Matplotlib
zLanqing/codex-claude-academic-skills
Low-level plotting library for full customization. An agent skill from zLanqing/codex-claude-academic-skills.
Load when matching LC-MS m/z features to an explicit local metabolite reference within a ppm tolerance; bundled HMDB entries are for explicit demonstrations only.
Install Metabolomics Annotation
$ npx skills add TianGzlab/OmicsClaw --skill metabolomics-annotation -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install TianGzlab/OmicsClaw metabolomics-annotation --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-annotation .claude/skills/metabolomics-annotation && 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-annotation" agent skill from https://github.com/TianGzlab/OmicsClaw/tree/main/skills/metabolomics/metabolomics-annotation into .claude/skills/metabolomics-annotation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "metabolomics-annotation", 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-annotationType 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-annotation -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install TianGzlab/OmicsClaw metabolomics-annotation --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-annotation .agents/skills/metabolomics-annotation && 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-annotation" agent skill from https://github.com/TianGzlab/OmicsClaw/tree/main/skills/metabolomics/metabolomics-annotation into .agents/skills/metabolomics-annotation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "metabolomics-annotation", 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-annotation -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install TianGzlab/OmicsClaw metabolomics-annotation --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-annotation .cursor/skills/metabolomics-annotation && 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-annotation" agent skill from https://github.com/TianGzlab/OmicsClaw/tree/main/skills/metabolomics/metabolomics-annotation into .cursor/skills/metabolomics-annotation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "metabolomics-annotation", 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-annotation--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-annotation -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install TianGzlab/OmicsClaw metabolomics-annotation --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-annotation .gemini/skills/metabolomics-annotation && 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-annotation" agent skill from https://github.com/TianGzlab/OmicsClaw/tree/main/skills/metabolomics/metabolomics-annotation into .gemini/skills/metabolomics-annotation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "metabolomics-annotation", 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-annotationInstalls 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-annotation -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-annotation .github/skills/metabolomics-annotation && 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-annotation" agent skill from https://github.com/TianGzlab/OmicsClaw/tree/main/skills/metabolomics/metabolomics-annotation into .github/skills/metabolomics-annotation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "metabolomics-annotation", 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-annotation -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-annotation --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-annotation .opencode/skills/metabolomics-annotation && 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-annotation" agent skill from https://github.com/TianGzlab/OmicsClaw/tree/main/skills/metabolomics/metabolomics-annotation into .opencode/skills/metabolomics-annotation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "metabolomics-annotation", 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-annotation- GitHub stars
- 161
- Token cost
- ~1.1k tokens
- SKILL.md length
- 378 words
- Files
- 8 (incl. references)
- Skills in repo
- 88
- Repo updated
- First seen
- Licence
- Apache-2.0
At a glance
Load when matching LC-MS m/z features to an explicit local metabolite reference within a ppm tolerance; bundled HMDB entries are for explicit demonstrations only.
- Data & Analytics work in your project
- 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
What it does
Metabolomics Annotation is an agent skill from TianGzlab/OmicsClaw. Load when matching LC-MS m/z features to an explicit local metabolite reference within a ppm tolerance; bundled HMDB entries are for explicit demonstrations only. Skip pathway ORA (use metabolomics-pathway-enrichment) and spectral matching or online searches (use external SIRIUS / GNPS).
Its SKILL.md is about 1.1k 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 `metabolomics_annotation.py`).
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-annotation”
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 Annotation loads about 1.1k tokens when it runs, and up to ~1.5k if it reads all its reference files. Until then it costs about 78 tokens; SKILL.md has 378 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). 378 words, ~1,110 tokens.
Download SKILL.mdSave it as
.claude/skills/metabolomics-annotation/SKILL.md (or your agent's skills folder). This skill also uses 7 other files; get the full folder from GitHub.- name
- metabolomics-annotation
- description
- Load when matching LC-MS m/z features to an explicit local metabolite reference within a ppm tolerance; bundled HMDB entries are for explicit demonstrations only. Skip pathway ORA (use metabolomics-pathway-enrichment) and spectral matching or online searches (use external SIRIUS / GNPS).
- trigger
- metabolite annotation, SIRIUS, GNPS, MetFrag, spectral matching, metabolite ID, ppm tolerance
- tags
- metabolomics, annotation, hmdb, demo, mz-match
metabolomics-annotation
When to use
Match m/z to adduct masses in an explicit reference or the bundled 15-metabolite demo. Use external SIRIUS/GNPS for spectral or database-scale identification.
Use from a step
import pandas as pd
from skills._sdk.notebook import load_skill, read_input, write_output
library = load_skill("metabolomics-annotation")
data = read_input('features.csv', reader=pd.read_csv)
reference = read_input('reference.csv', reader=pd.read_csv)
result = library.annotate(data, reference=reference)
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 -->annotate(data, *, database='hmdb', ppm=10.0, adducts=None, reference=None)
Match every observed m/z to all reference adducts within tolerance.
