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 AlterLab-IEU/AlterLab-Academic-Skills --skill alterlab-borzoigit clone --depth 1 https://github.com/AlterLab-IEU/AlterLab-Academic-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/skills/alterlab-ieu/alterlab-academic-skills/alterlab-borzoi)<a href="https://agentmods.dev/skills/alterlab-ieu/alterlab-academic-skills/alterlab-borzoi"><img src="https://agentmods.dev/badge/skills/alterlab-ieu/alterlab-academic-skills/alterlab-borzoi/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/alterlab-ieu/alterlab-academic-skills/alterlab-borzoi"><img src="https://agentmods.dev/badge/skills/alterlab-ieu/alterlab-academic-skills/alterlab-borzoi.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 | $0.00164 | $0.01015 |
| Opus 5 | $0.00082 | $0.00508 |
| Sonnet 5 | $0.00033 | $0.00203 |
| Haiku 4.5 | $0.00016 | $0.00102 |
Grade A, and why
alterlab-borzoi 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 12d 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 — 80 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Borzoi (sequence → function)
Overview
Borzoi (Linder et al. 2025; calico/borzoi) is a sequence-to-function deep-learning
model: given a DNA sequence over a long genomic context, it predicts genome-wide functional
tracks — RNA-seq, CAGE, ATAC-seq, and ChIP coverage across many assays/tissues. Its headline
use is non-coding variant effect scoring: run the reference and alternate alleles through
the model and compare predicted tracks to estimate a regulatory variant's impact on expression
or chromatin.
It predicts function from sequence; it does not look up known variants. For a variant's
population frequency use alterlab-gnomad; for clinical significance use alterlab-clinvar.
When to Use This Skill
Use this skill when the user wants to:
- Predict functional tracks (RNA-seq/CAGE/ATAC/ChIP) from a DNA sequence or locus.
- Score a non-coding / regulatory variant's predicted effect (ref vs. alt).
- Run in-silico mutagenesis to find driver bases in a regulatory element.
- Prioritize candidate regulatory variants by predicted functional impact.
Does NOT Trigger
| Scenario | Use instead |
|---|---|
| Look up a variant's population frequency | alterlab-gnomad |
| Look up a variant's clinical significance | alterlab-clinvar |
| Predict a protein-structure / coding effect | alterlab-alphafold |
| Single-cell foundation-model tasks | alterlab-scgpt |
| Standard variant calling from reads | alterlab-nf-core-sarek (or the relevant pipeline skill) |
Core Capabilities
1. Track prediction from sequence
# calico/borzoi — API sketch; TODO(verify) against installed borzoi
# 1) extract the reference sequence window around a locus
# 2) run the model to get multi-track predicted coverage
# (see references/borzoi_usage.md for the exact model-loading + predict calls)
Provide a genome window (coordinates + reference, or a FASTA); the model returns predicted coverage across its output tracks.
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.
- 12d ago First seen · 80 lines · 164 tokens per session scan A 3fcb8984c4bb
alterlab-borzoi is a skill published in the GitHub repository AlterLab-IEU/AlterLab-Academic-Skills (66 stars, last pushed 7d ago), licensed MIT. It adds 164 tokens to every session and 1,015 once invoked, about $0.0008 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 2026-08-30.
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