Generate production-quality SVG+PNG technical diagrams from natural language. 7 styles, UML support, and AI/Agent workflow patterns.
# Add to your Claude Code skills
git clone https://github.com/yizhiyanhua-ai/fireworks-tech-graphGuides for using ai agents skills like fireworks-tech-graph.
Last scanned: 5/5/2026
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}See how fireworks-tech-graph compares with popular alternatives.
fireworks-tech-graph is an open-source ai agents skill for AI coding assistants such as Claude Code, Codex CLI, and ChatGPT, built by yizhiyanhua-ai. Generate production-quality SVG+PNG technical diagrams from natural language. 7 styles, UML support, and AI/Agent workflow patterns. It has 11,441 GitHub stars.
Yes. fireworks-tech-graph passed SkillsLLM's automated security scan — a dependency vulnerability audit plus prompt-injection heuristics — with no high-severity issues. You can read the full report in the Security Report section on this page.
Clone the repository with "git clone https://github.com/yizhiyanhua-ai/fireworks-tech-graph" and add it to your Claude Code skills directory (see the Installation section above). fireworks-tech-graph ships a SKILL.md manifest, so compatible agents can discover and load it automatically.
fireworks-tech-graph is primarily written in Python. It is open-source under yizhiyanhua-ai on GitHub, so you can review or fork the full source.
Yes. SkillsLLM lists many other AI Agents skills you can browse and compare side by side. Open the AI Agents category from the badge at the top of this page, or use the Related Skills and comparison links further down to weigh fireworks-tech-graph against similar tools.
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See comparison
One portable Agent Skill for Codex and Claude Code. SVG is the canonical artifact; PNG, offline HTML and supported GIF motion are output routes. Preserve requested labels, topology and meaning; a successful command is not a visual quality verdict.
Resolve the directory containing this file as SKILL_ROOT. Use
${CLAUDE_SKILL_DIR} in Claude Code or the absolute directory in Codex's loaded
skill metadata. Do not assume cwd or a previous shell variable persists.
Use the installed version for the task. Run version for source/version questions
and doctor when diagnosing a missing renderer, font or dependency; do not make
installation, updates or a complete test suite prerequisites for every diagram.
SKILL_ROOT="${CLAUDE_SKILL_DIR:-/absolute/path/from-codex-skill-metadata}"
python3 "$SKILL_ROOT/scripts/fireworks.py" version
Reuse the user's current brief and artifact; an extra planning document is optional.
For JSON work, select text_policy: "strict" when all labels must be visible exactly.
The compatible report default preserves full labels in SVG metadata and reports
any visible truncation. Resolve that warning before claiming complete exact text.
For polished work apply the composition contract.
SKILL_ROOT="${CLAUDE_SKILL_DIR:-/absolute/path/from-codex-skill-metadata}"
python3 "$SKILL_ROOT/scripts/fireworks.py" validate architecture input.json
python3 "$SKILL_ROOT/scripts/fireworks.py" render architecture input.json diagram.svg --report layout.json
python3 "$SKILL_ROOT/scripts/fireworks.py" check diagram.svg
python3 "$SKILL_ROOT/scripts/fireworks.py" export-png diagram.svg diagram.png --width 1920
check validates SVG identity, marker references, generic collisions, semantic
geometry and composition. Inspect the report's typography and palette scope;
heuristic text widths do not replace inspecting the actual rendered font.
Use visual quality guidance for readability and
style-specific refinements. Keep one semantic connector per business edge.
export-png, which reads root canvas dimensions, limits output
size, writes atomically and reads the PNG dimensions back. Alternate renderer
details are in PNG export.fireworks.py export-html diagram.svg diagram.html. One sanitized
offline file provides pan/zoom, source copy and static image downloads.fireworks.py animate diagram.svg diagram.gif. Default is 960px, 20fps, 5.75s
with the +2s-settled-flow preset and a .motion.json report. Historical
user-approved fields describe maintainer-reviewed presets, not authorization
from the current user to publish, spend or send data.Inspect the final PNG at intended reading size when image viewing is available: check text completeness, contrast, font substitution, hierarchy, spacing, clipping, arrow direction, crossings and labels. Preserve style palette and material while fixing defects. Reuse an unchanged reviewed render; do not keep adding tests or polish after acceptance passes. If viewing is unavailable, explicitly mark the visual check skipped and do not claim visual correctness.
After a failed check, use its element IDs and geometry to make a focused repair; change the approach after two unchanged failures. Widen/split an overfull diagram instead of hiding required copy or endlessly shrinking type. Do not silently weaken semantic or composition constraints to obtain a pass.
Complete every requested local output and its applicable checks, then report file paths, dimensions, visual review and residual limitations. A first SVG does not complete a requested PNG/GIF/HTML package. Publication or remote delivery requires its own scope-matching authorization; existing authorization is not requested twice.
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.
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.
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
Interested in becoming a sponsor? Contact: ccc7574@gmail.com
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.
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.
Mem0 Memory Architecture — personal-memory extraction, conflict resolution, storage, and retrieval

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

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

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

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

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

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

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

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

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

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

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

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, n