DevOps & Infra

oimiragieo Bundle

Standard single-cell RNA-seq analysis pipeline. Use for QC, normalization, dimensionality reduction (PCA/UMAP/t-SNE), clustering, differential expression, and visualization. Best for exploratory scRNA-seq analysis with established workflows. For deep learning models use scvi-tools; for data format questions use anndata.

oimiragieo Bundle

Cloud laboratory platform for automated protein testing and validation. Use when designing proteins and needing experimental validation including binding assays, expression testing, thermostability measurements, enzyme activity assays, or protein sequence optimization. Also use for submitting experiments via API, tracking experiment status, downloading results, optimizing protein sequences for better expression using computational tools (NetSolP, SoluProt, SolubleMPNN, ESM), or managing protein design workflows with wet-lab validation.

gptomics Bundle

Standardizes molecular structures using the ChEMBL structure pipeline for normalization and parent selection plus RDKit rdMolStandardize for explicit custom steps such as tautomer canonicalization, salt/solvent stripping, charge handling, stereochemistry handling, mixture selection, and isotope normalization. Explicitly compares ChEMBL, canSARchem, RDKit, and PubChem standardization choices. Use when preparing libraries for QSAR training, joining datasets across sources, deduplicating compound collections, or building canonical compound registries.

g1joshi Skill

Neon serverless PostgreSQL with branching. Use for serverless Postgres.

g1joshi Skill

Ansible configuration management with playbooks and roles. Use for server provisioning.

g1joshi Skill

Jenkins automation server with pipelines and plugins. Use for CI/CD pipelines.

g1joshi Skill

Netlify web deployment with serverless functions. Use for static hosting.

g1joshi Skill

Rancher Kubernetes management platform. Use for multi-cluster K8s.

g1joshi Skill

Traefik cloud-native reverse proxy. Use for container networking.

gptomics Bundle

Analyzes multiplexed antibody-imaging data (CODEX/PhenoCycler, MIBI-TOF, IMC, CyCIF, Opal/Vectra mIF) as continuous protein intensity rather than transcript counts, using scimap and squidpy. Use when choosing an intensity transform/normalization (arcsinh cofactor vs z-score vs percentile -- NOT log1p-of-counts) and correcting channel spillover and antibody-batch effects; deciding whether to phenotype by gating or by clustering on intensities; recognizing that a bounded antibody panel makes marker absence uninformative; treating whole-cell segmentation (Mesmer) as the dominant error source; and knowing which platform applies and when to defer to the imaging-mass-cytometry skills for the IMC pipeline.

gptomics Bundle

Build whole-genome alignments using Progressive Cactus (Armstrong 2020 reference-free clade-level WGA), Minigraph-Cactus (Hickey 2024 pangenome-aware), LASTZ chain/net (UCSC pipeline), MUMmer4 (Marçais 2018 pairwise), minimap2 -x asm5/10/20 (Li 2018 fast pairwise), AnchorWave (Song 2022 WGD-aware), and Mauve / progressiveMauve (bacterial). Operates the HAL toolkit (Hickey 2013) for downstream extraction including halSynteny, halLiftover, halBranchMutations, and hal2maf. Use when constructing multi-species alignments for comparative-annotation projection (TOGA), synteny detection, conservation analyses (phyloP / PhastCons), or pangenome graph construction; selecting between reference-free (Cactus) and reference-anchored (LASTZ chains/nets) approaches; tuning sensitivity for closely vs distantly related genomes; or producing HAL files for genome-wide downstream tools.

gptomics Bundle

Build Sankey, alluvial, river, and CONSORT-style flow diagrams to visualize cohort transitions, cell-state changes, or pipeline filtering using ggalluvial, networkD3, plotly, and consort. Use when showing how entities move between categories across timepoints (cell states, drug response classes, patient flow through a trial) or filtering pipelines (variants filtered through QC stages).

gptomics Bundle

Predicts protein-coding gene structures (exons, introns, UTRs) in eukaryotic genomes with BRAKER3 (RNA-seq + protein evidence), BRAKER1/BRAKER2, GALBA (protein-only), Funannotate (fungi), GeMoMa (homology projection), or Helixer/Tiberius (deep-learning ab initio). Covers the evidence-first tool decision, mandatory soft-masking, the training-set-quality-dominates principle, OrthoDB clade-partition selection, the one-isoform-per-locus and missing-UTR traps, merge/split errors, and reference bias against orphan genes. Use when annotating a newly assembled eukaryotic genome, choosing a gene-prediction pipeline based on available evidence, or diagnosing a poor annotation.

g1joshi Skill

Azure CLI command-line interface. Use for Azure automation.

g1joshi Skill

CircleCI cloud CI/CD platform. Use for continuous integration.

