Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add TianGzlab/OmicsClaw --skill metabolomics-xcms-preprocessinggit clone --depth 1 https://github.com/TianGzlab/OmicsClawWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/tiangzlab/omicsclaw/metabolomics-xcms-preprocessing)<a href="https://agentmods.dev/skills/tiangzlab/omicsclaw/metabolomics-xcms-preprocessing"><img src="https://agentmods.dev/badge/skills/tiangzlab/omicsclaw/metabolomics-xcms-preprocessing/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/tiangzlab/omicsclaw/metabolomics-xcms-preprocessing"><img src="https://agentmods.dev/badge/skills/tiangzlab/omicsclaw/metabolomics-xcms-preprocessing.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Rogue Agent · line 3 Skill modifies its own code, configuration, or behavior at runtime. Self-modification enables an agent to escalate privileges, disable safety constraints, or install persistent backdoors.Fix: Prevent the skill from modifying its own code, SKILL.md, or configuration files. Treat skill files as read-only at runtime.
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00076 | $0.01024 |
| Opus 5 | $0.00038 | $0.00512 |
| Sonnet 5 | $0.00015 | $0.00205 |
| Haiku 4.5 | $0.00008 | $0.00102 |
Grade A, and why
metabolomics-xcms-preprocessing scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 5d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 87 lines — stays where its author put it; the contents beside it link to each section on GitHub.
metabolomics-xcms-preprocessing
When to use
The user has LC-MS / GC-MS metabolomics files (or a placeholder
multi-file list) and wants the standard XCMS-style preprocessing
output: peak table with mz, rt, and per-sample intensity
columns. The skill mirrors the canonical CentWave + Obiwarp +
correspondence + gap-fill workflow conceptually but is pure
Python — there is no rcpp / xcms R bridge here.
For per-sample peak picking from a single intensity matrix use
metabolomics-peak-detection. For metabolite annotation use
metabolomics-annotation.
Inputs & Outputs
Inputs
- Modalities: lc-ms
Outputs
tables/peak_table.csvreport.mdresult.json- Produces artifact
metabolomics.peak_tableastables/peak_table.csv(csv)
Flow
- Load files (
--input <files>) or generate a demo peak table (--demo). - Apply CentWave-style peak detection at the configured
--ppmand--peakwidth-*parameters. - Write
tables/peak_table.csv(metabolomics_xcms_preprocessing.py:211) +report.md+result.json.
Gotchas
- Pure Python — NO real XCMS / CAMERA invocation. The script does not call R /
rcpp/xcms/CAMERA. Demo and real-input runs both produce a synthetic-shaped peak table; for production XCMS workflows, run XCMS in R upstream and feed the resulting peak table intometabolomics-peak-detectionormetabolomics-quantification. --inputaccepts MULTIPLE files vianargs="+".metabolomics_xcms_preprocessing.py:186declaresnargs="+", so passing several files is the supported single-call shape. Demo ignores--input.--inputREQUIRED unless--demo.metabolomics_xcms_preprocessing.py:203raisesValueError("--input required when not using --demo").- Peak-width units are SECONDS (chromatographic).
--peakwidth-min 10.0 --peakwidth-max 60.0defaults assume LC-MS scan timing. For UPLC narrow peaks consider--peakwidth-min 5 --peakwidth-max 20. --ppm 25.0default is broad. Suitable for low-resolution Orbitrap / Q-TOF; for high-resolution FTMS use--ppm 5.0. Wrong value silently yields false positive merges.
What ships with it
5 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 5d ago First seen · 87 lines · 76 tokens per session scan A a035bc8d1eb4
metabolomics-xcms-preprocessing is a skill published in the GitHub repository TianGzlab/OmicsClaw (160 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 76 tokens to every session and 1,024 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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