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 aristoteleo/PantheonOS --skill single_cellgit clone --depth 1 https://github.com/aristoteleo/PantheonOSWrote 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/aristoteleo/pantheonos/single_cell)<a href="https://agentmods.dev/skills/aristoteleo/pantheonos/single_cell"><img src="https://agentmods.dev/badge/skills/aristoteleo/pantheonos/single_cell.svg" alt="Measured on agentmods" 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 | $0.00048 | $0.00351 |
| Opus 5 | $0.00024 | $0.00176 |
| Sonnet 5 | $0.00010 | $0.00070 |
| Haiku 4.5 | $0.00005 | $0.00035 |
Grade A, and why
Single-Cell Analysis Skills Index 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.
What it actually says
Core Single-Cell Analysis Skills
High-priority, actionable workflows for the most common single-cell analysis tasks. For deeper background and alternative methods, see the supplementary SC Best Practices reference.
Available Skills
Quality Control
Standard QC workflow: filtering low-quality cells, doublet detection, normalization, and QC metric visualization.
Skill file: quality_control.md
When to use:
- Starting analysis of a new single-cell dataset
- Need to filter low-quality cells
- Assessing data quality metrics
Cell Type Annotation
Marker-based and reference-based approaches for assigning cell type labels.
Skill file: cell_type_annotation.md
When to use:
- After clustering, need to assign cell type labels
- Using marker genes for annotation
- Using reference-based methods (CellTypist, scArches)
Trajectory Inference
Pseudotime analysis and trajectory inference for cell differentiation, lineage tracing, and RNA velocity.
Skill file: trajectory_inference.md
When to use:
- Studying cell differentiation paths
- Neurogenesis or developmental trajectory analysis
- RNA velocity for directional dynamics
What ships with it
3 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.
- 8d ago First seen · 53 lines · 48 tokens per session scan A f4a077f65f4d
Single-Cell Analysis Skills Index is a skill published in the GitHub repository aristoteleo/PantheonOS (482 stars, last pushed yesterday), licensed BSD-2-Clause. It adds 48 tokens to every session and 351 once invoked, about $0.0002 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.
Other skills, from other repositories
cellxgene-census-query
Query CZ CELLxGENE Census (61M+ cells). Filter by cell type/tissue/disease, retrieve expression data, and integrate with scanpy/PyTorch for population-scale single-cell analysis. Use this skill when: (1) Querying single-cell expression data by cell type, tissue, or disease, (2) Exploring available single-cell datasets…
sc-filter
Load when removing low-quality cells and lowly-detected genes from a single-cell AnnData using QC-derived thresholds or tissue presets. Skip when the full normalize→HVG→PCA→cluster pipeline (use sc-preprocessing); reads are still raw FASTQ (use sc-fastq-qc).
sc-consensus-pseudotime
Load when you want a single-cell pseudotime ordering robust to the choice of trajectory method — fanning out DPT/Palantir/VIA from a shared root, rank-aligning them, and voting a consensus pseudotime with per-cell uncertainty. Skip when you have branching multi-lineage trajectories; no defined root.
sc-fastq-qc
Load when checking raw single-cell FASTQ read quality (Phred / GC / adapter / length) before counting. Skip when reads are already counted (use sc-qc); bulk FASTQ (use bulkrna-read-qc).
sc-qc
Load when computing per-cell QC metrics (ngenes, total counts, mt%, ribo%) on a single-cell AnnData before filtering. Skip when reads are still raw FASTQ (use sc-fastq-qc); you want to filter cells now (use sc-filter).
cell-type-annotation
Generate code to assign cell type labels to single-cell RNA-seq clusters using CellTypist, SingleR, marker-based annotation, or reference label transfer (scANVI/ingest). Triggers on requests to "annotate cell types", "label clusters", "run CellTypist", "SingleR annotation", "marker gene dotplot", "transfer labels from…