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Agent skill

Metabolomics Xcms Preprocessing

by TianGzlab in TianGzlab/OmicsClaw

Load when exercising the CLI and replay pipeline with a synthetic LC-MS peak table.

Apache-2.0Auto-check passedData & Analytics

Install Metabolomics Xcms Preprocessing

skills CLI
$ npx skills add TianGzlab/OmicsClaw --skill metabolomics-xcms-preprocessing -a claude-code

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

GitHub CLI
$ gh skill install TianGzlab/OmicsClaw metabolomics-xcms-preprocessing --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/TianGzlab/OmicsClaw.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/metabolomics/metabolomics-xcms-preprocessing .claude/skills/metabolomics-xcms-preprocessing && 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/

Facts

Skill name
metabolomics-xcms-preprocessing
GitHub stars
161
Token cost
~566 tokens
SKILL.md length
208 words
Files
7 (incl. references)
Skills in repo
88
Repo updated
First seen
Licence
Apache-2.0

At a glance

Load when exercising the CLI and replay pipeline with a synthetic LC-MS peak table.

  • Works in 3 steps: Reject real input and invalid… → Generate a seeded synthetic peak table… → Write the CSV, report, result envelope…
  • Data & Analytics work in your project
  • SKILL.md covers When to use, Inputs & Outputs, Flow and Gotchas, plus 3 more sections
  • Runs Python scripts from its folder; calls python

What it does

Metabolomics Xcms Preprocessing is an agent skill from TianGzlab/OmicsClaw. Load when exercising the CLI and replay pipeline with a synthetic LC-MS peak table. Skip real mzML preprocessing (run XCMS externally); table peak picking belongs to metabolomics-peak-detection.

Its SKILL.md is about 570 tokens, which your agent loads only when the skill is triggered. The skill folder holds 9 other files, including reference files (for example `examples/example_step.py`, `metabolomics_xcms_preprocessing.py` and `references/methodology.md`).

It sits in Data & Analytics. The repository describes itself as: Conversational & memory-enabled AI research partner for multi-omics analysis. CLI + Desktop App (installers in Releases). From biological idea to full research paper. The licence is Apache-2.0.

When your agent uses it

  • Data & Analytics work in your project

Example prompts

  • “/metabolomics-xcms-preprocessing”

Requirements

  • Python 3

Workflow steps

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

  1. Reject real input and invalid ppm/peak-width settings.
  2. Generate a seeded synthetic peak table using the supplied demo parameters.
  3. Write the CSV, report, result envelope and command record.

What it can do on your machine

Read from SKILL.md and the folder at commit 90a3bec. 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 script files (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • python

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

  • Network

    No URLs in SKILL.md.

    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

Metabolomics Xcms Preprocessing loads about 566 tokens when it runs, and up to ~826 if it reads all its reference files. Until then it costs about 57 tokens; SKILL.md has 208 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~57
When it runs · the whole SKILL.md, loaded when a task matches
~566
With references · SKILL.md plus every file in references/, read only if the agent opens them
~826

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); files beside SKILL.md are not scanned.

SKILL.md

The full file from TianGzlab/OmicsClaw at commit 90a3bec, republished under its Apache-2.0 licence (© TianGzlab). 208 words, ~566 tokens.

Download SKILL.mdSave it as .claude/skills/metabolomics-xcms-preprocessing/SKILL.md (or your agent's skills folder). This skill also uses 6 other files; get the full folder from GitHub.
name
metabolomics-xcms-preprocessing
description
Load when exercising the CLI and replay pipeline with a synthetic LC-MS peak table. Skip real mzML preprocessing (run XCMS externally); table peak picking belongs to metabolomics-peak-detection.
trigger
xcms demo, synthetic metabolomics peaks
tags
metabolomics, demo, cli-only

metabolomics-xcms-preprocessing

When to use

This CLI generates synthetic peak tables only. It does not read mzML spectra, run XCMS, align retention times or perform gap filling. Real --input runs fail before writing results. Use XCMS externally for raw LC-MS analysis. The skill remains CLI-only because it has no implemented scientific analysis that can be exposed as a computational function library.

Inputs & Outputs

--demo needs no input. Outputs are tables/peak_table.csv, report.md, result.json and reproducibility/commands.sh. The table contains synthetic m/z bounds, retention-time bounds, integrated/maximum intensities and five sample columns. There are no Figures or AnnData outputs.

