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 crosslink-site-detectiongit 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/crosslink-site-detection)<a href="https://agentmods.dev/skills/gptomics/bioskills/crosslink-site-detection"><img src="https://agentmods.dev/badge/skills/gptomics/bioskills/crosslink-site-detection/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/crosslink-site-detection"><img src="https://agentmods.dev/badge/skills/gptomics/bioskills/crosslink-site-detection.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 | $0.00117 | $0.05541 |
| Opus 5 | $0.00059 | $0.02771 |
| Sonnet 5 | $0.00023 | $0.01108 |
| Haiku 4.5 | $0.00012 | $0.00554 |
Grade A, and why
bio-clip-seq-crosslink-site-detection 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 7d 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-clip-seq-crosslink-site-detection — 100% 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: PureCLIP 1.3.1+, CTK 1.1.4+, PARalyzer 1.5+, wavClusteR 2.34+, pyCRAC 1.5+, samtools 1.19+, bedtools 2.31+, pysam 0.22+, R 4.3+.
Before using code patterns, verify installed versions match. If versions differ:
- CLI:
<tool> --versionthen<tool> --helpto confirm flags - Python:
pip show <package>thenhelp(module.function)to check signatures - R:
packageVersion('<pkg>')then?function_nameto verify parameters
If code throws unexpected errors, introspect the installed tool and adapt the example to match the actual CLI rather than retrying.
CLIP-seq Crosslink-Site Detection
"Detect single-nucleotide crosslink sites in my CLIP data" -> Identify the exact base where the protein-RNA UV adduct caused the reverse transcriptase to stop (truncation, in iCLIP/eCLIP), to read through with a mutation (deletion in HITS-CLIP, T->C in PAR-CLIP), or to leave a multi-base signature (PARalyzer kernel density for PAR-CLIP). Single-nucleotide resolution is the foundation of motif registration (mCross), allele-specific binding (BEAPR/ASPRIN), variant-effect prediction, and the most rigorous comparisons across CLIP variants. The detection chemistry differs by CLIP type: iCLIP/eCLIP read 5' end is one nucleotide downstream of the crosslink (CITS); PAR-CLIP reads contain T->C transitions at the crosslink (CIMS substitution); HITS-CLIP reads contain deletions at the crosslink (CIMS deletion).
- CLI (HMM, all CLIP variants):
pureclip -i dedup.bam -bai dedup.bam.bai -g genome.fa -ibam sminput.bam -ibai sminput.bam.bai -o crosslinks.bed -or regions.bed -nt 8 -dm 8 - CLI (CTK CITS truncations, iCLIP/eCLIP):
parseAlignment.pl --map-qual 1 --min-len 18 --mutation-file mut.txt dedup.bam dedup.bedthentag2cluster.pl ... -cs5 5 -m 1for truncation-cluster - CLI (CTK CIMS deletions, HITS-CLIP):
getMutationType.pl dedup.bed mut.txt -type delthenCIMS.pl dedup.bed mut.txt -big -c -p 0.01 cims.bed - CLI (CTK CIMS T->C, PAR-CLIP):
getMutationType.pl dedup.bed mut.txt -type sub -nuc t -mut cthenCIMS.pl dedup.bed t2c.mut -p 0.001 t2c_cims.bed - CLI (PAR-CLIP kernel density):
PARalyzer params.ini(parameters file defines read length, min reads per cluster, mutation rate threshold) - CLI (PAR-CLIP wavClusteR R):
wavClusteR::filterClusters(cl, snps=NULL, filterFC=FALSE)after wavelet clustering
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.
- 7d ago First seen · 260 lines · 117 tokens per session scan A e4ddc2272c92
bio-clip-seq-crosslink-site-detection is a skill published in the GitHub repository GPTomics/bioSkills (1,199 stars, last pushed 26d ago), licensed MIT. It adds 117 tokens to every session and 5,541 once invoked, about $0.0006 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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