Data Table Analysis
NVIDIA-AI-Blueprints/deep-researcher-agent
A skill your agent uses for converting researched facts or user-provided data into structured tables by writing code, then running Python/pandas calculations in the job-scoped sandbox.
Load when imputing missing values (min / median / KNN) and normalising (TIC / median / log) a feature × sample metabolomics CSV.
Install Metabolomics Quantification
$ npx skills add TianGzlab/OmicsClaw --skill metabolomics-quantification -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install TianGzlab/OmicsClaw metabolomics-quantification --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/TianGzlab/OmicsClaw.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/metabolomics/metabolomics-quantification .claude/skills/metabolomics-quantification && rm -rf skills-srcUse ~/.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/
Install the "metabolomics-quantification" agent skill from https://github.com/TianGzlab/OmicsClaw/tree/main/skills/metabolomics/metabolomics-quantification into .claude/skills/metabolomics-quantification/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "metabolomics-quantification", 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 install https://github.com/TianGzlab/OmicsClaw/tree/main/skills/metabolomics/metabolomics-quantificationType 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.
$ npx skills add TianGzlab/OmicsClaw --skill metabolomics-quantification -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install TianGzlab/OmicsClaw metabolomics-quantification --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/TianGzlab/OmicsClaw.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/metabolomics/metabolomics-quantification .agents/skills/metabolomics-quantification && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "metabolomics-quantification" agent skill from https://github.com/TianGzlab/OmicsClaw/tree/main/skills/metabolomics/metabolomics-quantification into .agents/skills/metabolomics-quantification/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "metabolomics-quantification", 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.
$ npx skills add TianGzlab/OmicsClaw --skill metabolomics-quantification -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install TianGzlab/OmicsClaw metabolomics-quantification --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/TianGzlab/OmicsClaw.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/metabolomics/metabolomics-quantification .cursor/skills/metabolomics-quantification && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "metabolomics-quantification" agent skill from https://github.com/TianGzlab/OmicsClaw/tree/main/skills/metabolomics/metabolomics-quantification into .cursor/skills/metabolomics-quantification/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "metabolomics-quantification", 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 https://github.com/TianGzlab/OmicsClaw.git --path skills/metabolomics/metabolomics-quantification--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add TianGzlab/OmicsClaw --skill metabolomics-quantification -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install TianGzlab/OmicsClaw metabolomics-quantification --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/TianGzlab/OmicsClaw.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/metabolomics/metabolomics-quantification .gemini/skills/metabolomics-quantification && rm -rf skills-srcUse ~/.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/
Install the "metabolomics-quantification" agent skill from https://github.com/TianGzlab/OmicsClaw/tree/main/skills/metabolomics/metabolomics-quantification into .gemini/skills/metabolomics-quantification/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "metabolomics-quantification", 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.
$ gh skill install TianGzlab/OmicsClaw metabolomics-quantificationInstalls 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).
$ npx skills add TianGzlab/OmicsClaw --skill metabolomics-quantification -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/TianGzlab/OmicsClaw.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/metabolomics/metabolomics-quantification .github/skills/metabolomics-quantification && rm -rf skills-srcUse ~/.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/
Install the "metabolomics-quantification" agent skill from https://github.com/TianGzlab/OmicsClaw/tree/main/skills/metabolomics/metabolomics-quantification into .github/skills/metabolomics-quantification/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "metabolomics-quantification", 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.
$ npx skills add TianGzlab/OmicsClaw --skill metabolomics-quantification -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install TianGzlab/OmicsClaw metabolomics-quantification --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/TianGzlab/OmicsClaw.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/metabolomics/metabolomics-quantification .opencode/skills/metabolomics-quantification && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "metabolomics-quantification" agent skill from https://github.com/TianGzlab/OmicsClaw/tree/main/skills/metabolomics/metabolomics-quantification into .opencode/skills/metabolomics-quantification/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "metabolomics-quantification", 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
metabolomics-quantification- GitHub stars
- 161
- Token cost
- ~916 tokens
- SKILL.md length
- 322 words
- Files
- 8 (incl. references)
- Skills in repo
- 88
- Repo updated
- First seen
- Licence
- Apache-2.0
At a glance
Load when imputing missing values (min / median / KNN) and normalising (TIC / median / log) a feature × sample metabolomics CSV.
