pacsomatic

pacsomatic is a skill for Claude Code, Codex from crazymsn/academic-skills. It costs 103 tokens per session (1,201 once invoked), scanned A, a copy of pacsomatic, MIT.

A toolkit for running nf-core/pacsomatic, a workflow that compares matched tumour and normal DNA samples from BAM files. It validates inputs and creates the files needed to run the analysis locally or on a computing cluster.

In plain words
What is it for?
Use it to validate BAM-based tumour-normal analyses, create samplesheets and parameter files, prepare reproducible Nextflow runs, submit jobs to schedulers, perform dry runs, and troubleshoot execution.
Why use it?
It reduces setup mistakes and makes analysis runs easier to repeat by checking inputs and generating consistent launch files.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to validate BAM-based tumour-normal analyses, create samplesheets and parameter files, prepare reproducible Nextflow runs, submit jobs to schedulers, perform dry runs, and troubleshoot execution.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/crazymsn/academic-skills/pacsomatic
Install

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.

Any agent
npx skills add crazymsn/academic-skills --skill pacsomatic
Clone the repo
git clone --depth 1 https://github.com/crazymsn/academic-skills

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for pacsomatic

README.md
[![agentmods](https://agentmods.dev/badge/skills/crazymsn/academic-skills/pacsomatic/github.svg)](https://agentmods.dev/skills/crazymsn/academic-skills/pacsomatic)
Your own site
<a href="https://agentmods.dev/skills/crazymsn/academic-skills/pacsomatic"><img src="https://agentmods.dev/badge/skills/crazymsn/academic-skills/pacsomatic/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.

agentmods 80×15 button for pacsomatic

Your own site · 80×15
<a href="https://agentmods.dev/skills/crazymsn/academic-skills/pacsomatic"><img src="https://agentmods.dev/badge/skills/crazymsn/academic-skills/pacsomatic.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 103 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,201 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin 100% copy Near-identical to another mod in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00103 $0.01201
Opus 5 $0.00051 $0.00600
Sonnet 5 $0.00021 $0.00240
Haiku 4.5 $0.00010 $0.00120

Measured 8d ago against content hash 178da103b16d, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

pacsomatic 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.

The scan reads SKILL.md. This mod also ships 2 executable files (scripts/run_pacsomatic.py, tests/test_run_pacsomatic.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

Origin

This is a copy

100% identical to pacsomatic — 3 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.

academic-skills/pacsomatic/SKILL.md · 150 lines

How it starts

The opening of the file, as written. The whole thing — 150 lines — stays where its author put it; the contents beside it link to each section on GitHub.

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-level sanity checks
  • editing pipeline internals unless explicitly requested

Typical trigger phrases:

  • "run nf-core/pacsomatic for this tumor-normal pair"
  • "prepare pacsomatic samplesheet and launch script"
  • "do a dry run first and tell me what is missing"
  • "submit pacsomatic to slurm/lsf and return the job id"
  • "why did pacsomatic submission fail"

Routing and Execution Rules

  1. Always collect required run inputs first.
  2. Always route through scripts/run_pacsomatic.py for validation and artifact generation.
  3. Default to --dry-run when the user asks for checks/validation only.
  4. Use --run only when the user asks to execute/submit.
  5. For scheduler modes, include executor-specific resource arguments and return detected job ID when available.
  6. If execution fails, report first failure point and next triage target (.nextflow.log, pipeline_info, failing task logs).

Read the full file on GitHub · 150 lines

Files

What ships with it

7 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.

Changes

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.

  1. 8d ago First seen · 150 lines · 103 tokens per session scan A 178da103b16d

Subscribe to this mod's changes

pacsomatic is a skill published in the GitHub repository crazymsn/academic-skills (22 stars, last pushed 3mo ago), licensed MIT. It adds 103 tokens to every session and 1,201 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to pacsomatic, differing in 3 lines, and is treated as a copy.

Related

Other skills, from other repositories

instrument-data-to-allotrope

Convert laboratory instrument output files (PDF, CSV, Excel, TXT) to Allotrope Simple Model (ASM) JSON format or flattened 2D CSV. Use this skill when scientists need to standardize instrument data for LIMS systems, data lakes, or downstream analysis. Supports auto-detection of instrument types. Outputs include full…

anthropics/knowledge-work-plugins · 123 tokens

matlab

Build, review, migrate, and safely plan MATLAB or GNU Octave numerical workflows, including arrays, tabular/time data, tests, projects, graphics, MAT files, and explicit Python interoperability.

K-Dense-AI/scientific-agent-skills · 42 tokens

exploratory-data-analysis

Perform bounded, local exploratory analysis of explicitly supported scientific files. Use for redacted CSV/TSV/JSON profiles; optional NumPy, HDF5, FASTA/FASTQ, and basic image metadata inspection; missingness/leakage audits; outlier and transformation sensitivity; and rigorous EDA report scaffolds. Other domain…

K-Dense-AI/scientific-agent-skills · 83 tokens

phylogenetics

Build and analyze phylogenetic trees using MAFFT (multiple alignment), IQ-TREE 2 (maximum likelihood), and FastTree (fast NJ/ML). Visualize with ETE3 or FigTree. For evolutionary analysis, microbial genomics, viral phylodynamics, protein family analysis, and molecular clock studies.

K-Dense-AI/scientific-agent-skills · 68 tokens

research-engineer

An uncompromising Academic Research Engineer. Operates with absolute scientific rigor, objective criticism, and zero flair. Focuses on theoretical correctness, formal verification, and optimal implementation across any required technology.

davila7/claude-code-templates · 43 tokens

mapping-to-snomed

Maps clinical concept spans extracted by OpenMed to SNOMED CT concepts through a USER-SUPPLIED terminology server (the user's own Ontoserver, Snowstorm, or UMLS/UTS), never a bundled vocabulary. Use when the user wants to code findings, disorders, procedures, body structures, or substances to SNOMED CT, run an ECL…

maziyarpanahi/openmed · 205 tokens