Agent skill

Proteomics Data Import

by TianGzlab in TianGzlab/OmicsClaw

Load when ingesting a MaxQuant proteinGroups.txt, FragPipe combinedprotein.tsv, DIA-NN report, or generic CSV / TSV protein-quantification table — normalises columns to a standard schema, emits…

MITAuto-check passedResearch & Science

Install Proteomics Data Import

skills CLI
$ npx skills add TianGzlab/OmicsClaw --skill proteomics-data-import -a claude-code

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

GitHub CLI
$ gh skill install TianGzlab/OmicsClaw proteomics-data-import --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/proteomics/proteomics-data-import .claude/skills/proteomics-data-import && 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
proteomics-data-import
GitHub stars
161
Token cost
~1.1k tokens
SKILL.md length
303 words
Files
6 (incl. references)
Skills in repo
95
Repo updated
First seen
Licence
MIT

At a glance

Load when ingesting a MaxQuant proteinGroups.txt, FragPipe combinedprotein.tsv, DIA-NN report, or generic CSV / TSV protein-quantification table — normalises columns to a standard schema, emits…

  • Works in 4 steps: Load input (--input ) or generate a demo… → Dispatch to the format-specific importer… → Rename columns: LFQ intensity → LFQ_ and… → …
  • Tasks that involve Bioinformatics
  • SKILL.md covers When to use, Inputs & Outputs, Flow and Gotchas, plus 2 more sections
  • Runs Python scripts from its folder; calls python

What it does

Proteomics Data Import is an agent skill from TianGzlab/OmicsClaw. Load when ingesting a MaxQuant proteinGroups.txt, FragPipe combinedprotein.tsv, DIA-NN report, or generic CSV / TSV protein-quantification table — normalises columns to a standard schema, emits tables/proteins.csv. Skip when raw spectra are the input (run the search engine first); the file is already OmicsClaw schema.

Its SKILL.md is about 1.1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 6 other files, including reference files (for example `proteomics_data_import.py`, `references/methodology.md` and `references/output_contract.md`).

It sits in Research & Science, covering Bioinformatics and CSV and tabular files. 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 MIT.

When your agent uses it

  • Tasks that involve Bioinformatics
  • Tasks that involve CSV and tabular files

Example prompts

  • “/proteomics-data-import”

Requirements

  • Python 3

Workflow steps

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

  1. Load input (--input ) or generate a demo MaxQuant-shaped file (--demo).
  2. Dispatch to the format-specific importer (proteomics_data_import.py:164-174 _dispatch_import); supported keys are maxquant, fragpipe…
  3. Rename columns: LFQ intensity → LFQ_ and Intensity → Int_ (proteomics_data_import.py:85); Majority protein IDs → protein_id; Gene names →…
  4. Write tables/proteins.csv (proteomics_data_import.py:284) + report.md + result.json (:299).

What it can do on your machine

Read from SKILL.md and the folder at commit 6fbd79f. 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

Proteomics Data Import loads about 1.1k tokens when it runs, and up to ~1.6k if it reads all its reference files. Until then it costs about 87 tokens; SKILL.md has 303 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~87
When it runs · the whole SKILL.md, loaded when a task matches
~1.1k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~1.6k

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 6fbd79f, republished under its MIT licence (© TianGzlab). 303 words, ~1,133 tokens.

Download SKILL.mdSave it as .claude/skills/proteomics-data-import/SKILL.md (or your agent's skills folder). This skill also uses 5 other files; get the full folder from GitHub.
name
proteomics-data-import
description
Load when ingesting a MaxQuant `proteinGroups.txt`, FragPipe `combined_protein.tsv`, DIA-NN report, or generic CSV / TSV protein-quantification table — normalises columns to a standard schema, emits `tables/proteins.csv`. Skip when raw spectra are the input (run the search engine first); the file is already OmicsClaw schema.
version
0.5.0
author
OmicsClaw
license
MIT
emoji
📥
tags
proteomics, import, maxquant, fragpipe, diann, spectronaut
requires
numpy, pandas

proteomics-data-import

When to use

The user has a search-engine output (MaxQuant proteinGroups.txt, FragPipe combined_protein.tsv, DIA-NN main report, or a generic CSV / TSV protein table) and wants it normalised into OmicsClaw's standard schema (lowercase protein_id plus LFQ_<sample> / Int_<sample> intensity columns derived from MaxQuant's LFQ intensity ... / Intensity ... headers). Pick the format with --format {maxquant,fragpipe,diann,generic} (default maxquant).

For raw MS spectra (mzML / RAW), run a search engine first (MaxQuant / FragPipe / DIA-NN) and feed THIS skill the resulting table.

Inputs & Outputs

<!-- AUTO-GENERATED from skill.yaml (interface) — do not edit by hand. Regenerate: python scripts/generate_skill_md.py <skill_dir> -->

Inputs

  • File types: .txt, .tsv, .csv

Outputs

  • tables/proteins.csv
  • report.md
  • result.json

Flow

  1. Load input (--input <file>) or generate a demo MaxQuant-shaped file (--demo).
  2. Dispatch to the format-specific importer (proteomics_data_import.py:164-174 _dispatch_import); supported keys are maxquant, fragpipe, diann, generic.
  3. Rename columns: LFQ intensity <sample> → LFQ_<sample> and Intensity <sample> → Int_<sample> (proteomics_data_import.py:85); Majority protein IDs → protein_id; Gene names → gene_name; etc.
  4. Write tables/proteins.csv (proteomics_data_import.py:284) + report.md + result.json (:299).