:param data: Feature DataFrame with a numeric mz column. :param database: CLI default hmdb; label for the supplied reference, not a database fetch. :param ppm: CLI default 10; nonnegative mass error tolerance in parts per million. :param adducts: CLI default None resolves to [M+H]+ and [M-H]-. :param reference: Required DataFrame with name, neutral_mass, database_id and formula; demo_reference() is for demonstrations only. :returns: A new annotations DataFrame; attrs['run_info'] names the reference scope. :raises ValueError: Reference, observed masses, tolerance or adducts are invalid.
demo_reference()
Return the 15 bundled metabolites for explicit demonstrations.
:returns: An independent reference DataFrame marked as demo in its attrs.
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.
Show full SKILL.md (156 more words)Show less
mass_error_figure(data)
Plot the ppm error of matched metabolite candidates.
:param data: Annotation table returned by annotate. :returns: A matplotlib Figure. :raises KeyError: ppm_error is absent.
<!-- api:end -->Methods and parameters
Pass reference= with name, neutral_mass, database_id and formula for local reference mass matching. The CLI requires --reference-file reference.csv for real input. No network lookup runs; database labels the supplied reference. demo_reference() explicitly selects 15 illustrative HMDB entries, also used by --demo.
Gotchas
annotaterejects missing reference data; demo references cannot be relabelled as another database. Each query can have multiple candidate rows intables/annotations.csv; Unknown rows retain unmatched queries. Confidence labels describe ppm bins, not identification probability.result.jsonpreserves the reference scope indata.run_info.reference_scope; demo matches are not biological identification evidence.
Inputs and outputs
CSV input; tables/annotations.csv, report.md and result.json. The CLI writes reproducibility/commands.sh.
The function library returns objects; the CLI and step own file writes.
CLI
python skills/metabolomics/metabolomics-annotation/metabolomics_annotation.py --demo --output /tmp/metabolomics_annotation
python skills/metabolomics/metabolomics-annotation/metabolomics_annotation.py --input features.csv --reference-file reference.csv --output /tmp/metabolomics_annotation_realSee also
Dependencies
numpy, pandas, 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-annotation of TianGzlab/OmicsClaw.
- SKILL.md
- _api.py
- examples/example_step.py
- metabolomics_annotation.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 Annotation 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 Annotation this skillTianGzlab/OmicsClaw | 161 | — | ~1.1k | Automated safety check: Pass | Apache-2.0 | |
| MatplotlibzLanqing/codex-claude-academic-skills | 4.7k | 17 repos | ~2.9k | Automated safety check: Pass | MIT | |
| Exploratory Data Analysisspacering-net/codeg | 3.9k | 14 repos | ~3.6k | Automated safety check: Pass | MIT | |
| Scikit LearnzLanqing/codex-claude-academic-skills | 4.7k | 16 repos | ~3.9k | Automated safety check: Pass | BSD-3-Clause | |
| Chart Visualizationbytedance/deer-flow | 84k | 1 repos | ~840 | Automated safety check: Pass | MIT | |
| TimesFM Forecastinggoogle-research/timesfm | 34k | — | ~4.7k | Automated safety check: Pass | Apache-2.0 |
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Related
Categories
Questions about Metabolomics Annotation
What does Metabolomics Annotation do?
Load when matching LC-MS m/z features to an explicit local metabolite reference within a ppm tolerance; bundled HMDB entries are for explicit demonstrations only. Metabolomics Annotation is an agent skill from TianGzlab/OmicsClaw. Load when matching LC-MS m/z features to an explicit local metabolite reference within a ppm tolerance; bundled HMDB entries are for explicit demonstrations only.
When should I use Metabolomics Annotation?
Metabolomics Annotation fits situations like: data & Analytics work in your project.
How do I install Metabolomics Annotation in Claude Code?
Run `npx skills add TianGzlab/OmicsClaw --skill metabolomics-annotation -a claude-code`. Or copy the skill folder (skills/metabolomics/metabolomics-annotation in TianGzlab/OmicsClaw) into .claude/skills/metabolomics-annotation in your project. Claude Code loads it when a task matches its description.
How do I install Metabolomics Annotation in Codex?
Run `npx skills add TianGzlab/OmicsClaw --skill metabolomics-annotation -a codex`. Or copy the skill folder (skills/metabolomics/metabolomics-annotation in TianGzlab/OmicsClaw) into .agents/skills/metabolomics-annotation in your project. Codex loads it when a task matches its description.
Can I use Metabolomics Annotation 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-annotation -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-annotation, .gemini/skills/metabolomics-annotation, .github/skills/metabolomics-annotation and .opencode/skills/metabolomics-annotation in your project.
What does Metabolomics Annotation need to run?
Going by SKILL.md and its folder, Metabolomics Annotation needs Python for the scripts in its folder and the command-line tools its instructions call (python). Our summary lists: Python 3.
Does Metabolomics Annotation 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 Annotation 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 Annotation use?
Metabolomics Annotation 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 Annotation use?
About 1.1k tokens (SKILL.md is roughly 4.4k 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 399 tokens, read only when the agent opens those files.
What are the alternatives to Metabolomics Annotation?
Skills that share tags, products or a category with Metabolomics Annotation: Matplotlib (zLanqing/codex-claude-academic-skills, 4.7k stars), Exploratory Data Analysis (spacering-net/codeg, 3.9k stars), Scikit Learn (zLanqing/codex-claude-academic-skills, 4.7k stars) and Chart Visualization (bytedance/deer-flow, 84k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Metabolomics Annotation?
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.