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-proteomics-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-proteomics-analysis)<a href="https://agentmods.dev/skills/andyzhuang/opentest/tooluniverse-proteomics-analysis"><img src="https://agentmods.dev/badge/skills/andyzhuang/opentest/tooluniverse-proteomics-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-proteomics-analysis"><img src="https://agentmods.dev/badge/skills/andyzhuang/opentest/tooluniverse-proteomics-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 | $0.00110 | $0.06545 |
| Opus 5 | $0.00055 | $0.03272 |
| Sonnet 5 | $0.00022 | $0.01309 |
| Haiku 4.5 | $0.00011 | $0.00654 |
Grade A, and why
tooluniverse-proteomics-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 — 844 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Proteomics Analysis
Comprehensive analysis of mass spectrometry-based proteomics data from protein identification through quantification, differential expression, post-translational modifications, and systems-level interpretation.
When to Use This Skill
Triggers:
- User has proteomics data (MS output files)
- Questions about protein abundance or expression
- Differential protein expression analysis requests
- PTM analysis (phosphorylation, acetylation, ubiquitination)
- Protein-RNA correlation analysis
- Multi-omics integration involving proteomics
- Protein complex or interaction analysis
- Proteomics biomarker discovery
Example Questions This Skill Solves:
- "Analyze this MaxQuant output for differential protein expression"
- "Which proteins are significantly upregulated in disease vs control?"
- "Correlate protein abundance with mRNA expression"
- "What post-translational modifications change between conditions?"
- "Identify protein complexes in my co-IP MS data"
- "Which pathways are enriched in differentially expressed proteins?"
- "Find protein biomarkers for disease classification"
- "Compare protein and RNA levels to identify translation-regulated genes"
Core Capabilities
| Capability | Description |
|---|---|
| Data Import | MaxQuant, Spectronaut, DIA-NN, Proteome Discoverer, FragPipe outputs |
| Quality Control | Missing value analysis, intensity distributions, sample clustering |
| Normalization | Median, quantile, TMM, VSN normalization methods |
| Imputation | MinProb, KNN, QRILC for missing values |
| Differential Expression | Limma, DEP, MSstats for statistical testing |
| PTM Analysis | Phospho-site localization, PTM enrichment, kinase prediction |
| Protein-RNA Integration | Correlation analysis, translation efficiency |
| Pathway Enrichment | Over-representation and GSEA for protein sets |
| PPI Analysis | Protein complex detection, interaction networks via STRING/IntAct |
| Reporting | Comprehensive reports with volcano plots, heatmaps, pathway diagrams |
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 · 844 lines · 110 tokens per session scan A b203d5fe82f6
tooluniverse-proteomics-analysis is a skill published in the GitHub repository AndyZhuang/Opentest (22 stars, last pushed 6mo ago), licensed MIT. It adds 110 tokens to every session and 6,545 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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