Pyopenms

What it does

When your agent uses it

• LC-MS/MS proteomics and metabolomics workflows including file handling (mzML
• Signal processing
• Feature detection
• Peptide identification

Example prompts

• “/pyopenms”

Requirements

• Python 3

Workflow steps

5 steps, taken from the step headings in SKILL.md.

1. 1File I/O and Data Formats
2. 2Signal Processing
3. 3Feature Detection
4. 4Peptide and Protein Identification
5. 5Metabolomics Analysis

What it can do on your machine

Read from SKILL.md and the folder at commit 4c82aba. 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

  Shell commands in SKILL.md call:

  • uv

  From the folder's file list and the shell code blocks in SKILL.md.

• Network

  Links to these hosts (documentation or services it may open):

  • pyopenms.readthedocs.io
  • openms.org
  • github.com

  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 loads about 1.4k tokens when it runs, and up to ~18k if it reads all its reference files. Until then it costs about 104 tokens; SKILL.md has 346 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it

~104

When it runs · the whole SKILL.md, loaded when a task matches

~1.4k

With references · SKILL.md plus every file in references/, read only if the agent opens them

~18k

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

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); files beside SKILL.md are not scanned.

SKILL.md

The full file from davila7/claude-code-templates at commit 4c82aba, republished under its MIT licence (© davila7). 346 words, ~1,407 tokens.

name

pyopenms

description

Python interface to OpenMS for mass spectrometry data analysis. Use for LC-MS/MS proteomics and metabolomics workflows including file handling (mzML, mzXML, mzTab, FASTA, pepXML, protXML, mzIdentML), signal processing, feature detection, peptide identification, and quantitative analysis. Apply when working with mass spectrometry data, analyzing proteomics experiments, or processing metabolomics datasets.

uv uv pip install pyopenms

import pyopenms
print(pyopenms.__version__)

import pyopenms as ms

# Read mzML file
exp = ms.MSExperiment()
ms.MzMLFile().load("data.mzML", exp)

# Access spectra
for spectrum in exp:
    mz, intensity = spectrum.get_peaks()
    print(f"Spectrum: {len(mz)} peaks")

# Smooth spectrum with Gaussian filter
gaussian = ms.GaussFilter()
params = gaussian.getParameters()
params.setValue("gaussian_width", 0.1)
gaussian.setParameters(params)
gaussian.filterExperiment(exp)

# Detect features
ff = ms.FeatureFinder()
ff.run("centroided", exp, features, params, ms.FeatureMap())

# Load identification data
protein_ids = []
peptide_ids = []
ms.IdXMLFile().load("identifications.idXML", protein_ids, peptide_ids)

# Apply FDR filtering
fdr = ms.FalseDiscoveryRate()
fdr.apply(peptide_ids)

import pyopenms as ms

# Load mzML file
exp = ms.MSExperiment()
ms.MzMLFile().load("sample.mzML", exp)

# Get basic statistics
print(f"Number of spectra: {exp.getNrSpectra()}")
print(f"Number of chromatograms: {exp.getNrChromatograms()}")

# Examine first spectrum
spec = exp.getSpectrum(0)
print(f"MS level: {spec.getMSLevel()}")
print(f"Retention time: {spec.getRT()}")
mz, intensity = spec.get_peaks()
print(f"Peaks: {len(mz)}")

# Get algorithm parameters
algo = ms.GaussFilter()
params = algo.getParameters()

# View available parameters
for param in params.keys():
    print(f"{param}: {params.getValue(param)}")

# Modify parameters
params.setValue("gaussian_width", 0.2)
algo.setParameters(params)

import pyopenms as ms
import pandas as pd

# Load feature map
fm = ms.FeatureMap()
ms.FeatureXMLFile().load("features.featureXML", fm)

# Convert to DataFrame
df = fm.get_df()
print(df.head())

© davila7, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 6 other files (references) in cli-tool/components/skills/scientific/pyopenms of davila7/claude-code-templates.

• SKILL.md
• references/data_structures.md
• references/feature_detection.md
• references/file_io.md
• references/identification.md
• references/metabolomics.md
• references/signal_processing.md

Open the folder on GitHubat commit 4c82aba

Used in 12 other repositories

We found 27 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 12 other GitHub owners. This page covers the copy in davila7/claude-code-templates, which our catalogue first saw on October 7, 2026.

• jimmc414/Kosmoskosmos-claude-scientific-skills/scientific-skills/pyopenms
• Microck/ordinary-claude-skillsskills_all/pyopenmsskills_categorized/lab-tools/pyopenms+2 more
• aiskillstore/marketplaceskills/davila7/pyopenmsskills/k-dense-ai/pyopenms
• majiayu000/claude-skill-registryskills/ai-ml/scientific-pyopenmsskills/analysis/scientific-pkg-pyopenms+10 more
• lamm-mit/scienceclawskills/pyopenms
• agent-skills-hub/agent-skills-hubskills/pyopenms
• foryourhealth111-pixel/Vibe-Skillsbundled/skills/pyopenms
• LeonChaoX/qinyan-academic-skillsskills/06-化学信息与药物发现/pyopenms
• wu-yc/LabClawskills/bio/pyopenms
• FreedomIntelligence/OpenClaw-Medical-Skillsskills/pyopenms
• BioTender-max/awesome-bio-agent-skillsskills/kdense/pyopenms
• infometa/workbuddyskillsplugins/codebuddy-plugins-official/external_plugins/scientific-skills/pyopenms