Scientific Agent Skills is a collection of reusable procedures that give AI agents capabilities for scientific research across areas such as biology, chemistry, medicine, and drug discovery. It is used by researchers and by people building AI scientist workflows with compatible coding agents. The catalogue contains many of the project's skills and supporting instructions.
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 K-Dense-AI/scientific-agent-skills --skill infographicsgit clone --depth 1 https://github.com/K-Dense-AI/scientific-agent-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/k-dense-ai/scientific-agent-skills/infographics)<a href="https://agentmods.dev/skills/k-dense-ai/scientific-agent-skills/infographics"><img src="https://agentmods.dev/badge/skills/k-dense-ai/scientific-agent-skills/infographics/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/k-dense-ai/scientific-agent-skills/infographics"><img src="https://agentmods.dev/badge/skills/k-dense-ai/scientific-agent-skills/infographics.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk warn
- NVIDIA SkillSpector pass
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 | $0.00057 | $0.03482 |
| Opus 5.5 | $0.00023 | $0.01393 |
| Sonnet 5.5 | $0.00011 | $0.00696 |
| Haiku 4.5 | $0.00006 | $0.00348 |
Grade A, and why
infographics 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 26d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- infographics — 100% identical, 97 lines differ
How it starts
The opening of the file, as written. The whole thing — 371 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Infographics
Overview
Infographics are visual representations of information, data, or knowledge designed to present complex content quickly and clearly. This skill uses Nano Banana 2 AI for infographic generation with Gemini 3.7 Flash quality review and Perplexity Sonar for research.
How it works:
- (Optional) Research phase: Gather candidate facts and source records using Perplexity Sonar Pro
- Describe your infographic in natural language
- Nano Banana 2 generates raster drafts from your content
- Gemini 3.7 Flash reviews quality against document-type thresholds
- Smart iteration: Regenerates when review requests improvements, within the iteration budget
- Inspect every final image at its intended display size and check claims against sources
Quality Thresholds by Document Type:
| Document Type | Threshold | Description |
|---|---|---|
| marketing | 8.5/10 | Marketing materials - must be compelling |
| report | 8.0/10 | Business reports - professional quality |
| presentation | 7.5/10 | Slides, talks - clear and engaging |
| social | 7.0/10 | Social media content |
| internal | 7.0/10 | Internal use |
| draft | 6.5/10 | Working drafts |
| default | 7.5/10 | General purpose |
Simply describe what you want, and Nano Banana 2 creates it.
Quick Start
Install the only runtime dependency in your chosen Python environment (python -m pip install requests),
then set OPENROUTER_API_KEY. Examples below illustrate CLI usage; paid generation was not
executed during this review. Scripts accept PNG output paths only.
Generate a draft by describing it:
# Generate a list infographic (default threshold 7.5/10)
python skills/infographics/scripts/generate_infographic.py \
"5 benefits of regular exercise" \
-o figures/exercise_benefits.png --type list
# Generate for marketing (highest threshold: 8.5/10)
python skills/infographics/scripts/generate_infographic.py \
"Product features comparison" \
-o figures/product_comparison.png --type comparison --doc-type marketing
# Generate with corporate style
python skills/infographics/scripts/generate_infographic.py \
"Company milestones 2010-2025" \
-o figures/timeline.png --type timeline --style corporate
# Generate with colorblind-safe palette
python skills/infographics/scripts/generate_infographic.py \
"Heart disease statistics worldwide" \
-o figures/health_stats.png --type statistical --palette wong
# Generate WITH RESEARCH for accurate, up-to-date data
python skills/infographics/scripts/generate_infographic.py \
"Global AI market size and growth projections" \
-o figures/ai_market.png --type statistical --research
What ships with it
7 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.
- 26d ago Changed · +32 lines dcd4ac5b46ac
- 27d ago Changed · +5 lines a4677d13d9f0
- 1mo ago Changed · +18 lines 370dc1cadbcf
- 1mo ago First seen · 316 lines · 57 tokens per session scan A e1d8a7601c1d
infographics is a skill published in the GitHub repository K-Dense-AI/scientific-agent-skills (54,953 stars, last pushed yesterday), licensed MIT. It adds 57 tokens to every session and 3,482 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
discovery-toolbox
A routed repertoire of 90 scientific thinking operators for biological research agents - visual reasoning, detectability and information budgets, search reframing, causal identification, competing explanations, observation and selection processes, pipeline artifact diagnosis, effort allocation, and confirmation…
discovery-director
Operate as a research director making original discoveries from a given biological question and dataset. Use when the task is open-ended scientific research, exploring omics or experimental data for findings, hypothesis generation and testing, screening a large candidate space of genes, variants, features or…
create-video-seedance-2-fal
Generate a single 4-15s vertical video clip with ByteDance Seedance 2.0 reference-to-video via fal.ai, for shots with no realistic face (a product hero, a product in motion, an empty set). Multi-image reference (product + setting), ambient audio, internal multi-cut handling within one render, 720p by default. Routes…
meta-ad-manager
Front door and loop owner of a Meta (Facebook/Instagram) ad harness. Reads the brand's ads/ docs, works out which campaign the user means and which stage it is at, hands off to the stage skill that runs it (intake, strategy, creative, launch, checks, fixes, answers), and writes every stage change back to the docs. Use…
run-memory
Shared step of the marketing playbooks (analyze-performance, run-paid-campaigns, research-competitors, email-lifecycle): reads the last run's record, checks whether its recommendations were done and whether they worked, and saves a short record of this run for the next one. Loaded by those playbooks; not for direct…
render-imessage-chat
Render a configurable iMessage conversation inside a properly framed phone, then a brand end card. Uses the original send/receive sounds and a shared frame timeline for text, typing, scrolling and sound. Free local Playwright + ffmpeg assembly; optional image/music generation belongs to separate gated capabilities.