oimiragieo Bundle

Google Cloud Run deployment, service management, traffic splitting, and log inspection. Use when deploying containerized apps to Cloud Run, managing services, or inspecting Cloud Run logs.

g1joshi Skill

GitLab CI/CD pipelines with runners and stages. Use for GitLab automation.

g1joshi Skill

Terraform infrastructure as code with providers and state management. Use for cloud provisioning.

oimiragieo Bundle

Google Cloud CLI operations and resource management

gptomics Bundle

Detects aberrant splicing in single rare-disease patients vs a control panel using FRASER 2.0 (Bioconductor; Beta-binomial autoencoder on Intron Jaccard Index, default delta cutoff 0.1, q hyperparameter), OUTRIDER (gene-level outlier expression via autoencoder denoising), LeafcutterMD (Dirichlet-multinomial outlier mode of LeafCutter for annotation-free junctions), and DROP (Snakemake pipeline integrating FRASER2 + OUTRIDER + monoallelic expression for clinical diagnostics). The statistical model is fundamentally different from differential splicing — single-sample-vs-cohort outlier detection rather than two-group comparison. Standard tool in EU rare-disease (Solve-RD) and NIH UDN programs. Use when applying RNA-seq to undiagnosed Mendelian disease, validating predicted splice variants in clinical samples, or detecting cryptic splicing in disease tissue.

g1joshi Skill

MongoDB document database with aggregation pipeline and Atlas. Use for document storage.

g1joshi Skill

Kubernetes container orchestration with Helm, operators, and service mesh. Use for cluster management.

ariffazil Bundle

runpod-flash — code-first serverless: write Python locally, run it on remote Runpod GPUs/CPUs with `flash dev` (hot-reload + live worker logs), then `flash deploy`. Use for @Endpoint/@remote functions, resource config, and debugging flash deployments. For CLI-only infra management use runpodctl or runpod-mcp.

ariffazil Bundle

Start here for any Runpod task — running GPU/CPU pods, deploying serverless endpoints, templates, network volumes, building images, or understanding how Runpod works. Routes the request to the right Runpod skill (runpod-mcp, runpodctl, flash, companion-clis, or runpod-usage). Use when it is unclear which Runpod skill applies.

ariffazil Bundle

Runpod CLI for managing GPU/CPU workloads from the terminal — pods, serverless endpoints, templates, network volumes, Hub deploys, models, SSH, and file transfer (send/receive). Use for terminal/CI/scripting, Hub browse/deploy, SSH setup, `doctor`, or when the Runpod MCP tools are not connected. For structured tool calls in an MCP-enabled session, prefer runpod-mcp.

ariffazil Bundle

Manage Runpod infrastructure — pods, serverless endpoints, jobs, templates, network volumes, container-registry auth, GPU/CPU catalog, and billing — via the Runpod MCP server's structured tool calls. Use when the Runpod MCP tools (create-pod, list-endpoints, …) are connected in this session, or to connect them (hosted OAuth or local npx). Prefer this over runpodctl for plain infra CRUD when MCP is available; use runpodctl for the terminal, file transfer, or SSH setup.

oimiragieo Bundle

Chunked N-D arrays for cloud storage. Compressed arrays, parallel I/O, S3/GCS integration, NumPy/Dask/Xarray compatible, for large-scale scientific computing pipelines.

g1joshi Skill

Azure Cosmos DB multi-model database with global distribution. Use for Azure.

g1joshi Skill

AWS DynamoDB serverless NoSQL with streams and global tables. Use for AWS serverless.

g1joshi Skill

Supabase PostgreSQL backend-as-a-service with realtime. Use for serverless PostgreSQL.

ariffazil Bundle

Build, test, inspect, install, and deploy MCP servers with FastMCP in Python

ariffazil Bundle

Companion CLIs for Runpod workflows — HuggingFace, GitHub, Docker, and AWS.

g1joshi Skill

Snowflake cloud data warehouse with data sharing. Use for cloud analytics.

g1joshi Skill

Microsoft SQL Server with T-SQL, SSMS, and enterprise features. Use for Windows/Azure.

g1joshi Skill

DigitalOcean cloud platform with droplets. Use for simple cloud.

ariffazil Bundle

One-click deploy, publish, and update a local project or Git repository to Alibaba Cloud International (alibabacloud.com), producing an accessible online service with a public IP. Supports full-stack ROS orchestration, automatic cloud-resource provisioning, pre-deployment price confirmation, service health checks, deployment-state recording, hot updates, and optional domain + HTTPS setup. Use when: the user asks to deploy a project to the cloud, put an app online, publish a website, generate an access URL, deploy a Git repo, or update an online version and has NOT named a specific cloud platform; or the user mentions "Alibaba Cloud", "alibabacloud.com", or the international site. Do not use when: the user explicitly targets Aliyun China (aliyun.com), AWS, GCP, Azure, or another specific cloud platform.