Agent skill · AI & Agents

pacsomatic

Operator toolkit for nf-core/pacsomatic matched tumor-normal workflows from BAM inputs. Use this skill when the user needs to validate run inputs, generate pacsomatic-compliant samplesheets, prepare reproducible Nextflow launch artifacts, run locally or submit to schedulers (LSF/Slurm/PBS/SGE), and triage execution failures. Triggers on requests to run pacsomatic, prepare launch commands/scripts, perform dry-run checks, or troubleshoot pipeline startup and scheduler submission errors.

BioTender-maxgithub.com/BioTender-maxGitHub ↗
claude-codeships scriptsNOASSERTION
Install
npx skills add BioTender-max/awesome-bio-agent-skills --skill pacsomatic --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 8
SKILL.md size: 5 KB
Bundled scripts: yes
Path: skills/kdense/pacsomatic/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 135
Language: Python

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# pacsomatic ## Overview This skill provides a reproducible execution workflow for nf-core/pacsomatic, centered on a single helper entrypoint that handles validation, artifact generation, and optional execution. Primary entrypoint: - `scripts/run_pacsomatic.py` The helper script: - validates required identifiers, files, reference mode, and runtime prerequisites - writes a pacsomatic-compatible samplesheet (`patient,sample,status,bam,pbi`) - generates a params YAML and launch script for reproducible reruns - supports dry-run validation and run/submit execution paths Use this skill as the default path for pacsomatic operations. Do not bypass it with manually assembled `nextflow run nf-core/pacsomatic` commands unless the user explicitly asks for manual command construction. ## When to Use This Skill Invoke this skill when the user asks to: - run matched tumor-normal analysis from BAM files - generate or fix pacsomatic samplesheet and launch artifacts - execute locally or submit to schedulers (LSF/Slurm/PBS/SGE) - perform dry-run validation before execution - troubleshoot launch failures or summarize run outputs Do not use this skill for: - deep biological interpretation beyond run-le

What's inside
Steps it walks through
  1. Overview
  2. When to Use This Skill
  3. Routing and Execution Rules
  4. Inputs Required
  5. Workflow
  6. Agent Response Contract
  7. Quick Start
  8. Configuration
  9. Testing
  10. References
Ships with 7 files
  • LICENSE
  • config.yaml
  • references/agent-playbook.md
  • references/config-and-output.md
  • references/pacsomatic_guide.md
  • scripts/run_pacsomatic.py
  • tests/test_run_pacsomatic.py
Commands it runs
python scripts/run_pacsomatic.py \
python -m unittest discover -s tests -v
More from awesome-bio-agent-skills
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About this skill
What does the pacsomatic skill do?

Operator toolkit for nf-core/pacsomatic matched tumor-normal workflows from BAM inputs. Use this skill when the user needs to validate run inputs, generate pacsomatic-compliant samplesheets, prepare reproducible Nextflow launch artifacts, run locally or submit to schedulers (LSF/Slurm/PBS/SGE), and triage execution failures. Triggers on requests to run pacsomatic, prepare launch commands/scripts, perform dry-run checks, or troubleshoot pipeline startup and scheduler submission errors.

How do I install it?

Run `npx skills add BioTender-max/awesome-bio-agent-skills --skill pacsomatic --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From BioTender-max/awesome-bio-agent-skills, a repository with 135 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

Keep going