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.
npx skills add Lzy599775/agent-auto-sci-skills --skill scientific-schematicsgit clone --depth 1 https://github.com/Lzy599775/agent-auto-sci-skillsWrote 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.
[](https://agentmods.dev/skills/lzy599775/agent-auto-sci-skills/scientific-schematics)<a href="https://agentmods.dev/skills/lzy599775/agent-auto-sci-skills/scientific-schematics"><img src="https://agentmods.dev/badge/skills/lzy599775/agent-auto-sci-skills/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.
<a href="https://agentmods.dev/skills/lzy599775/agent-auto-sci-skills/scientific-schematics"><img src="https://agentmods.dev/badge/skills/lzy599775/agent-auto-sci-skills/scientific-schematics.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00068 | $0.04557 |
| Opus 5.5 | $0.00027 | $0.01823 |
| Sonnet 5.5 | $0.00014 | $0.00911 |
| Haiku 4.5 | $0.00007 | $0.00456 |
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 15d ago.
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.
This is a copy
94% identical to scientific-schematics — 0 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.
How it starts
The opening of the file, as written. The whole thing — 394 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 3.7 Flash quality review.
How it works:
- Describe your diagram in natural language
- Nano Banana 2 generates a PNG draft from the specified components and relationships
- Gemini 3.7 Flash reviews quality against document-type thresholds
- Smart iteration: Refines when the score or verdict requests improvement
- Saved drafts and a review log for manual verification
- No coding, templates, or manual drawing required
Local review thresholds by document type (heuristics chosen by this helper, not publisher acceptance criteria):
| 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 |
Save diagrams under figures/ using -o figures/name.png, then inspect every label and relationship before including them in a paper or poster. The output location is the path you choose.
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
Run from this skill directory with requests installed and OPENROUTER_API_KEY set. The following paid-generation examples are illustrative; the request contracts are tested offline. Supply source-backed labels and relationships rather than asking the image model to invent them:
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.
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.
- 15d ago Changed · +6 lines · +1 tokens per session e15d761ef880
- 1mo ago Changed · +17 lines 3ef33ab3eb6e
- 1mo ago First seen · 371 lines · 67 tokens per session scan A 0bb588af42e7
scientific-schematics is a skill published in the GitHub repository Lzy599775/agent-auto-sci-skills (2 stars, last pushed 11d ago), licensed MIT. It adds 68 tokens to every session and 4,557 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 94% identical to scientific-schematics, differing in 0 lines, and is treated as a copy.
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