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Use when after LDA inference has produced a trained motifset (motifset.json or motifset_optimized.json) with Mass2Motif probability distributions over fragments and neutral losses.
motif-metadata-annotation is an agent skill entry in ChatHome Skills, sourced from GitHub Skill Search and scored 58/100. # motif-metadata-annotation ## Summary Annotate discovered Mass2Motifs with structural substructure meaning, fragment/neutral-loss composition, and spectral loa. 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 motif-metadata-annotation 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.
# motif-metadata-annotation ## Summary Annotate discovered Mass2Motifs with structural substructure meaning, fragment/neutral-loss composition, and spectral loading counts to enabl