Loading…
Use when when you have raw LC-MS chromatographic data (mzML or vendor format) and need to identify and characterize all detectable peaks across the full retention time range for untargeted metabolomics or discovery workflows.
lcms-feature-extraction is an agent skill entry in ChatHome Skills, sourced from GitHub Skill Search and scored 58/100. # lcms-feature-extraction > **License: noncommercial** — confirm your use is a permitted (noncommercial) purpose before applying; commercial use requires a sepa. As an agent skill, it packages a reusable instruction set that AI coding agents such as Codex and Claude Code can load to perform this task without hand-written glue code. ChatHome Skills discovered this entry through its daily ingest of official registries and GitHub discovery queries, and re-verifies repository facts, freshness signals, and install metadata on every run. The quality score weighs official-registry presence, a working install command, license clarity, GitHub star trajectory, and repository freshness — the full formula is on the Sources page. The install command above is ready to copy. Review the last-pushed date and repository status before adding lcms-feature-extraction to a production agent workflow; the snapshot facts below are point-in-time values from the most recent ingest.
codex skill install HolobiomicsLab/asb-skill-collectionsReview the upstream source before running this command.
Scan coverage: Install metadata and the indexed document body.
Automated signals from install metadata and a bounded skill body — not a full code security audit and not a recursive source or dependency review.
# lcms-feature-extraction > **License: noncommercial** — confirm your use is a permitted (noncommercial) purpose before applying; commercial use requires a separate license (see `m