fireworks-tech-graph
Generate production-quality SVG+PNG technical diagrams from natural language. 7 styles, UML support, and AI/Agent workflow patterns.
Install / Use
npx skills add yizhiyanhua-ai/fireworks-tech-graphInstalls into whichever agent you are using.
CLAUDE.md
Claude Code project instructions
Quality Score
Category
AutomationSupported Platforms
Tags
Our assessment of fireworks-tech-graph
fireworks-tech-graph scores 88/100 on our quality scale, 1476th of 2,863 Automation skills we index.
Its CLAUDE.md is 39 KB long, well organised into 59 sections with 37 code examples: long enough that it reads more like full documentation than a focused instruction file, which agents can find harder to follow.
With 11,943 GitHub stars, it is one of the more widely adopted skills in the catalogue.
Maintenance, license and trust
- The repository was last updated 15 days ago, so fireworks-tech-graph is actively maintained.
- Our last check on 2026-10-17 found the source still online.
- It is released under the MIT license, a permissive license that allows use, modification and commercial use with attribution.
- Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.
Safety scan
No issues foundOur scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. An AI review of the same text found nothing harmful.
AI review by kimi-k2.7-code on 2026-09-24. Automated pattern scan on 2026-09-24. It catches known dangerous patterns, not every risk — read a skill before letting an agent act on it.
fireworks-tech-graph compared with similar skills
All 4 of these similar skills score higher than fireworks-tech-graph; compare them before choosing.
| Skill | Score | Stars | Updated | Format |
|---|---|---|---|---|
| fireworks-tech-graph (this skill)by yizhiyanhua-ai | 88 | 11.9k | 15d ago | CLAUDE.md |
| claude-memby thedotmack | 100 | 113.5k | today | CLAUDE.md |
| taste-skillby Leonxlnx | 100 | 110.6k | today | CLAUDE.md |
| Agent-Reachby Panniantong | 100 | 109.2k | today | CLAUDE.md |
| Understand-Anythingby Egonex-AI | 100 | 90.9k | 10d ago | CLAUDE.md |
Frequently asked questions
- How do I install fireworks-tech-graph?
- Run
npx skills add yizhiyanhua-ai/fireworks-tech-graph. The install tabs above show the steps for each supported agent. - Which AI agents does fireworks-tech-graph work with?
- It is written for Claude Code, as a CLAUDE.md file. Other agents that read the same format can often use it too.
- Is fireworks-tech-graph safe to use?
- Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. An AI review of the same text found nothing harmful. It is MIT-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
- Is fireworks-tech-graph still maintained?
- The repository was last updated 15 days ago, so fireworks-tech-graph is actively maintained.
Skill content
View source on GitHubfireworks-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
<table> <tr> <td width="200" align="center"><a href="https://aigocode.app/invite/yizhiyanhua"><img src="assets/sponsors/aigocode.png" alt="AIGoCode" width="160" /></a></td> <td>Thanks to <strong>AIGoCode</strong> 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 <strong>fireworks-tech-graph</strong> users: if you register via <a href="https://aigocode.app/invite/yizhiyanhua">this link</a>, you'll receive an extra <strong>10% bonus credit</strong> on your first top-up!</td> </tr> <tr> <td width="200" align="center"><a href="https://go.apimart.ai/gh-fireworks-tech-graph"><img src="assets/sponsors/apimart.png" alt="APIMart" width="160" /></a></td> <td>Thanks to <strong>APIMart</strong> for sponsoring this project! APIMart is a low-cost API platform for AI image & video generation — GPT-Image-2 from <strong>$0.006/image</strong>, 160+ images per dollar. One async API covers both image and video: submit a task, get an ID, fetch results via polling or callback. Batch tens of thousands of images without timeouts, switch models without changing code. Pay-as-you-go with no monthly fee — <a href="https://go.apimart.ai/gh-fireworks-tech-graph">sign up here</a> to get started.</td> </tr> </table>Interested in becoming a sponsor? Contact: <a href="mailto:ccc7574@gmail.com">ccc7574@gmail.com</a>
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)
- 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;
Truncated for display — read the full file on GitHub.
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Languages
Trust signals
From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.