- Tasks that involve Database schema design
- SKILL.md covers When to use, Use from a step, API and Methods and parameters, plus 5 more sections
- Runs Python scripts from its folder; calls python
- Tasks that involve Data cleaning
What it does
Metabolomics Quantification is an agent skill from TianGzlab/OmicsClaw. Load when imputing missing values (min / median / KNN) and normalising (TIC / median / log) a feature × sample metabolomics CSV. Skip when only normalisation is needed (use metabolomics-normalization); the input is raw spectra (use metabolomics-xcms-preprocessing).
Its SKILL.md is about 920 tokens, which your agent loads only when the skill is triggered. The skill folder holds 10 other files, including reference files (for example `_api.py`, `examples/example_step.py` and `met_quantify.py`).
It sits in Data & Analytics, covering Database schema design, Data cleaning 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 Apache-2.0.
When your agent uses it
- Tasks that involve Database schema design
- Tasks that involve Data cleaning
- Tasks that involve CSV and tabular files
Example prompts
- “/metabolomics-quantification”
Requirements
- Python 3
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 Quantification loads about 916 tokens when it runs, and up to ~1.3k if it reads all its reference files. Until then it costs about 73 tokens; SKILL.md has 322 words of instructions outside code blocks.
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). 322 words, ~916 tokens.
Download SKILL.mdSave it as
.claude/skills/metabolomics-quantification/SKILL.md (or your agent's skills folder). This skill also uses 7 other files; get the full folder from GitHub.- name
- metabolomics-quantification
- description
- Load when imputing missing values (min / median / KNN) and normalising (TIC / median / log) a feature × sample metabolomics CSV. Skip when only normalisation is needed (use metabolomics-normalization); the input is raw spectra (use metabolomics-xcms-preprocessing).
- trigger
- metabolomics quantification, imputation, feature quantification, missing values
- tags
- metabolomics, quantification, imputation, normalization, knn, tic
metabolomics-quantification
When to use
Impute zeros/NaNs and normalize sample intensities while keeping feature metadata. Use metabolomics-normalization for normalization alone.
Use from a step
import pandas as pd
from skills._sdk.notebook import load_skill, read_input, write_output
library = load_skill("metabolomics-quantification")
data = read_input('features.csv', reader=pd.read_csv)
result = library.quantify(data)
write_output(result, 'tables/result.csv')examples/example_step.py runs a seeded synthetic
example through the step runner and writes a table and Figure. Computations
return new DataFrames, leave the input unchanged and expose diagnostics through
run_info(result). Plotting functions write no files.
API
<!-- api:begin generated from _api.py; regenerate with run.py api <skill dir> --write -->quantify(data, *, impute='min', normalize='tic')
Return imputed and normalized intensities with metadata preserved.
:param data: Feature table with sample/intensity columns; zeros and NaNs are missing. :param impute: CLI default min (half global positive minimum); median or knn also work. :param normalize: CLI default tic; median or log are alternatives. :returns: A new DataFrame with missing-value counts in attrs['run_info']. :raises ValueError: Samples are absent, have no positive observations or a method is unknown. :raises ImportError: KNN requires scikit-learn; use install_skill_deps.
run_info(data, *, keep=True)
Read diagnostics attached to a returned table.
:param data: DataFrame returned by this library. :param keep: Default True; use False in the CLI to remove diagnostics. :returns: An independent dictionary describing the run. :raises ValueError: The table carries no run_info.
distribution_figure(data)
Plot sample intensities, excluding numeric feature metadata.
:param data: The input or quantified feature table. :returns: A matplotlib Figure. :raises ValueError: No numeric sample columns are available.
<!-- api:end -->Methods and parameters
Min imputation uses half the global positive minimum, median uses each column positive median, and KNN uses neighbouring feature rows with up to five neighbours. TIC scales column sums to their median; median scales column medians; log computes log2(x+1).
Gotchas
quantifydetects sample/intensity prefixes, then numeric columns excluding feature_id, mz, rt, name and id. Every sample needs a positive observed intensity; completely missing samples raise ValueError for all methods.
