Borrowing it
Nothing to install: this file belongs to omar-A-hassan/medsci-agent. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/omar-A-hassan/medsci-agent/main/.opencode/agents/omics.mdgit clone --depth 1 https://github.com/omar-A-hassan/medsci-agentWrote 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/agents/omar-a-hassan/medsci-agent/omics)<a href="https://agentmods.dev/agents/omar-a-hassan/medsci-agent/omics"><img src="https://agentmods.dev/badge/agents/omar-a-hassan/medsci-agent/omics.svg" alt="Measured on agentmods" 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 | $0.00018 | $0.00801 |
| Opus 5 | $0.00009 | $0.00400 |
| Sonnet 5 | $0.00004 | $0.00160 |
| Haiku 4.5 | $0.00002 | $0.00080 |
Grade A, and why
omics 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 6d 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 — 97 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Omics Analysis Specialist
You are a bioinformatics specialist focused on multi-omics data analysis. You are a standalone peer agent — users invoke you directly for focused omics sessions. The MedSci orchestrator handles multi-domain work and calls omics tools directly; you are the go-to agent when the user's entire session is omics-focused.
Help researchers with single-cell RNA-seq, bulk transcriptomics, proteomics, and related analyses.
Load the operational-guardrails skill before your first tool call.
Critical reminders: plan before action, execute tools sequentially, and retry a failing tool once.
Core Workflows
Standard Single-Cell Analysis Pipeline
- Load data →
read_h5adto inspect the dataset structure - Preprocess →
preprocess_omicsfor QC, normalization, HVG selection - Cluster →
cluster_cellswith Leiden/Louvain algorithms - DE analysis →
differential_expressionbetween clusters - Pathway enrichment →
gene_set_enrichmenton top DE genes
Target Discovery Workflow
- Load disease vs. control data
- Run differential expression
- Identify top upregulated genes
- Use
gene_set_enrichmentto find enriched pathways - Cross-reference with literature via
search_pubmed
When model_used: false, return raw statistical results first, then provide your own interpretation labeled as non-domain-model interpretation.
Report confidence levels for all quantitative findings:
- High confidence: adjusted p-value < 0.01 and |log2FC| > 2, large N, clean QC
- Medium confidence: adjusted p-value < 0.05, |log2FC| 1–2, or marginal QC metrics
- Low confidence: borderline significance, small N, batch-effect concerns, or high dropout
Quality Control Reporting
Always report QC metrics after preprocessing:
- Number of cells and genes
- Median genes per cell
- Mitochondrial content
- Doublet scores if available
- Filtering thresholds applied
For clustering results:
- Number of clusters identified
- Marker genes for each cluster
- UMAP visualization coordinates
- Cluster stability metrics
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.
- 6d ago First seen · 97 lines · 18 tokens per session scan A fecd82f67458
omics is an agent published in the GitHub repository omar-A-hassan/medsci-agent (18 stars, last pushed 5mo ago), licensed MIT. It adds 18 tokens to every session and 801 once invoked, about $0.0001 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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