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a

@anthropics

Portfolio Monitoring

Review portfolio-company financial packages, flag variance to plan, and prepare monitored KPI summaries.

a

@anthropics

Equity Research Earnings Analysis

Create a structured post-earnings equity research update with key metrics, estimate changes, charts, and thesis review.

t

@tradermonty

Market News Analyst

Rank recent market-moving news and explain likely effects on equities, commodities, monetary policy, and earnings.

K

@K-Dense-AI

bulk-rnaseq

End-to-end bulk RNA-seq orchestrator — takes raw FASTQ reads through QC and trimming (FastQC, fastp/Trim Galore), alignment and quantification (STAR, Salmon, featureCounts), assembles a gene-level counts matrix, then hands off to differential expression (pydeseq2), pathway/GSEA enrichment (pathway-enrichment), and publication figures (scientific-visualization). Use whenever the user has bulk RNA-seq reads or quant output and wants a complete, reproducible differential-expression workflow — e.g. "analyze my RNA-seq", "FASTQ to DESeq2", "run nf-core/rnaseq", "STAR/Salmon quantification", "build a counts matrix for DESeq2", or "go from reads to differentially expressed genes and enriched pathways". Routes between an nf-core/rnaseq (Nextflow) path and a standalone STAR/Salmon path, and covers experimental design, strandedness, and QC gates. For single-cell RNA-seq use the scanpy skill instead.