Agent skill

Pyopenms Skill

by aipoch in aipoch/medical-research-skills

Comprehensive tool for computational mass spectrometry using PyOpenMS; use when you need to read/write MS formats (mzML/mzXML/MGF), run signal processing (smoothing/peak picking), detect isotope…

MITAuto-check passedData & Analytics

Install Pyopenms Skill

skills CLI

$ npx skills add aipoch/medical-research-skills --skill pyopenms-skill -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI

$ gh skill install aipoch/medical-research-skills pyopenms-skill --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy

$ git clone --depth 1 https://github.com/aipoch/medical-research-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/'scientific-skills/Data Analysis/pyopenms-skill' .claude/skills/pyopenms-skill && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Paste into Claude Code

Install the "pyopenms-skill" agent skill from https://github.com/aipoch/medical-research-skills/tree/main/scientific-skills/Data%20Analysis/pyopenms-skill into .claude/skills/pyopenms-skill/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "pyopenms-skill", then confirm the skill loads.

Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

$skill-installer

$skill-installer install https://github.com/aipoch/medical-research-skills/tree/main/scientific-skills/Data%20Analysis/pyopenms-skill

Type this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.

skills CLI

$ npx skills add aipoch/medical-research-skills --skill pyopenms-skill -a codex

Project install goes to .agents/skills/; add -g for ~/.codex/skills/.

GitHub CLI

$ gh skill install aipoch/medical-research-skills pyopenms-skill --agent codex

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/aipoch/medical-research-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/'scientific-skills/Data Analysis/pyopenms-skill' .agents/skills/pyopenms-skill && rm -rf skills-src

Use ~/.agents/skills/ instead of .agents/skills for a personal install.

Codex skills documentation · loads skills from .agents/skills/

Paste into Codex

Install the "pyopenms-skill" agent skill from https://github.com/aipoch/medical-research-skills/tree/main/scientific-skills/Data%20Analysis/pyopenms-skill into .agents/skills/pyopenms-skill/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "pyopenms-skill", then confirm the skill loads.

Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add aipoch/medical-research-skills --skill pyopenms-skill -a cursor

Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.

GitHub CLI

$ gh skill install aipoch/medical-research-skills pyopenms-skill --agent cursor

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/aipoch/medical-research-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/'scientific-skills/Data Analysis/pyopenms-skill' .cursor/skills/pyopenms-skill && rm -rf skills-src

Use ~/.cursor/skills/ instead of .cursor/skills for a personal install.

Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/

Paste into Cursor

Install the "pyopenms-skill" agent skill from https://github.com/aipoch/medical-research-skills/tree/main/scientific-skills/Data%20Analysis/pyopenms-skill into .cursor/skills/pyopenms-skill/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "pyopenms-skill", then confirm the skill loads.

Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

gemini skills install

$ gemini skills install https://github.com/aipoch/medical-research-skills.git --path 'scientific-skills/Data Analysis/pyopenms-skill'

--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.

skills CLI

$ npx skills add aipoch/medical-research-skills --skill pyopenms-skill -a gemini-cli

Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.

GitHub CLI

$ gh skill install aipoch/medical-research-skills pyopenms-skill --agent gemini-cli

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/aipoch/medical-research-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/'scientific-skills/Data Analysis/pyopenms-skill' .gemini/skills/pyopenms-skill && rm -rf skills-src

Use ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.

Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/

Paste into Gemini CLI

Install the "pyopenms-skill" agent skill from https://github.com/aipoch/medical-research-skills/tree/main/scientific-skills/Data%20Analysis/pyopenms-skill into .gemini/skills/pyopenms-skill/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "pyopenms-skill", then confirm the skill loads.

Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

GitHub CLI

$ gh skill install aipoch/medical-research-skills pyopenms-skill

Installs for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).

skills CLI

$ npx skills add aipoch/medical-research-skills --skill pyopenms-skill -a github-copilot

Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.

Manual copy

$ git clone --depth 1 https://github.com/aipoch/medical-research-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/'scientific-skills/Data Analysis/pyopenms-skill' .github/skills/pyopenms-skill && rm -rf skills-src

Use ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.

GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/

Paste into GitHub Copilot

Install the "pyopenms-skill" agent skill from https://github.com/aipoch/medical-research-skills/tree/main/scientific-skills/Data%20Analysis/pyopenms-skill into .github/skills/pyopenms-skill/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "pyopenms-skill", then confirm the skill loads.

GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add aipoch/medical-research-skills --skill pyopenms-skill -a opencode

OpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.

GitHub CLI

$ gh skill install aipoch/medical-research-skills pyopenms-skill --agent opencode

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/aipoch/medical-research-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/'scientific-skills/Data Analysis/pyopenms-skill' .opencode/skills/pyopenms-skill && rm -rf skills-src

Use ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.

OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/

Paste into OpenCode

Install the "pyopenms-skill" agent skill from https://github.com/aipoch/medical-research-skills/tree/main/scientific-skills/Data%20Analysis/pyopenms-skill into .opencode/skills/pyopenms-skill/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "pyopenms-skill", then confirm the skill loads.

OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

Facts

Skill name: pyopenms-skill
GitHub stars: 2k
Token cost: ~852 tokens
SKILL.md length: 264 words
Files: 5 (incl. scripts, references)
Skills in repo: 567
Repo updated: Sep 17, 2026
First seen: Oct 7, 2026
Licence: MIT

At a glance

Comprehensive tool for computational mass spectrometry using PyOpenMS; use when you need to read/write MS formats (mzML/mzXML/MGF), run signal processing (smoothing/peak picking), detect isotope…

Works in 3 steps: Load an MS run from disk (e.g., mzML). → Process spectra (optional… → Analyze results (e.g., peak picking,…
You need to read/write MS formats (mzML/mzXML/MGF)
SKILL.md covers When to Use, Key Features, Dependencies and Example Usage, plus 1 more section
Runs Python scripts from its folder; calls uv and python

What it does

Pyopenms Skill is an agent skill from aipoch/medical-research-skills. Comprehensive tool for computational mass spectrometry using PyOpenMS; use when you need to read/write MS formats (mzML/mzXML/MGF), run signal processing (smoothing/peak picking), detect isotope features, or perform peptide identification in proteomics/metabolomics workflows.

Its SKILL.md is about 850 tokens, which your agent loads only when the skill is triggered. The skill folder holds 6 other files, including scripts and reference files (for example `pyopenms-skill_audit_result_v1.json`, `references/file_io.md` and `references/signal_processing.md`).

It sits in Data & Analytics, covering Bioinformatics. It works with Python. The repository describes itself as: Hundreds of agent skills for medical research, including protocol design, data analysis, evidence insights, and academic writing. The licence is MIT.

When your agent uses it

You need to read/write MS formats (mzML/mzXML/MGF)
Run signal processing (smoothing/peak picking)
Detect isotope features
Perform peptide identification in proteomics/metabolomics workflows

Example prompts

“/pyopenms-skill”

Requirements

Python 3

Workflow steps

3 steps, taken from the first numbered list in SKILL.md.

Load an MS run from disk (e.g., mzML).
Process spectra (optional filtering/smoothing/baseline correction).
Analyze results (e.g., peak picking, feature detection, or downstream summaries).

What it can do on your machine

Read from SKILL.md and the folder at commit 686e09d. It shows what the files ask for, not the result of running them.

Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Ships 1 file in scripts/ (Python), which the agent can run.
Shell commands in SKILL.md call:
- uv
- python
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md. Its commands use uv, which can reach the network depending on how they are called.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Pyopenms Skill loads about 852 tokens when it runs, and up to ~1.2k if it reads all its reference files. Until then it costs about 73 tokens; SKILL.md has 264 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it: ~73
When it runs · the whole SKILL.md, loaded when a task matches: ~852
With references · SKILL.md plus every file in references/, read only if the agent opens them: ~1.2k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from aipoch/medical-research-skills at commit 686e09d, republished under its MIT licence (© aipoch). 264 words, ~852 tokens.

