Data & Analytics

**Skill ID**: `nutrigx-advisor` **Version**: 0.1.0 **Status**: MVP **Author**: David de Lorenzo (ClawBio Community) **Requires**: Python 3.11+, pandas, numpy, matplotlib, seaborn, reportlab (optional) ---

Personalised nutrition report from consumer genetic data (23andMe, AncestryDNA, VCF) — interrogates nutritionally-relevant

使用 NovelWeave 进行小说创作的完整工作流程，包括命令使用、最佳实践和高效创作技巧。适用于规划小说项目、组织创作过程或学习 NovelWeave 功能。

当用户提到悬疑、侦探、犯罪或悬念叙事时使用 - 提供类型规范、线索布置和推理小说的公平游戏原则

This skill should be used when user asks to "query MongoDB", "show database collections", "get collection schema", "list MongoDB databases", "search records in MongoDB", or "check database indexes".

Load when running an XCMS-style preprocessing summary on LC-MS metabolomics raw / vendor-converted

Load when running univariate two-group testing (t-test / Wilcoxon / ANOVA / Kruskal-Wallis)

Load when imputing missing values (min / median / KNN) and normalising (TIC / median / log)

Load when running per-sample peak picking on a feature × intensity table via `scipy.signal.find_peaks`

Load when running over-representation analysis (ORA) on a metabolite list via Fisher's exact

Load when normalising a feature × sample metabolomics CSV via median, quantile, total (sum),

Load when running two-group metabolomics DE (t-test + log2FC + BH-FDR + PCA) on a feature

Load when annotating LC-MS features against a built-in 15-metabolite HMDB demo dictionary

Ensure deterministic and safe memory usage: static allocation, pools, stack sizing, MPU usage, and corruption detection for medical device firmware.

Cargo.toml dependency management patterns for HASH workspace. Use when adding dependencies, managing workspace dependencies, organizing Cargo.toml sections, setting version pinning, configuring default features, or working with public dependencies.

Load when extracting GEO accessions, dataset metadata, and downloadable references from a

当用户开始新小说项目时激活 - 通过温和的提示和解释引导他们完成七步方法论（constitution → specify → clarify → plan → tasks → write → analyze）

Load when summarising / filtering a VCF — variant classification (SNP / MNP / INS / DEL /

Load when summarising small variants (SNVs / indels) from a VCF or computing demo-pattern

Load when summarising functional impact of an annotated variant CSV — per-IMPACT counts (HIGH

Load when summarising structural variants from an SV VCF (DEL / DUP / INV / TRA) — BND-notation

Load when running pre-alignment FASTQ quality control — Phred quality scores, Q20/Q30 rates,

Load when summarising a phased VCF (output of WhatsHap / SHAPEIT5 / Eagle2) — phased fraction

Load when summarising a peak file (BED / narrowPeak) from ATAC-seq / ChIP-seq / CUT&Tag —