions and direct access without a VPN; availability and account conditions follow its own service terms. AIGoCode has prepared a special benefit for fireworks-tech-graph users: if you register via this link, you'll receive an extra 10% bonus credit on your first top-up!

Interested in becoming a sponsor? Contact: ccc7574@gmail.com

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.

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 2 — Dark Terminal

Tool Call Flow — dark terminal execution, source grounding, retrieval, and answer synthesis

Style 3 — Blueprint

Microservices Architecture — engineering grid, domain services, data stores, events, and telemetry

Style 4 — Notion Clean

Agent Memory Types — minimal hierarchy from sensory and working context to durable memory

Style 5 — Glassmorphism

Multi-Agent Collaboration — coordinator, specialists, shared state, review, and synthesis

Style 6 — Claude Official

System Architecture — warm interface, runtime, safety, memory, tools, and operations layers

Style 7 — OpenAI Official

API Integration Flow — clean SDK, prompt, model, tool, delivery, and release stages

Style 8 — Dark Luxury (AI-authored)

Agent Runtime Architecture — control plane, execution and state layers, champagne-gold structure, semantic color buckets

Style 9 — C4 Review Canvas

Checkout Container Review — one abstraction level, explicit responsibilities, technologies, and protocols

Style 10 — Cloud Fabric

Active–Active Checkout Deployment — global ingress, regions, VPC ownership, and cross-region replication

Style 11 — Event Transit

Checkout Event Line — topics as rails, processors as stations, a declared junction, DLQ, and state projection

Style 12 — Ops Pulse

Checkout Reliability Pulse — golden signals, one critical path, OTel export, and a correlated trace

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/.

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:

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)