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 biocontext-ai/skill-to-mcp --skill single-cell-rna-qcgit clone --depth 1 https://github.com/biocontext-ai/skill-to-mcpWrote 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/biocontext-ai/skill-to-mcp/single-cell-rna-qc)<a href="https://agentmods.dev/skills/biocontext-ai/skill-to-mcp/single-cell-rna-qc"><img src="https://agentmods.dev/badge/skills/biocontext-ai/skill-to-mcp/single-cell-rna-qc/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/biocontext-ai/skill-to-mcp/single-cell-rna-qc"><img src="https://agentmods.dev/badge/skills/biocontext-ai/skill-to-mcp/single-cell-rna-qc.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 | $0.00072 | $0.01892 |
| Opus 5.5 | $0.00029 | $0.00757 |
| Sonnet 5.5 | $0.00014 | $0.00378 |
| Haiku 4.5 | $0.00007 | $0.00189 |
Grade A, and why
single-cell-rna-qc 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 1mo 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.
This is a copy
97% identical to single-cell-rna-qc — 4 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 178 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Single-Cell RNA-seq Quality Control
Automated QC workflow for single-cell RNA-seq data following scverse best practices.
Acknowledgment: This skill is adapted from Anthropic's Life Sciences repository and follows best practices from the scverse® community.
When to Use This Skill
Use when users:
- Request quality control or QC on single-cell RNA-seq data
- Want to filter low-quality cells or assess data quality
- Need QC visualizations or metrics
- Ask to follow scverse/scanpy best practices
- Request MAD-based filtering or outlier detection
Supported input formats:
.h5adfiles (AnnData format from scanpy/Python workflows).h5files (10X Genomics Cell Ranger output)
Default recommendation: Use Approach 1 (complete pipeline) unless the user has specific custom requirements or explicitly requests non-standard filtering logic.
Approach 1: Complete QC Pipeline (Recommended for Standard Workflows)
For standard QC following scverse best practices, use the convenience script scripts/qc_analysis.py:
python3 scripts/qc_analysis.py input.h5ad
# or for 10X Genomics .h5 files:
python3 scripts/qc_analysis.py raw_feature_bc_matrix.h5
The script automatically detects the file format and loads it appropriately.
When to use this approach:
- Standard QC workflow with adjustable thresholds (all cells filtered the same way)
- Batch processing multiple datasets
- Quick exploratory analysis
- User wants the "just works" solution
Requirements: anndata, scanpy, scipy, matplotlib, seaborn, numpy
Parameters:
Customize filtering thresholds and gene patterns using command-line parameters:
--output-dir- Output directory--mad-counts,--mad-genes,--mad-mt- MAD thresholds for counts/genes/MT%--mt-threshold- Hard mitochondrial % cutoff--min-cells- Gene filtering threshold--mt-pattern,--ribo-pattern,--hb-pattern- Gene name patterns for different species
What ships with it
4 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.
- 1mo ago First seen · 178 lines · 72 tokens per session scan A 0dbfd50c87ee
single-cell-rna-qc is a skill published in the GitHub repository biocontext-ai/skill-to-mcp (29 stars, last pushed 8mo ago), licensed Apache-2.0. It adds 72 tokens to every session and 1,892 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 97% identical to single-cell-rna-qc, differing in 4 lines, and is treated as a copy.
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