Upstream Processing Skills Index
- Repo stars 428
- Author updated Live
- Author repo PantheonOS
- Domain
- Engineering
- Compatible agents
-
- Claude Code
- Cursor
- Cline
- Codex
- Windsurf
- Gemini CLI
- +20
- Trust score
- 88 / 100 · community maintained
- Author / version / license
- @aristoteleo · no license declared
- Token usage
- Lean
- Setup complexity
- Plug-and-play
- External API key
- Not required
- Operating systems
- Unspecified (assume cross-platform)
- Runtime requirements
- No special requirements
- Permissions
-
- Read-only
- Write / modify
- Network behavior
- Local-only
- Install commands
- 26 variants
Profile is derived at build time from SKILL.md and install vectors. Subject to drift from author intent.
Heads up: 未限定 allowed-tools，默认拥有全部工具权限。
---
name: Upstream Processing Skills Index
description: | Skills and workflows for upstream data processing steps that precede standard single-cell anal…
category: engineering
runtime: no special runtime
---
# Upstream Processing Skills Index output preview
## PART A: Task fit
- Use case: | Skills and workflows for upstream data processing steps that precede standard single-cell analysis (QC, normalization, clustering, etc.). These cover technology-specific pipelines from raw sequencing data runs entirely locally. Works with Claude Code, Cursor, Cline and 23 more..
- Inputs: target material, constraints, expected output, and acceptance criteria.
- Evidence boundary: follow “Available Skills / OpenST / nf-core Pipelines” and do not present inference as author intent.
## PART B: Execution result
- **01** The card summarizes the use case; runtime output centers on “| Skills and workflows for upstream data processing steps that precede standard single-cell analysis (QC, normalization, clustering, etc.). These cover technology-specific pipelines from raw sequencing data runs entirely locally. Works with Claude Code, Cursor, Cline and 23 more.”.
- **02** When the source has headings, the agent prioritizes “Available Skills / OpenST / nf-core Pipelines” so the result follows the author’s structure.
- **03** Typical output includes task judgment, concrete steps, required commands or file edits, validation, and follow-up options.
- **04** Risk context follows the fingerprint: read files, write/modify files; mostly runs locally; usually needs no extra API key.
## Running Rules
- read files, write/modify files; mostly runs locally; usually needs no extra API key.
- Validate with a small sample before expanding scope.
- Return the result, validation criteria, and next iteration options.The source does not require a stable slash command. After installation, invoke the skill by name and describe the task.
Name target files or source material, expected output, forbidden changes, and whether network or shell access is allowed. Permission fingerprint: read files, write/modify files.
Start with a small task and check whether the result follows “Available Skills / OpenST / nf-core Pipelines”. Inspect diffs, logs, previews, or tests before expanding scope.
Confirm the final output includes a concrete result, evidence, and next action. If it stays generic, tighten inputs, boundaries, and acceptance criteria.
---
name: Upstream Processing Skills Index
description: | Skills and workflows for upstream data processing steps that precede standard single-cell anal…
category: engineering
source: aristoteleo/PantheonOS
---
# Upstream Processing Skills Index
## When to use
- | Skills and workflows for upstream data processing steps that precede standard single-cell analysis (QC, normalizatio…
- Use it when the task has clear inputs, repeatable steps, and validation criteria.
## What to provide
- Target material, scope, expected result, and forbidden changes.
- Whether network, commands, file writes, or external services are allowed.
## Execution rules
- Organize steps around “Available Skills / OpenST / nf-core Pipelines” and keep inference separate from source facts.
- read files, write/modify files; mostly runs locally; usually needs no extra API key.
- Validate with a small sample before expanding the task.
## Output requirements
- Return the deliverable, key evidence, validation method, and next action.
- Mark missing information as unknown; do not invent commands, platforms, or dependencies.The author source anchors workflow facts; repository files anchor sources and commands; Fluxly only adds fit, limitations, and quality judgment.
skill "Upstream Processing Skills Index" {
input -> user goal + target files + boundaries + acceptance criteria
context -> Available Skills / OpenST / nf-core Pipelines
rules -> SKILL.md triggers / order / output contract
runtime -> no special runtime | read files, write/modify files | mostly runs locally
guardrails -> usually needs no extra API key + small-sample validation + diff/log review
output -> copyable result + checklist + next iteration
}Upstream Processing Skills
Skills and workflows for upstream data processing steps that precede standard single-cell analysis (QC, normalization, clustering, etc.). These cover technology-specific pipelines from raw sequencing data to analysis-ready count matrices with spatial coordinates.
Available Skills
OpenST
Open-ST is an open-source spatial transcriptomics technology that captures transcriptome-wide data at sub-cellular resolution. The computational pipeline covers flow cell barcode preprocessing, transcriptomic alignment via spacemake, image-to-coordinate registration, cell segmentation, and 3D reconstruction.
Skill directory: openst/
When to use:
- Processing raw Open-ST data from BCL files to spatially-resolved h5ad
- Aligning transcriptomic coordinates to H&E tissue images
- Cell segmentation and transcript-to-cell assignment
- 3D reconstruction from serial tissue sections
nf-core Pipelines
nf-core is a community-driven collection of 143+ curated Nextflow pipelines for bioinformatics. Skills cover installation, configuration, and pipeline-specific guides for transcriptomics, spatial omics, epigenomics, and variant calling.
Skill directory: nfcore/
When to use:
- Processing scRNA-seq data (10x, Drop-seq, Smart-seq) with nf-core/scrnaseq
- Processing spatial transcriptomics (Visium, Xenium, MERSCOPE) with nf-core pipelines
- Processing bulk RNA-seq, ATAC-seq, ChIP-seq, CUT&Run, or methylation data
- Variant calling from WGS/WES with nf-core/sarek
- Setting up Nextflow and nf-core on HPC clusters or cloud environments
Using Skills
- Identify your technology: Find the relevant sub-directory for your spatial/sequencing platform
- Load skill files: Read the full skill documents for step-by-step guidance
- Follow the pipeline: Upstream processing is sequential; follow stages in order
- Proceed to downstream analysis: After generating the count matrix, use the main omics skills for QC, clustering, etc.
Decide Fit First
Design Intent
How To Use It
Boundaries And Review