Download SKILL.mdSave it as .claude/skills/pyopenms-skill/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.

name: pyopenms-skill
description: Comprehensive tool for computational mass spectrometry using PyOpenMS; use when you need to read/write MS formats (mzML/mzXML/MGF), run signal processing (smoothing/peak picking), detect isotope features, or perform peptide identification in proteomics/metabolomics workflows.
license: MIT
author: AIPOCH

Source: https://github.com/aipoch/medical-research-skills

When to Use

Converting, validating, or batch-processing mass spectrometry files (e.g., mzML, mzXML, MGF) as part of a pipeline.
Cleaning raw spectra before downstream analysis (smoothing, baseline correction, denoising, peak picking).
Detecting and linking isotope patterns / features for proteomics or metabolomics feature tables.
Running identification-oriented steps where peptide/protein identification integration is required.
Building custom computational MS workflows in Python while leveraging OpenMS algorithms.

Key Features

MS File I/O: Read/write common MS formats (mzML, mzXML, MGF).
Signal Processing: Smoothing, baseline correction, filtering, and peak picking.
Feature Detection: Isotope pattern detection and feature linking utilities.
Identification Support: Hooks for peptide identification workflows via OpenMS-compatible components.
Scripted Workflows: A ready-to-use “Load → Process → Analyze” workflow entry point.

Dependencies

Install the following Python packages:

pyopenms (version: compatible with your OpenMS/PyOpenMS distribution)
pandas (version: latest recommended)
numpy (version: latest recommended)

Installation:

bash

uv pip install pyopenms pandas numpy

Example Usage

A complete runnable example using the provided workflow script (scripts/process_ms.py):

python

# run_example.py
from scripts.process_ms import run_workflow

def main():
    # Load -> Process -> Analyze
    # The script is expected to read the input mzML and apply optional filtering.
    result = run_workflow("data.mzML", apply_filter=True)

    # The returned object depends on the implementation of run_workflow.
    # Common patterns include a processed experiment, a feature map, or a summary dict.
    print("Workflow finished.")
    print(result)

if __name__ == "__main__":
    main()

Run:

bash

python run_example.py

For manual/custom workflows, see:

File operations: references/file_io.md
Signal processing algorithms: references/signal_processing.md

Implementation Details

Binding Layer: This skill uses PyOpenMS, the Python bindings for the OpenMS C++ library, to expose core computational MS algorithms.
Workflow Pattern: The default script follows a standard pipeline structure:
1. Load an MS run from disk (e.g., mzML).
2. Process spectra (optional filtering/smoothing/baseline correction).
3. Analyze results (e.g., peak picking, feature detection, or downstream summaries).
Configurable Processing: The apply_filter flag in run_workflow(...) is intended to toggle one or more preprocessing steps; exact filters and parameters should be documented in scripts/process_ms.py and the referenced guides.
Algorithm Reference: Detailed descriptions of available filters and peak pickers, including parameterization, are maintained in references/signal_processing.md.

Files

SKILL.md and 4 other files (scripts, references) in scientific-skills/Data Analysis/pyopenms-skill of aipoch/medical-research-skills.

SKILL.md
pyopenms-skill_audit_result_v1.json
references/file_io.md
references/signal_processing.md
scripts/process_ms.py

Open the folder on GitHubat commit 686e09d

Compare with similar skills

Pyopenms Skill next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Pyopenms Skill compared with similar skills
Skill	Stars	Used in	Tokens	Auto-check	Licence	Repo updated
Pyopenms Skill this skillaipoch/medical-research-skills	2k	—	~852	Automated safety check: Pass	MIT	20 days ago
Pyopenmsdavila7/claude-code-templates	32k	12 repos	~1.4k	Automated safety check: Pass	MIT	yesterday
Bio Metagenomics VisualizationGPTomics/bioSkills	1.2k	1 repos	~3.7k	Automated safety check: Pass	MIT	1 mo ago
Bio Proteomics Differential AbundanceGPTomics/bioSkills	1.2k	1 repos	~5.7k	Automated safety check: Pass	MIT	1 mo ago
Bio Splicing QcFreedomIntelligence/OpenClaw-Medical-Skills	3.1k	—	~1.6k	Automated safety check: Pass	None	2 mo ago
PyDESeq2 Differential Expressiondavila7/claude-code-templates	32k	12 repos	~4k	Automated safety check: Pass	MIT	yesterday

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Questions about Pyopenms Skill

What does Pyopenms Skill do?

