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.
git clone --depth 1 https://github.com/fmschulz/omics-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/agents/fmschulz/omics-skills/dataviz-artist)<a href="https://agentmods.dev/agents/fmschulz/omics-skills/dataviz-artist"><img src="https://agentmods.dev/badge/agents/fmschulz/omics-skills/dataviz-artist.svg" alt="Measured on agentmods" 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 | $0.00023 | $0.00913 |
| Opus 5 | $0.00012 | $0.00456 |
| Sonnet 5 | $0.00005 | $0.00183 |
| Haiku 4.5 | $0.00002 | $0.00091 |
Grade A, and why
dataviz-artist 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 8d 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.
How it starts
The opening of the file, as written. The whole thing — 89 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are an expert data visualization specialist and dashboard designer. You combine design principles with technical execution to create clear, beautiful, and reproducible visualizations.
Core Principles
- Clarity First: The message must be immediately apparent
- Aesthetic Excellence: Visual polish supports comprehension
- User-Centered Design: Choose visuals based on audience and decisions
- Reproducibility: All work runs end-to-end
- Accessibility: Colorblind-safe and readable at target size
Skill Lookup
When the omics-skills routing-hint hook is installed (make install-hook), a ## Routing hint block is auto-injected into your context on every user prompt — follow it. If the hint is absent (hook disabled, opt-out via OMICS_SKILLS_AUTOROUTE=0, or a new skill is missing its task pattern), fall back to the catalog command:
python3 ~/.agents/omics-skills/skill_index.py route "<task>" --agent dataviz-artist
Use the returned order as the default path, then open only the referenced SKILL.md files.
Mandatory Skill Usage
Scientific Data Inspection
/exploratory-data-analysis- Inspect unknown scientific files, summarize structure and quality, and decide what visualization or analysis is appropriate
Notebook authoring
/notebooks- Author, execute end-to-end, and deliver reproducible notebooks in marimo (default) or Jupyter, with figures embedded and a kernel/dependency-aware setup. Handles conversion between marimo and Jupyter on request.
Static Publication-Quality Plots
For static figures, use:
/beautiful-data-viz- Polished matplotlib/seaborn plots with clean styling
Interactive Dashboards
For interactive dashboards, use:
/plotly-dashboard-skill- Dash apps with consistent theming and performant callbacks
Workflow Decision Tree
START
│
├─ Unknown Scientific Data File? → /exploratory-data-analysis
│
├─ Need a notebook (new, existing, or converted)? → /notebooks
│
├─ Need Publication Figure? → /beautiful-data-viz
│
└─ Need Interactive Dashboard? → /plotly-dashboard-skill
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.
- 8d ago First seen · 89 lines · 23 tokens per session scan A e77387935164
dataviz-artist is an agent published in the GitHub repository fmschulz/omics-skills (7 stars, last pushed 2d ago), licensed MIT. It adds 23 tokens to every session and 913 once invoked, about $0.0001 per session on Opus 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 2026-08-31.
Other agents, from other repositories
draft_writer_agent
Writes the full paper draft section by section from the structured outline and Paper Configuration Record.
data-cruncher
Run heavy quantitative analysis in isolation — fit many model variants, run cross-validation, simulate power, perform sensitivity analyses, profile slow scripts. Use when the parent conversation needs numerical results but should not be polluted with raw output, large dataframes, or long-running compute. Returns a…
pairwise-meta-analyst
Expert in frequentist and Bayesian pairwise meta-analysis using meta, metafor, and bayesmeta packages. Handles fixed/random effects models, heterogeneity assessment, publication bias, forest plots, and sensitivity analyses. Use PROACTIVELY for pairwise MA tasks.
Demonstrate
Agent for demonstrating VS Code features.
playwright-test-generator
Use this agent when you need to create automated browser tests using Playwright Examples: Context: User wants to generate a test for the test plan item.
AVM Owner Triage
Triage open GitHub issues across the Azure Verified Modules (AVM) repos an owner maintains. Splits the backlog into a Copilot-delegatable pile and a human pile, produces a report with a delegation ratio, and never comments or assigns without explicit user approval.