Inputs and outputs
CSV input; tables/quantified_features.csv, report.md and result.json. Demo mode also writes its synthetic input CSV at the output root.
The function library returns objects; the CLI and step own file writes.
CLI
python skills/metabolomics/metabolomics-quantification/met_quantify.py --demo --output /tmp/metabolomics_quantificationSee also
Dependencies
numpy, pandas, scikit-learn, matplotlib
© 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 7 other files (references) in skills/metabolomics/metabolomics-quantification of TianGzlab/OmicsClaw.
- SKILL.md
- _api.py
- examples/example_step.py
- met_quantify.py
- references/methodology.md
- references/output_contract.md
- references/parameters.md
- tests/test_api.py
Open the folder on GitHubat commit 90a3bec
Compare with similar skills
Metabolomics Quantification 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.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Metabolomics Quantification this skillTianGzlab/OmicsClaw | 161 | — | ~916 | Automated safety check: Pass | Apache-2.0 | |
| Data Table AnalysisNVIDIA-AI-Blueprints/deep-researcher-agent | 883 | — | ~2.5k | Automated safety check: Pass | Apache-2.0 | |
| Verified Data Analysis with pandaspipeshub-ai/pipeshub-ai | 3.8k | — | ~1.2k | Automated safety check: Pass | Apache-2.0 | |
| Portaljs Check Data Qualitydatopian/portaljs | 2.4k | 1 repos | ~1.5k | Automated safety check: Pass | MIT | |
| Dataset Quality Auditzebbern/claude-code-guide | 4.7k | — | ~996 | Automated safety check: Pass | MIT | |
| Splitting Datasetsjeremylongshore/tons-of-skills-marketplace | 2.8k | 1 repos | ~836 | Automated safety check: Pass | MIT |
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Categories
Questions about Metabolomics Quantification
What does Metabolomics Quantification do?
Load when imputing missing values (min / median / KNN) and normalising (TIC / median / log) a feature × sample metabolomics CSV. Metabolomics Quantification is an agent skill from TianGzlab/OmicsClaw. Load when imputing missing values (min / median / KNN) and normalising (TIC / median / log) a feature × sample metabolomics CSV.
When should I use Metabolomics Quantification?
Metabolomics Quantification fits situations like: tasks that involve Database schema design; tasks that involve Data cleaning; tasks that involve CSV and tabular files.
How do I install Metabolomics Quantification in Claude Code?
Run `npx skills add TianGzlab/OmicsClaw --skill metabolomics-quantification -a claude-code`. Or copy the skill folder (skills/metabolomics/metabolomics-quantification in TianGzlab/OmicsClaw) into .claude/skills/metabolomics-quantification in your project. Claude Code loads it when a task matches its description.
How do I install Metabolomics Quantification in Codex?
Run `npx skills add TianGzlab/OmicsClaw --skill metabolomics-quantification -a codex`. Or copy the skill folder (skills/metabolomics/metabolomics-quantification in TianGzlab/OmicsClaw) into .agents/skills/metabolomics-quantification in your project. Codex loads it when a task matches its description.
Can I use Metabolomics Quantification 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-quantification -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-quantification, .gemini/skills/metabolomics-quantification, .github/skills/metabolomics-quantification and .opencode/skills/metabolomics-quantification in your project.
What does Metabolomics Quantification need to run?
Going by SKILL.md and its folder, Metabolomics Quantification needs Python for the scripts in its folder and the command-line tools its instructions call (python). Our summary lists: Python 3.
Does Metabolomics Quantification 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 Quantification 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 Quantification use?
Metabolomics Quantification 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 Quantification use?
About 916 tokens (SKILL.md is roughly 3.7k 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 363 tokens, read only when the agent opens those files.
What are the alternatives to Metabolomics Quantification?
Skills that share tags, products or a category with Metabolomics Quantification: Data Table Analysis (NVIDIA-AI-Blueprints/deep-researcher-agent, 883 stars), Verified Data Analysis with pandas (pipeshub-ai/pipeshub-ai, 3.8k stars), Portaljs Check Data Quality (datopian/portaljs, 2.4k stars) and Dataset Quality Audit (zebbern/claude-code-guide, 4.7k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Metabolomics Quantification?
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.