Gotchas

  • --format value must match _dispatch_import keys exactly. proteomics_data_import.py:166-171 registers maxquant, fragpipe, diann, generic. An unknown value raises ValueError("Unsupported format: ... Supported: ['maxquant', 'fragpipe', 'diann', 'generic']") at :173. There is no spectronaut importer despite the legacy SKILL.md mention — use --format generic for Spectronaut and rename columns yourself.
  • --input REQUIRED unless --demo. proteomics_data_import.py:275 raises ValueError("--input required when not using --demo"). Non-existent paths raise FileNotFoundError from pd.read_csv.
  • Output schema is LOWERCASE. Column renaming targets protein_id, intensity_<sample>, gene_name etc. Downstream skills (proteomics-quantification, proteomics-de) assume this casing. Verify after import with head tables/proteins.csv.
  • No deduplication of contaminants / decoys. Contaminant (CON_*) and decoy (REV_*) rows are passed through unchanged. Filter them upstream with the search engine's --keep-contaminants false flag, or add a downstream df = df[~df["protein_id"].str.startswith(("CON_", "REV_"))] step.

Key CLI

bash
# Demo (synthetic MaxQuant-style)
python omicsclaw.py run proteomics-data-import --demo --output /tmp/import_demo

# Real MaxQuant output
python omicsclaw.py run proteomics-data-import \
  --input proteinGroups.txt --output results/ --format maxquant

# FragPipe combined_protein
python omicsclaw.py run proteomics-data-import \
  --input combined_protein.tsv --output results/ --format fragpipe

# DIA-NN main report
python omicsclaw.py run proteomics-data-import \
  --input report.tsv --output results/ --format diann

# Generic / Spectronaut (rename columns yourself first)
python omicsclaw.py run proteomics-data-import \
  --input my_table.csv --output results/ --format generic

See also

  • references/parameters.md — every CLI flag
  • references/methodology.md — per-format column-mapping rules
  • references/output_contract.md — tables/proteins.csv schema
  • Adjacent skills: proteomics-ms-qc (downstream — QC the imported table), proteomics-quantification (downstream — compute LFQ / iBAQ / spectral count), proteomics-identification (parallel — peptide-level summary), proteomics-de (downstream — differential abundance after import)

© TianGzlab, 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 5 other files (references) in skills/proteomics/proteomics-data-import of TianGzlab/OmicsClaw.

  • SKILL.md
  • proteomics_data_import.py
  • references/methodology.md
  • references/output_contract.md
  • references/parameters.md
  • skill.yaml

Open the folder on GitHubat commit 6fbd79f

Compare with similar skills

Proteomics Data Import 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.

Proteomics Data Import compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Proteomics Data Import this skillTianGzlab/OmicsClaw161—~1.1kAutomated safety check: PassMIT
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Plannotate Plasmid Annotationjaechang-hits/SciAgent-Skills3701 repos~4.7kAutomated safety check: PassGPL-3.0
Vdjdb Extractantigenomics/vdjdb-db157—~1.2kAutomated safety check: PassCustom licence
Ukb Ppp Region FetchClawBio/ClawBio1.2k—~4.6kAutomated safety check: PassMIT

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Questions about Proteomics Data Import

What does Proteomics Data Import do?

Load when ingesting a MaxQuant proteinGroups.txt, FragPipe combinedprotein.tsv, DIA-NN report, or generic CSV / TSV protein-quantification table — normalises columns to a standard schema, emits…. Proteomics Data Import is an agent skill from TianGzlab/OmicsClaw.csv.

When should I use Proteomics Data Import?

Proteomics Data Import fits situations like: tasks that involve Bioinformatics; tasks that involve CSV and tabular files.

How do I install Proteomics Data Import in Claude Code?

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

How do I install Proteomics Data Import in Codex?

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

Can I use Proteomics Data Import 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 proteomics-data-import -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/proteomics-data-import, .gemini/skills/proteomics-data-import, .github/skills/proteomics-data-import and .opencode/skills/proteomics-data-import in your project.

What does Proteomics Data Import need to run?

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

Does Proteomics Data Import 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 Proteomics Data Import 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 Proteomics Data Import use?

Proteomics Data Import 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 Proteomics Data Import use?

About 1.1k tokens (SKILL.md is roughly 4.5k 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 445 tokens, read only when the agent opens those files.

What are the alternatives to Proteomics Data Import?

Skills that share tags, products or a category with Proteomics Data Import: Spatial Xenium (QING1105/ezST, 101 stars), Cerna Analysis (aipoch/medical-research-skills, 2k stars), Plannotate Plasmid Annotation (jaechang-hits/SciAgent-Skills, 370 stars) and Vdjdb Extract (antigenomics/vdjdb-db, 157 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Proteomics Data Import?

TianGzlab (a GitHub organization) maintains it in TianGzlab/OmicsClaw, which has 161 GitHub stars. The repository holds 95 skills in this directory. The repository was last updated on July 28, 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.