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 cut-and-run-taggit 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/cut-and-run-tag)<a href="https://agentmods.dev/skills/gptomics/bioskills/cut-and-run-tag"><img src="https://agentmods.dev/badge/skills/gptomics/bioskills/cut-and-run-tag/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/cut-and-run-tag"><img src="https://agentmods.dev/badge/skills/gptomics/bioskills/cut-and-run-tag.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 | $0.00177 | $0.04521 |
| Opus 5 | $0.00088 | $0.02261 |
| Sonnet 5 | $0.00035 | $0.00904 |
| Haiku 4.5 | $0.00018 | $0.00452 |
Grade A, and why
bio-chipseq-cut-and-run-tag 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.
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-chipseq-cut-and-run-tag — 97% identical, 12 lines differ
How it starts
The opening of the file, as written. The whole thing — 260 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Version Compatibility
Reference examples tested with: SEACR 1.3+, MACS2 2.2.9+, MACS3 3.0.4+, samtools 1.19+, bowtie2 2.5+, bedtools 2.31+, deepTools 3.5+, GoPeaks 1.0+, LanceOtron (pip).
CUT&RUN / CUT&Tag
"Analyze CUT&RUN or CUT&Tag chromatin profiling data" -> Use the lower-background, lower-input alternatives to traditional ChIP. CUT&RUN tethers MNase to an antibody via Protein A; CUT&Tag tethers Tn5 via Protein A/G. Both bypass cross-linking, fragmentation, and IP washes — producing 10-100× lower background, allowing 100-1000× lower cell input, and shifting the peak-calling problem from "find signal in noise" to "find signal in near-zero background."
- Aligner: bowtie2 (CUT&RUN/Tag standard) or bwa-mem; chromap optional
- Peak calling (CUT&RUN/Tag): SEACR (Meers 2019), MACS2 with
-f BAMPE --keep-dup all, or both for consensus - Spike-in: E. coli carryover from bacterially-produced pA-MNase/Tn5 (automatic, variable)
- Control: IgG-only (no input control; native chromatin has no meaningful "input")
CUT&RUN/CUT&Tag has different QC thresholds, different peak calling defaults, different spike-in protocols, and different antibody requirements than traditional ChIP. Treating it as ChIP fails silently.
Protocol Variant Taxonomy
| Variant | Chimera | Year | Use case | Failure mode |
|---|---|---|---|---|
| CUT&RUN (Skene Henikoff) | pA-MNase | 2017 | Native chromatin profiling; broad antibody compatibility | Native (no fixation) — gentler; MNase digest needs careful Ca²⁺ control |
| CUT&Tag (Kaya-Okur Henikoff) | pA-Tn5 (rabbit only) | 2019 | Lower cell input (~5000); faster; library-ready output | Rabbit-only antibody; PCR cycles can over-amplify |
| CUT&Tag-IT (Active Motif) | pA-Tn5 commercial | 2020 | Standardized lots; reproducible | Cost; vendor-locked |
| pAG-Tn5 CUT&Tag | pAG-Tn5 | 2020 | Binds both rabbit AND mouse IgG | More versatile; identical performance otherwise |
| AutoCut&Tag | pAG-Tn5 plate-based | 2021 | High-throughput (96-well) | Throughput at the cost of per-sample optimization |
| CUTAC (CUT&Tag-then-ATAC) | pAG-Tn5 + protocol modification | 2020 | Chromatin accessibility variant of CUT&Tag | Less common; not standard CUT&Tag |
| scCUT&Tag | pAG-Tn5 in droplets | 2021 | Single-cell histone mark profiling | Very sparse (~1000-5000 reads/cell) |
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.
- 9d ago First seen · 260 lines · 177 tokens per session scan A b299e8f4ce28
bio-chipseq-cut-and-run-tag is a skill published in the GitHub repository GPTomics/bioSkills (1,201 stars, last pushed 28d ago), licensed MIT. It adds 177 tokens to every session and 4,521 once invoked, about $0.0009 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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