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 GPTomics/bioSkills --skill lollipop-protein-mapsgit clone --depth 1 https://github.com/GPTomics/bioSkillsWrote 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/gptomics/bioskills/lollipop-protein-maps)<a href="https://agentmods.dev/skills/gptomics/bioskills/lollipop-protein-maps"><img src="https://agentmods.dev/badge/skills/gptomics/bioskills/lollipop-protein-maps/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/gptomics/bioskills/lollipop-protein-maps"><img src="https://agentmods.dev/badge/skills/gptomics/bioskills/lollipop-protein-maps.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 | $0.00098 | $0.03025 |
| Opus 5 | $0.00049 | $0.01512 |
| Sonnet 5 | $0.00020 | $0.00605 |
| Haiku 4.5 | $0.00010 | $0.00302 |
Grade A, and why
bio-data-visualization-lollipop-protein-maps 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- bio-data-visualization-lollipop-protein-maps — 94% identical, 12 lines differ
How it starts
The opening of the file, as written. The whole thing — 237 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Version Compatibility
Reference examples tested with: maftools 2.18+, trackViewer 1.38+, g3-lollipop (JavaScript via R g3viz 1.2+), Bio.PDB 1.83+ (for domain coordinates). ProteinPaint is a hosted service.
Before using code patterns, verify installed versions match. If versions differ:
- R:
packageVersion('<pkg>')then?function_name - Python:
pip show <package>thenhelp(module.function)
If code throws ImportError, AttributeError, or TypeError, introspect the installed package and adapt the example to match the actual API rather than retrying.
Lollipop / Needle Protein Maps
"Plot mutations on a gene's protein" -> Render a horizontal protein backbone with colored domain rectangles (from UniProt/Pfam/InterPro), then stack vertical lines ("stems") at mutated amino-acid positions, capped with circles ("lollipops") whose size reflects mutation count and whose color encodes variant class. The biological story is hotspot identification — a tall stack of recurrences at a single residue (e.g., KRAS G12, PIK3CA E545/H1047) is the visual signature of a driver mutation.
- R:
maftools::lollipopPlot,trackViewer::lolliplot,g3viz::g3Lollipop - Python:
pyLollipop(limited maintenance); ProteinPaint via API - Web: cBioPortal, ProteinPaint, MutationMapper
The Single Most Important Modern Insight -- Hotspot Recurrence Drives the Plot
A lollipop plot exists to identify hotspots — residues with disproportionate recurrence. The MutSig hotspot test (Lawrence 2014 Nature 505:495) and statisticalhotspot methods (Chang 2016 Nat Biotechnol 34:155) formalize this: a residue's mutation count should exceed the gene-wide background rate × residue count. Visualizing this on a domain map IS the diagnostic.
Key practical consequences:
- Stack height ≠ frequency: a tall lollipop at residue 600 means recurrence, not population frequency. Annotate the count.
- Domain colors should encode functional class (kinase, SH2, binding), not random hue.
- Mark known activating/inactivating residues (G12 for KRAS, R175 for TP53) with bold labels.
What ships with it
2 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.
- 8d ago First seen · 237 lines · 98 tokens per session scan A 190239cbc978
bio-data-visualization-lollipop-protein-maps is a skill published in the GitHub repository GPTomics/bioSkills (1,201 stars, last pushed 27d ago), licensed MIT. It adds 98 tokens to every session and 3,025 once invoked, about $0.0005 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 2026-09-03.
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