Skill-Verzeichnis

Wiederverwendbare Skills für AI Agents entdecken.

Durchsuche reale GitHub-Skills nach Aufgabe und prüfe Stars, Trust, Audit, Kategorie und Installationspfad vor der Verwendung.

Jede Empfehlung bleibt mit ihrem Repository, Audit und Installationspfad nachvollziehbar.

Suchergebnisse: comparative-genomics

Englisches Verzeichnis

A comprehensive collection of ready-to-use scientific and research skills for AI agents.

31K
Stars
78/100
Trust
Kategorie: utilityAudit

ADAM is a genomics analysis platform with specialized file formats built using Apache Avro, Apache Spark, and Apache Parquet. Apache 2 licensed.

1.1K
Stars
80/100
Trust
Kategorie: geo-scienceAudit

Data structure for annotated matrices in single-cell analysis. Use when working with .h5ad files or integrating with the scverse ecosystem. This is the data format skill—for analysis workflows use scanpy; for probabilistic models use scvi-tools; for population-scale queries use cellxgene-census.

34K
Stars
77/100
Trust
Kategorie: data-analysisAudit

Autonomously improve a real artifact (code, training recipe, agent harness, data pipeline, prompt) against an objective and an evaluator, using Hypothesis Tree Refinement (HTR) from the Arbor paper. Use this whenever someone wants to iteratively optimize something over many experiments without overfitting — e.g. "get my model's eval score up", "improve this agent/harness", "tune this pipeline", "beat the baseline on this benchmark", "run a search over approaches and keep the best", "do an MLE-bench / Kaggle-style optimization", or any long-horizon "make this artifact better and don't just memorize the dev set" task. Trigger it even when the user doesn't say "Arbor" or "hypothesis tree" but describes repeated experiment-and-evaluate loops, branching exploration of competing ideas, or worries about a dev/test gap. Runs Claude itself as the coordinator with subagent executors in isolated git worktrees; for the standalone `arbor` CLI tool see references/arbor-upstream.md.

34K
Stars
77/100
Trust
Kategorie: researchAudit

Infer gene regulatory networks (GRNs) from gene expression data using scalable algorithms (GRNBoost2, GENIE3). Use when analyzing transcriptomics data (bulk RNA-seq, single-cell RNA-seq) to identify transcription factor-target gene relationships and regulatory interactions. Supports distributed computation for large-scale datasets.

34K
Stars
77/100
Trust
Kategorie: data-analysisAudit

Obsei is a low code AI powered automation tool. It can be used in various business flows like social listening, AI based alerting, brand image analysis, comparative study and more .

1.4K
Stars
76/100
Trust
Kategorie: automationAudit

Pysam is a Python package for reading, manipulating, and writing genomics data such as SAM/BAM/CRAM and VCF/BCF files. It's a lightweight wrapper of the HTSlib API, the same one that powers samtools, bcftools, and tabix.

895
Stars
71/100
Trust
Kategorie: geo-scienceAudit

A genome visualization python package for comparative genomics

410
Stars
68/100
Trust
Kategorie: geo-scienceAudit

Python library to facilitate genome assembly, annotation, and comparative genomics

918
Stars
71/100
Trust
Kategorie: geo-scienceAudit

Curated collection of 39 agent skills for healthcare and life sciences workflows, installable via the Agent Skills standard.

10
Stars
66/100
Trust
Kategorie: researchAudit

LinkedIn-native long-form article and newsletter writing workflow for LinkedIn and Google-to-LinkedIn topic discovery, business-depth research, professional thought leadership, evidence-led drafting, final humanization, discussion design, SEO settings, auditing, and publish-ready packaging. Use when creating, outlining, researching, enriching, rewriting, humanizing, auditing, or packaging LinkedIn Articles, LinkedIn newsletters, LinkedIn long-form posts, LinkedIn thought leadership, LinkedIn B2B articles, LinkedIn 长文, LinkedIn 专栏, LinkedIn 话题调研, LinkedIn 商务内容, 去 AI 化编辑, or LinkedIn 发布包.

483
Stars
63/100
Trust
Kategorie: securityAudit