How do I install the Docs Generate Schematics skill?

Run npx skillmds@latest add bitranox/docs-generate-schematics in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Docs Generate Schematics safe to use?

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Which AI agents work with Docs Generate Schematics?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Docs Generate Schematics free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Docs Generate Schematics?

bitranox (@bitranox) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Docs Generate Schematics by bitranox

Name: Docs Generate Schematics
Author: bitranox

Docs Generate Schematics

Use when a document, paper, poster, or README needs a scientific schematic, flowchart, block diagram, or architecture figure GENERATED as an image from a text description via an AI image model - CONSORT participant flows, neural-network architectures, pipeline diagrams - using OpenRouter (OPENROUTER_API_KEY) with an automated quality-review loop. Not for converting existing documents (bitranox:docs-convert-markitdown) or code-rendered graphs (graphviz/matplotlib).

bitranox bc1c8d6 10 files · 57.2 KB Updated Sep 17, 2026

File contents

Generating scientific schematics with an AI image model

Adapted from the MarkItDown skill in K-Dense-AI/claude-scientific-skills (MIT). See THIRD_PARTY_NOTICES.md.

Generate publication-style schematic images (flowcharts, block diagrams, architecture figures) from a text description. The AI variant runs an iterative quality loop: generate, have a vision model critique the result against the document type, regenerate until the quality threshold or the iteration cap is hit.

Requirements

OPENROUTER_API_KEY in the environment (both scripts talk to OpenRouter).
httpx2 for the AI script: run it with uv run, which reads the script's PEP 723 block and fetches the dependency. Plain python3 only works if httpx2 is already installed. The wrapper script imports only stdlib, but it re-launches the AI script with the SAME interpreter (sys.executable), so it needs httpx2 just as much - run it under uv run --with httpx2 too, or the child exits 1 on its first import.

Usage

# AI generation with quality-review loop
uv run scripts/generate_schematic_ai.py "CONSORT participant flow for a two-arm RCT" -o flow.png
uv run scripts/generate_schematic_ai.py "Neural network architecture diagram" -o arch.png --iterations 2
uv run scripts/generate_schematic_ai.py "Simple block diagram" -o diagram.png --doc-type poster

# Wrapper: same quality-review loop, with the iteration cap clamped to 2
uv run --with httpx2 scripts/generate_schematic.py "Data pipeline overview" -o pipeline.png

--doc-type tunes the acceptance threshold (a poster tolerates less detail than a paper figure); --iterations caps the regenerate loop.

Common mistakes

Expecting deterministic output - image models vary run to run; keep the prompt specific (name the boxes, arrows, and labels you need) and review the result yourself.
Using this for graphs that should be code-rendered - reproducible plots and graphs belong in graphviz/matplotlib, not an image model; this skill is for illustrative schematics.
Committing the generated image without checking the labels - vision-model review catches layout problems, not domain wording.
Running without OPENROUTER_API_KEY - both scripts fail fast; set it in the environment, never on the command line.

---name: docs-generate-schematicsdescription: Use when a document, paper, poster, or README needs a scientific schematic, flowchart, block diagram, or architecture figure GENERATED as an image from a text description via an AI image model - CONSORT participant flows, neural-network architectures, pipeline diagrams - using OpenRouter (OPENROUTER_API_KEY) with an automated quality-review loop. Not for converting existing documents (bitranox:docs-convert-markitdown) or code-rendered graphs (graphviz/matplotlib).---# Generating scientific schematics with an AI image model> Adapted from the MarkItDown skill in K-Dense-AI/claude-scientific-skills (MIT). See THIRD_PARTY_NOTICES.md.Generate publication-style schematic images (flowcharts, block diagrams, architecturefigures) from a text description. The AI variant runs an iterative quality loop: generate,have a vision model critique the result against the document type, regenerate until thequality threshold or the iteration cap is hit.## Requirements- `OPENROUTER_API_KEY` in the environment (both scripts talk to OpenRouter).- `httpx2` for the AI script: run it with `uv run`, which reads the script's PEP 723 block and fetches the dependency. Plain `python3` only works if httpx2 is already installed. The wrapper script imports only stdlib, but it re-launches the AI script with the SAME interpreter (`sys.executable`), so it needs `httpx2` just as much - run it under `uv run --with httpx2` too, or the child exits 1 on its first import.## Usage```bash# AI generation with quality-review loopuv run scripts/generate_schematic_ai.py "CONSORT participant flow for a two-arm RCT" -o flow.pnguv run scripts/generate_schematic_ai.py "Neural network architecture diagram" -o arch.png --iterations 2uv run scripts/generate_schematic_ai.py "Simple block diagram" -o diagram.png --doc-type poster# Wrapper: same quality-review loop, with the iteration cap clamped to 2uv run --with httpx2 scripts/generate_schematic.py "Data pipeline overview" -o pipeline.png````--doc-type` tunes the acceptance threshold (a poster tolerates less detail than a paperfigure); `--iterations` caps the regenerate loop.## Common mistakes- Expecting deterministic output - image models vary run to run; keep the prompt specific (name the boxes, arrows, and labels you need) and review the result yourself.- Using this for graphs that should be code-rendered - reproducible plots and graphs belong in graphviz/matplotlib, not an image model; this skill is for illustrative schematics.- Committing the generated image without checking the labels - vision-model review catches layout problems, not domain wording.- Running without `OPENROUTER_API_KEY` - both scripts fail fast; set it in the environment, never on the command line.

Frequently asked questions