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 HolobiomicsLab/asb-skill-collections --skill narrow-peak-calling-score-thresholdgit clone --depth 1 https://github.com/HolobiomicsLab/asb-skill-collectionsWrote 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/holobiomicslab/asb-skill-collections/narrow-peak-calling-score-threshold)<a href="https://agentmods.dev/skills/holobiomicslab/asb-skill-collections/narrow-peak-calling-score-threshold"><img src="https://agentmods.dev/badge/skills/holobiomicslab/asb-skill-collections/narrow-peak-calling-score-threshold/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/holobiomicslab/asb-skill-collections/narrow-peak-calling-score-threshold"><img src="https://agentmods.dev/badge/skills/holobiomicslab/asb-skill-collections/narrow-peak-calling-score-threshold.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- 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 | $0.00045 | $0.01529 |
| Opus 5 | $0.00023 | $0.00764 |
| Sonnet 5 | $0.00009 | $0.00306 |
| Haiku 4.5 | $0.00005 | $0.00153 |
Grade A, and why
narrow-peak-calling-score-threshold 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.
How it starts
The opening of the file, as written. The whole thing — 95 lines — stays where its author put it; the contents beside it link to each section on GitHub.
narrow-peak-calling-score-threshold
Summary
Call narrow peaks from a q-value bedgraph track by applying a statistical significance cutoff and enforcing minimum peak length and gap constraints. This final step converts continuous score data into discrete peak regions for ChIP-Seq analysis.
When to use
After generating a q-value bedgraph track from ChIP-Seq pileup versus local lambda comparison, and you need to identify statistically significant narrow peaks with defined boundaries. Apply this skill when your input is a bedgraph file of q-values (or p-values) and you want discrete narrowPeak format output with regions that exceed a user-specified significance threshold.
When NOT to use
- Input is broad histone mark data (e.g., H3K27me3, H3K4me1) — use bdgbroadcall instead of bdgpeakcall
- Input bedgraph contains p-values not converted to -log10 scale — ensure proper transformation before applying cutoff
- Fragment length d is unavailable or unreliable (e.g., bimodal or very short ChIP library) — revisit macs3 predictd output or adjust d manually based on expected mark width
Inputs
- bedgraph file of q-value scores (output from macs3 bdgcmp with -m qpois)
- predicted fragment length d (from macs3 predictd)
- significance threshold (q-value cutoff, typically 0.05)
Outputs
- narrowPeak format file with peak coordinates, summit, and -log10(q-value) scores
How to apply
Use macs3 bdgpeakcall to identify contiguous regions in the q-value track that exceed a cutoff threshold (converted from q-value to -log10 scale; e.g., q-value 0.05 = cutoff 1.301). Enforce a minimum peak length equal to the predicted fragment length d (e.g., 245 bp) to filter out spurious short fragments, and set a gap parameter to the read length (typically 100 bp) to merge peaks separated by small intervals. The function outputs narrowPeak format, which includes peak coordinates, summit position, and -log10(q-value) score for each called peak. Rationale: the fragment length constraint ensures peaks are wide enough to represent true ChIP enrichment, while the gap parameter prevents artificial fragmentation of continuous enriched regions.
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 · 95 lines · 45 tokens per session scan A a8b377246bca
narrow-peak-calling-score-threshold is a skill published in the GitHub repository HolobiomicsLab/asb-skill-collections (15 stars, last pushed yesterday), licensed Apache-2.0. It adds 45 tokens to every session and 1,529 once invoked, about $0.0002 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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