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 HolobiomicsLab/asb-skill-collections --skill stream-trajectory-data-formattinggit clone --depth 1 https://github.com/HolobiomicsLab/asb-skill-collectionsWrote 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/holobiomicslab/asb-skill-collections/stream-trajectory-data-formatting)<a href="https://agentmods.dev/skills/holobiomicslab/asb-skill-collections/stream-trajectory-data-formatting"><img src="https://agentmods.dev/badge/skills/holobiomicslab/asb-skill-collections/stream-trajectory-data-formatting/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/holobiomicslab/asb-skill-collections/stream-trajectory-data-formatting"><img src="https://agentmods.dev/badge/skills/holobiomicslab/asb-skill-collections/stream-trajectory-data-formatting.svg" alt="Reviewed on agentmods" width="80" 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 | $0.01292 |
| Opus 5 | $0.00024 | $0.00646 |
| Sonnet 5 | $0.00010 | $0.00258 |
| Haiku 4.5 | $0.00005 | $0.00129 |
Grade A, and why
stream-trajectory-data-formatting 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 — 96 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Reconstruct peak matrix export for STREAM compatibility via exportPeakMatrixForSTREAM
Summary
Export a peak-by-cell matrix from ArchR in a format compatible with STREAM trajectory analysis tool. This skill enables interoperability between ArchR's scATAC-seq processing and STREAM's trajectory inference, allowing users to leverage STREAM's visualization and analysis capabilities on ArchR-processed peak data.
When to use
Use this skill when you have completed peak calling and cell annotation in ArchR and want to perform trajectory inference or visualization in STREAM. Apply it specifically when your analysis goal requires STREAM's specialized trajectory reconstruction methods (e.g., elastic principal graphs, branching structure inference) on single-cell ATAC-seq peak data.
When NOT to use
- If your downstream trajectory tool is monocle3 or Slingshot — ArchR directly supports these via getMonocleTrajectories and addSlingShotTrajectories, without export overhead.
- If you need to preserve full dimensionality reduction or embedding information — STREAM export focuses only on the peak matrix; trajectory-specific embeddings from ArchR are not exported.
- If your peak matrix is already in a STREAM-compatible format from another source — re-exporting introduces redundant processing.
Inputs
- ArchR project object (processed with peak calls and cell annotations)
- Peak-by-cell accessibility matrix (internal ArchR representation)
Outputs
- Peak-by-cell matrix in CSV or TSV format compatible with STREAM
- Matrix with peaks as rows and cells as columns
How to apply
Load a processed ArchR project object containing peak calls and cell annotations. Call the exportPeakMatrixForSTREAM function on the ArchR project to generate a peak-by-cell matrix formatted for STREAM compatibility. The function produces output in CSV or TSV format that conforms to STREAM's expected matrix structure (peaks as rows, cells as columns, binary or accessibility values as matrix entries). Write the resulting matrix to a file and validate that the output dimensions match your peak and cell counts before importing into STREAM. The export preserves the peak-level and cell-level metadata necessary for downstream trajectory analysis.
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 · 96 lines · 48 tokens per session scan A 739a68fd4d7b
stream-trajectory-data-formatting is a skill published in the GitHub repository HolobiomicsLab/asb-skill-collections (15 stars, last pushed 2d ago), licensed Apache-2.0. It adds 48 tokens to every session and 1,292 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 2026-09-06.
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