Explore skills

Resolve the architecture of focal oncogene amplifications — extrachromosomal DNA (ecDNA), breakage-fusion-bridge (BFB) cycles, homogeneously staining regions (HSR), and linear amplification — from whole-genome sequencing with AmpliconArchitect, the AmpliconSuite pipeline, and AmpliconClassifier. Covers copy-number seed selection, breakpoint-graph reconstruction, balanced-flow optimization, ecDNA c

Classical ML in Python: classification, regression, clustering, dim reduction, evaluation, tuning, preprocessing pipelines. Linear models, tree ensembles, SVMs, K-Means, PCA, t-SNE. Use PyTorch/TF for deep learning; XGBoost/LightGBM for scale.

Use when deploying LibreChat with Docker Compose, setting up docker-compose.yml or docker-compose.override.yml, configuring containers, setting up reverse proxies (nginx, Traefik), deploying to cloud providers (Azure, DigitalOcean, Railway), or running LibreChat locally for development. Also use when asked about container networking, volume mounts, or GPU passthrough.

Use when configuring LibreChat's MongoDB database, Redis caching, MeiliSearch message search, file storage strategy (local vs CDN/S3), or PGVector for RAG. Also use when asked about database backup, connection strings, or storage scaling.

Configure Istio traffic management including routing, load balancing, circuit breakers, and canary deployments. Use when implementing service mesh traffic policies, progressive delivery, or resilience patterns.

Use when facing 2+ independent tasks that can be worked on without shared state or sequential dependencies

Generate consensus FASTA sequences by applying VCF variants to a reference using bcftools consensus. Use when creating sample-specific reference sequences or reconstructing haplotypes.

Medicinal chemistry filters. Apply drug-likeness rules (Lipinski, Veber), PAINS filters, structural alerts, complexity metrics, for compound prioritization and library filtering.

Progressive delivery on Kubernetes — canary and blue-green deployments via Argo Rollouts, plus environment-to-environment promotion via Kargo. USE WHEN implementing canary releases, blue-green deployments, traffic shifting between revisions, metric-gated promotions, AnalysisTemplate/AnalysisRun design, Argo Rollouts CRDs, or Kargo freight/warehouse/stage promotion pipelines, multi-stage promotion

Manage device adoption and onboarding, maintain device inventory, and monitor device configurations across your UniFi network infrastructure.

AppFlowy Cloud/GoTrue API authentication and invocation process, covering token acquisition, workspace, documents, databases, and search. Use this in this repository for Python development, debugging, automation, or troubleshooting AppFlowy API clients and scripts.

Build GitLab CI/CD pipelines with multi-stage workflows, caching, and distributed runners for scalable automation. Use when implementing GitLab CI/CD, optimizing pipeline performance, or setting up automated testing and deployment.