Comprehensive tool for computational mass spectrometry using PyOpenMS; use when you need to read/write MS formats (mzML/mzXML/MGF), run signal processing (smoothing/peak picking), detect isotope…. Pyopenms Skill is an agent skill from aipoch/medical-research-skills. Comprehensive tool for computational mass spectrometry using PyOpenMS; use when you need to read/write MS formats (mzML/mzXML/MGF), run signal processing (smoothing/peak picking), detect isotope features, or perform peptide identification in proteomics/metabolomics workflows.

When should I use Pyopenms Skill?

Pyopenms Skill fits situations like: you need to read/write MS formats (mzML/mzXML/MGF); run signal processing (smoothing/peak picking); detect isotope features; perform peptide identification in proteomics/metabolomics workflows.

How do I install Pyopenms Skill in Claude Code?

Run `npx skills add aipoch/medical-research-skills --skill pyopenms-skill -a claude-code`. Or copy the skill folder (scientific-skills/Data Analysis/pyopenms-skill in aipoch/medical-research-skills) into .claude/skills/pyopenms-skill in your project. Claude Code loads it when a task matches its description.

How do I install Pyopenms Skill in Codex?

Run `npx skills add aipoch/medical-research-skills --skill pyopenms-skill -a codex`. Or copy the skill folder (scientific-skills/Data Analysis/pyopenms-skill in aipoch/medical-research-skills) into .agents/skills/pyopenms-skill in your project. Codex loads it when a task matches its description.

Can I use Pyopenms Skill in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add aipoch/medical-research-skills --skill pyopenms-skill -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/pyopenms-skill, .gemini/skills/pyopenms-skill, .github/skills/pyopenms-skill and .opencode/skills/pyopenms-skill in your project.

What does Pyopenms Skill need to run?

Going by SKILL.md and its folder, Pyopenms Skill needs Python for the scripts in its folder and the command-line tools its instructions call (uv and python). Our summary lists: Python 3.

Does Pyopenms Skill access the network?

SKILL.md contains no URLs. Its commands use uv, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Pyopenms Skill safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Pyopenms Skill use?

Pyopenms Skill is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Pyopenms Skill use?

About 852 tokens (SKILL.md is roughly 3.4k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 302 tokens, read only when the agent opens those files.

What are the alternatives to Pyopenms Skill?

Skills that share tags, products or a category with Pyopenms Skill: Pyopenms (davila7/claude-code-templates, 32k stars), Bio Metagenomics Visualization (GPTomics/bioSkills, 1.2k stars), Bio Proteomics Differential Abundance (GPTomics/bioSkills, 1.2k stars) and Bio Splicing Qc (FreedomIntelligence/OpenClaw-Medical-Skills, 3.1k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Pyopenms Skill?

aipoch (a GitHub organization) maintains it in aipoch/medical-research-skills, which has 1,973 GitHub stars. The repository holds 567 skills in this directory. The repository was last updated on September 17, 2026.

Source: aipoch/medical-research-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.

Pyopenms Skill

Install Pyopenms Skill

Facts

At a glance

What it does

When your agent uses it

Example prompts

Requirements

Workflow steps

What it can do on your machine

Tool permissions

Runs code

Network

Credentials

Context cost

Safety

SKILL.md

When to Use

Key Features

Dependencies

Example Usage

Implementation Details

Files

Compare with similar skills

Similar skills

Pyopenms

Bio Metagenomics Visualization

Bio Proteomics Differential Abundance

Bio Splicing Qc

PyDESeq2 Differential Expression

FBA Flux Analyzer

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Questions about Pyopenms Skill

Install Pyopenms Skill

Facts

At a glance

What it does

When your agent uses it

Example prompts

Requirements

Workflow steps

What it can do on your machine

Tool permissions

Runs code

Network

Credentials

Context cost

Safety

SKILL.md

When to Use

Key Features

Dependencies

Example Usage

Implementation Details

Files

Compare with similar skills

Similar skills

More from aipoch/medical-research-skills

Related

Questions about Pyopenms Skill