Flow

  1. Reject real input and invalid ppm/peak-width settings.
  2. Generate a seeded synthetic peak table using the supplied demo parameters.
  3. Write the CSV, report, result envelope and command record.

Gotchas

  • xcms_preprocess_python uses seed 42 and never reads spectra. The name is historical.
  • --demo --ppm 5 changes tables/peak_table.csv from 1,200 to 240 rows with default peak widths; these are simulated parameter responses.
  • result.json summary contains n_samples, n_peaks, mz_min, mz_max, rt_min and rt_max. They describe the simulation only.

Key CLI

bash
python skills/metabolomics/metabolomics-xcms-preprocessing/metabolomics_xcms_preprocessing.py --demo --output /tmp/xcms_demo

Steps call run_cli('metabolomics-xcms-preprocessing', '--demo'). examples/example_step.py records and checks the synthetic peak table through the step runner and fresh replay.

See also

Dependencies

numpy, pandas

© TianGzlab, Apache-2.0. 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 skills/metabolomics/metabolomics-xcms-preprocessing of TianGzlab/OmicsClaw.

  • SKILL.md
  • examples/example_step.py
  • metabolomics_xcms_preprocessing.py
  • references/methodology.md
  • references/output_contract.md
  • references/parameters.md
  • tests/test_cli.py

Open the folder on GitHubat commit 90a3bec

Compare with similar skills

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Categories

Questions about Metabolomics Xcms Preprocessing

What does Metabolomics Xcms Preprocessing do?

Load when exercising the CLI and replay pipeline with a synthetic LC-MS peak table. Metabolomics Xcms Preprocessing is an agent skill from TianGzlab/OmicsClaw. Load when exercising the CLI and replay pipeline with a synthetic LC-MS peak table.

When should I use Metabolomics Xcms Preprocessing?

Metabolomics Xcms Preprocessing fits situations like: data & Analytics work in your project.

How do I install Metabolomics Xcms Preprocessing in Claude Code?

Run `npx skills add TianGzlab/OmicsClaw --skill metabolomics-xcms-preprocessing -a claude-code`. Or copy the skill folder (skills/metabolomics/metabolomics-xcms-preprocessing in TianGzlab/OmicsClaw) into .claude/skills/metabolomics-xcms-preprocessing in your project. Claude Code loads it when a task matches its description.

How do I install Metabolomics Xcms Preprocessing in Codex?

Run `npx skills add TianGzlab/OmicsClaw --skill metabolomics-xcms-preprocessing -a codex`. Or copy the skill folder (skills/metabolomics/metabolomics-xcms-preprocessing in TianGzlab/OmicsClaw) into .agents/skills/metabolomics-xcms-preprocessing in your project. Codex loads it when a task matches its description.

Can I use Metabolomics Xcms Preprocessing 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 TianGzlab/OmicsClaw --skill metabolomics-xcms-preprocessing -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/metabolomics-xcms-preprocessing, .gemini/skills/metabolomics-xcms-preprocessing, .github/skills/metabolomics-xcms-preprocessing and .opencode/skills/metabolomics-xcms-preprocessing in your project.

What does Metabolomics Xcms Preprocessing need to run?

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

Does Metabolomics Xcms Preprocessing access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Metabolomics Xcms Preprocessing 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. Review the folder before installing.

What licence does Metabolomics Xcms Preprocessing use?

Metabolomics Xcms Preprocessing is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Metabolomics Xcms Preprocessing use?

About 566 tokens (SKILL.md is roughly 2.3k 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 260 tokens, read only when the agent opens those files.

What are the alternatives to Metabolomics Xcms Preprocessing?

Skills that share tags, products or a category with Metabolomics Xcms Preprocessing: Exploratory Data Analysis (spacering-net/codeg, 3.8k stars), Matplotlib (zLanqing/codex-claude-academic-skills, 4.6k stars), Scikit Learn (zLanqing/codex-claude-academic-skills, 4.6k stars) and Chart Visualization (bytedance/deer-flow, 83k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Metabolomics Xcms Preprocessing?

TianGzlab (a GitHub organization) maintains it in TianGzlab/OmicsClaw, which has 161 GitHub stars. The repository holds 88 skills in this directory. The repository was last updated on October 7, 2026.

Source: TianGzlab/OmicsClaw on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.