agentmods.dev

nature-figure

nature-figure is a skill for Claude Code, Codex from hamzabellouch/agent-skills. It costs 235 tokens per session (1,565 once invoked), scanned A, a copy of nature-figure, MIT.

A tool for creating, revising, checking, and exporting scientific figures with Python or R, including multi-panel plots and journal-ready SVG, PDF, and TIFF files. Python and R are programming languages commonly used for data analysis and plotting.

In plain words
What is it for?
Use it to make manuscript plots, multi-panel figures, heat maps, paper schematics, and export files for scientific journals.
Why use it?
It helps researchers turn data into consistent figures that meet publication requirements and makes figure quality checks part of the workflow.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

not rated 4repo 1mo ago A scan 235 tokens copy · 88% MIT

Good fit Use it to make manuscript plots, multi-panel figures, heat maps, paper schematics, and export files for scientific journals.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/hamzabellouch/agent-skills/academic-nature-nature-figure
View source ↗ hamzabellouch/agent-skills sites.google.com
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 hamzabellouch/agent-skills --skill academic-nature-nature-figure
Clone the repo
git clone --depth 1 https://github.com/hamzabellouch/agent-skills

Made for: Claude Code, Codex.

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 nature-figure

README.md
[![agentmods](https://agentmods.dev/badge/skills/hamzabellouch/agent-skills/academic-nature-nature-figure/github.svg)](https://agentmods.dev/skills/hamzabellouch/agent-skills/academic-nature-nature-figure)
Your own site
<a href="https://agentmods.dev/skills/hamzabellouch/agent-skills/academic-nature-nature-figure"><img src="https://agentmods.dev/badge/skills/hamzabellouch/agent-skills/academic-nature-nature-figure/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 nature-figure

Your own site · 80×15
<a href="https://agentmods.dev/skills/hamzabellouch/agent-skills/academic-nature-nature-figure"><img src="https://agentmods.dev/badge/skills/hamzabellouch/agent-skills/academic-nature-nature-figure.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 235 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,565 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 88% 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 $0.00235 $0.01565
Opus 5 $0.00118 $0.00783
Sonnet 5 $0.00047 $0.00313
Haiku 4.5 $0.00023 $0.00156

Measured 9d ago against content hash fbc78556785f, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

nature-figure 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 9d ago.

The scan reads SKILL.md. This mod also ships 17 executable files (assets/figures4papers/figure_brainteaser/plot_brute_force.py, assets/figures4papers/figure_brainteaser/plot_correctness_by_category.py, assets/figures4papers/figure_brainteaser/plot_correctness_by_subcategory.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

88% identical to nature-figure — 102 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.

Academic and Scientific Research/academic-nature-nature-figure/SKILL.md · 79 lines

How it starts

The opening of the file, as written. The whole thing — 79 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Nature Figure Making — Router

This skill is split into two layers:

  • A static layer under static/ that holds versioned, reusable content fragments (the figure contract and default stance, plus a per-backend quick-start for Python and R).
  • A dynamic layer (this file plus manifest.yaml) that detects the plotting backend and loads only the fragment needed for the current job. The large design, API, pattern, and QA material lives in on-demand references.

Do not try to apply the figure logic from memory or from this router. Always load fragments from disk as described below.

Routing protocol

Follow these steps every time the skill is invoked.

0. Check for the OpenRouter AI-schematic route

If the user explicitly asks to generate a manuscript schematic, graphical abstract, mechanism diagram, concept illustration, or paper schematic with OpenRouter, GPT Image 2, an image-generation API, or similar wording, do not ask "Python or R?". This is a non-plotting AI-schematic route.

For this route:

  1. Read manifest.yaml and the always_load files.
  2. Read references/openrouter-image-generation.md.
  3. Use scripts/generate_openrouter_schematic.py when the user wants a real API call or a reproducible payload.
  4. Treat output as a draft schematic / graphical abstract, not as a quantitative data panel. Do not invent experimental values, author logos, institutional marks, or unsupported mechanisms.

Only continue to the Python/R backend gate for plotting, charting, data visualization, or manuscript figure assembly tasks that are not explicit OpenRouter AI image-generation requests.

1. Load the manifest and the core layer

Read manifest.yaml. It declares the backend axis, the allowed values, and the file paths each value maps to.

Also read every file listed under always_load (static/core/contract.md and static/core/stance.md). These hold the figure contract, the backend gate, the missing-runtime rule, the privacy rule, and the default operating stance that apply to every figure job.

Read the full file on GitHub · 79 lines

Files

What ships with it

60 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. 9d ago First seen · 79 lines · 235 tokens per session scan A fbc78556785f

Subscribe to this mod's changes

nature-figure is a skill published in the GitHub repository hamzabellouch/agent-skills (4 stars, last pushed 1mo ago), licensed MIT. It adds 235 tokens to every session and 1,565 once invoked, about $0.0012 per session on Opus 5. A static security scan graded it A with 0 findings. It is 88% identical to nature-figure, differing in 102 lines, and is treated as a copy.

Claude CodeDocumentsPDFScientificagent-skillsai-agentantigravitycodex-clicursor
Related

Other skills, from other repositories

nsfc-budget

A tool that creates an editable LaTeX budget justification and renders it as a PDF for an NSFC research-funding application. NSFC is China’s National Natural Science Foundation, and a budget justification explains why proposed costs are needed.

huangwb8/ChineseResearchLaTeX · 138 tokens

nsfc-ref-alignment

A read-only checker for references in NSFC LaTeX proposals. It compares citations with the bibliography and flags missing entries, field errors, and possible mismatches between claims and papers.

huangwb8/ChineseResearchLaTeX · 90 tokens

read

Read PDF page by page with structured output — key arguments, terms glossary, thesis connections. Use when reading academic papers, books, or articles.

yha9806/academic-writing-toolkit · 31 tokens

release-governance

Use when preparing, auditing, releasing, PDF-hardening, or rebuttal-hardening academic manuscripts, datasets, artifacts, reviewer packets, or claim registers involving multiple refs, local assets, human labels, agent-assisted drafts, wide tables, figure provenance, submission PDFs, or evidence-boundary checks.

yha9806/academic-writing-toolkit · 64 tokens

taxonomy-vto

A reference guide for diagnosing visual problems in LaTeX research papers. It defines categories such as wasted page space, misplaced figures, inconsistent formatting, overflow, alignment, and template-migration issues.

OpenRaiser/PaperFit · 0 tokens

infrastructure-validation

Skill for the validation infrastructure module providing PDF validation, markdown validation, output integrity checks, link verification, documentation audits, issue categorization, and repository scanning. Use when validating research outputs, checking document quality, running audits, or verifying cross-references.

docxology/template · 54 tokens