scientific-schematics

scientific-schematics is a skill for Claude Code from agentlas-ai/agentlas-desktop. It costs 67 tokens per session (3,936 once invoked), scanned A, a copy of scientific-schematics, Apache-2.0.

A tool for creating scientific diagrams and schematics from a natural-language description. It is intended for visuals such as system diagrams, flowcharts, biological pathways, and neural-network layouts, with an automated quality review and possible revision.

In plain words
What is it for?
Use it to make diagrams for journal papers, conference papers, theses, grant proposals, preprints, reports, posters, and presentations.
Why use it?
It helps explain complex scientific ideas visually without requiring manual drawing or diagram templates. The review step can identify when a generated figure needs improvement for its intended document type.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter. Also seen: built for openclaw.

Good fit Use it to make diagrams for journal papers, conference papers, theses, grant proposals, preprints, reports, posters, and presentations.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/agentlas-ai/agentlas-desktop/scientific-schematics
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add agentlas-ai/agentlas-desktop --skill scientific-schematics
Clone the repo
git clone --depth 1 https://github.com/agentlas-ai/agentlas-desktop

Made for: Claude Code.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for scientific-schematics

README.md
[![agentmods](https://agentmods.dev/badge/skills/agentlas-ai/agentlas-desktop/scientific-schematics/github.svg)](https://agentmods.dev/skills/agentlas-ai/agentlas-desktop/scientific-schematics)
Your own site
<a href="https://agentmods.dev/skills/agentlas-ai/agentlas-desktop/scientific-schematics"><img src="https://agentmods.dev/badge/skills/agentlas-ai/agentlas-desktop/scientific-schematics/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for scientific-schematics

Your own site · 80×15
<a href="https://agentmods.dev/skills/agentlas-ai/agentlas-desktop/scientific-schematics"><img src="https://agentmods.dev/badge/skills/agentlas-ai/agentlas-desktop/scientific-schematics.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 67 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,936 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin 100% copy Near-identical to another mod in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00067 $0.03936
Opus 5.5 $0.00027 $0.01574
Sonnet 5.5 $0.00013 $0.00787
Haiku 4.5 $0.00007 $0.00394

Measured 1mo ago against content hash 3ef33ab3eb6e, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

scientific-schematics scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.

The scan reads SKILL.md. This mod also ships 3 executable files (scripts/example_usage.sh, scripts/generate_schematic_ai.py, scripts/generate_schematic.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

This is a copy

100% identical to scientific-schematics — 82 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

plugins/agentlas-science-skills/skills/scientific-schematics/SKILL.md · 388 lines

How it starts

The opening of the file, as written. The whole thing — 388 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Scientific Schematics and Diagrams

Overview

Scientific schematics and diagrams transform complex concepts into clear visual representations for publication. This skill uses Nano Banana 2 AI for diagram generation with Gemini 3.6 Flash quality review.

How it works:

  • Describe your diagram in natural language
  • Nano Banana 2 generates publication-quality images automatically
  • Gemini 3.6 Flash reviews quality against document-type thresholds
  • Smart iteration: Only regenerates if quality is below threshold
  • Publication-ready output in minutes
  • No coding, templates, or manual drawing required

Quality Thresholds by Document Type:

Document Type Threshold Description
journal 8.5/10 Nature, Science, peer-reviewed journals
conference 8.0/10 Conference papers
thesis 8.0/10 Dissertations, theses
grant 8.0/10 Grant proposals
preprint 7.5/10 arXiv, bioRxiv, etc.
report 7.5/10 Technical reports
poster 7.0/10 Academic posters
presentation 6.5/10 Slides, talks
default 7.5/10 General purpose

Simply describe what you want, and Nano Banana 2 creates it. All diagrams are stored in the figures/ subfolder and referenced in papers/posters.

What the output is: a raster PNG at whatever resolution the image model returns. This skill has no vector path and no DPI control — if a journal demands PDF, EPS, or 300 dpi TIFF, convert the PNG downstream and check the result at final print size.

Quick Start: Generate Any Diagram

Create any scientific diagram by simply describing it. Nano Banana 2 handles everything automatically with smart iteration:

# Generate for journal paper (highest quality threshold: 8.5/10)
python scripts/generate_schematic.py "CONSORT participant flow diagram with 500 screened, 150 excluded, 350 randomized" -o figures/consort.png --doc-type journal

# Generate for presentation (lower threshold: 6.5/10 - faster)
python scripts/generate_schematic.py "Transformer encoder-decoder architecture showing multi-head attention" -o figures/transformer.png --doc-type presentation

# Generate for poster (moderate threshold: 7.0/10)
python scripts/generate_schematic.py "MAPK signaling pathway from EGFR to gene transcription" -o figures/mapk_pathway.png --doc-type poster

# Custom max iterations (max 2)
python scripts/generate_schematic.py "Complex circuit diagram with op-amp, resistors, and capacitors" -o figures/circuit.png --iterations 2 --doc-type journal

Read the full file on GitHub · 388 lines

Files

What ships with it

5 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 1mo ago First seen · 388 lines · 67 tokens per session scan A 3ef33ab3eb6e

Subscribe to this mod's changes

scientific-schematics is a skill published in the GitHub repository agentlas-ai/agentlas-desktop (6 stars, last pushed yesterday), licensed Apache-2.0. It adds 67 tokens to every session and 3,936 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to scientific-schematics, differing in 82 lines, and is treated as a copy.

Related

Other skills, from other repositories

architecture-diagram

How to draw and maintain the architecture diagram Ensemblr keeps for a workspace — ensemblrgetarchitecturediagram to fetch the stored one (it answers with null when nobody has drawn this workspace yet), the IR shape, how to derive it from the codebase, and ensemblrupdatearchitecturediagram to store it. Read this when…

ensemblr-hq/ensemblr · 94 tokens

winui-design

Read before writing or changing WinUI 3 XAML: choosing controls, pages and navigation, layout, Fluent Design, theming, accessibility, x:Bind, real samples, and checking that APIs exist with winapp find-api. Not for WPF or WinForms UI, even if the app uses the Windows App SDK.

microsoft/winappCli · 70 tokens

figma-generate-design

Use this skill alongside figma-use when the task involves translating an application page, view, or multi-section layout into Figma. Triggers: 'write to Figma', 'create in Figma from code', 'push page to Figma', 'take this app/page and build it in Figma', 'create a screen', 'build a landing page in Figma', 'update the…

warpdotdev/warp · 160 tokens

openscreen-design

Use this skill to generate well-branded interfaces and assets for OpenScreen (an AI-native screen-recording studio & video editor), either for production or throwaway prototypes/mocks/etc. Contains essential design guidelines, colors, type, fonts, assets, and UI kit components for prototyping.

getopenscreen/openscreen · 62 tokens

vellum-avatar

Customize the assistant's avatar - build a native character, upload an image, or generate one with AI.

vellum-ai/vellum-assistant · 24 tokens

edit-figma-design

Create or update Figma designs directly from a written product or UI description using the Figma MCP authoring tools. Use when the user wants a mockup, wireframe, screen, component, flow, or concept designed in Figma from text, or wants to iterate on an existing Figma file from textual feedback. Despite the name, this…

warpdotdev/warp · 134 tokens