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 AndyZhuang/Opentest --skill tooluniverse-structural-variant-analysisgit clone --depth 1 https://github.com/AndyZhuang/OpentestWrote 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/andyzhuang/opentest/tooluniverse-structural-variant-analysis)<a href="https://agentmods.dev/skills/andyzhuang/opentest/tooluniverse-structural-variant-analysis"><img src="https://agentmods.dev/badge/skills/andyzhuang/opentest/tooluniverse-structural-variant-analysis/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/andyzhuang/opentest/tooluniverse-structural-variant-analysis"><img src="https://agentmods.dev/badge/skills/andyzhuang/opentest/tooluniverse-structural-variant-analysis.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 | $0.00094 | $0.12078 |
| Opus 5 | $0.00047 | $0.06039 |
| Sonnet 5 | $0.00019 | $0.02416 |
| Haiku 4.5 | $0.00009 | $0.01208 |
Grade A, and why
tooluniverse-structural-variant-analysis 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.
How it starts
The opening of the file, as written. The whole thing — 1,357 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Structural Variant Analysis Workflow
Systematic analysis of structural variants (deletions, duplications, inversions, translocations, complex rearrangements) for clinical genomics interpretation using ACMG-adapted criteria.
KEY PRINCIPLES:
- Report-first approach - Create SV_analysis_report.md FIRST, then populate progressively
- ACMG-style classification - Pathogenic/Likely Pathogenic/VUS/Likely Benign/Benign with explicit evidence
- Evidence grading - Grade all findings by confidence level (★★★/★★☆/★☆☆)
- Dosage sensitivity critical - Gene dosage effects drive SV pathogenicity
- Breakpoint precision matters - Exact gene disruption vs dosage-only effects
- Population context essential - gnomAD SVs for frequency assessment
- English-first queries - Always use English terms in tool calls (gene names, disease names), even if the user writes in another language. Only try original-language terms as a fallback. Respond in the user's language
Problem This Skill Solves
Structural variants (SVs) present unique interpretation challenges:
- Complex molecular consequences - SVs can cause gene dosage changes, gene disruption, gene fusions, position effects
- Size matters - Pathogenicity depends on size, gene content, and breakpoint precision
- Limited databases - Fewer curated SVs in ClinVar compared to SNVs
- Dosage sensitivity - Haploinsufficiency and triplosensitivity are critical but gene-specific
- Population frequency - Large benign CNVs are common; distinguishing pathogenic from benign is challenging
This skill provides: A systematic workflow integrating SV classification, gene content analysis, dosage sensitivity assessment, population frequencies, and ACMG-adapted criteria into clinically actionable interpretations.
Triggers
Use this skill when users:
- Ask about structural variant interpretation
- Have CNV data from array or sequencing
- Ask "is this deletion/duplication pathogenic?"
- Need ACMG classification for SVs
- Want to assess gene dosage effects
- Ask about chromosomal rearrangements
- Have large-scale genomic alterations requiring interpretation
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 · 1,357 lines · 94 tokens per session scan A fb17ce5ad2f9
tooluniverse-structural-variant-analysis is a skill published in the GitHub repository AndyZhuang/Opentest (22 stars, last pushed 6mo ago), licensed MIT. It adds 94 tokens to every session and 12,078 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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