DevOps & Infra

gptomics Bundle

Download genome assemblies, gene records, and ortholog data from NCBI using the modern Datasets v2 CLI (replaces assembly_summary.txt scraping and many EFetch workflows). Use when bulk-pulling genome assemblies, gene metadata across species, ortholog sets, or BLAST databases; when E-utilities are too slow for genome-scale work; or when automatic checksum verification, parallel download, and clean accession-driven retrieval are required. Encodes the JSON-lines output format, dataformat conversion, --dehydrated for cloud workflows, and when Datasets is/isn't the right tool.

sboghossian-mini-claude-for-legal Skill

Use at the start of every request pipeline to grade the complexity of the incoming request and assign it to a complexity bucket. Buckets drive downstream model selection, token budget, tool activation, and latency targets. Five buckets ranging from short-answer (under 200 tokens) to agentic (multi-step with tool calls and gates). Outputs a JSON object consumed by the tool selector and model router.

intent-solutions-io Skill

This skill sets up log aggregation solutions using ELK (Elasticsearch, Logstash, Kibana), Loki, or Splunk. It generates production-ready configurations and setup code based on specific requirements and infrastructure. Use this skill when the user requests to set up logging infrastructure, configure log aggregation, deploy ELK stack, deploy Loki, deploy Splunk, or needs help with observability. It is triggered by terms like "log aggregation," "ELK setup," "Loki configuration," "Splunk deployment," or similar requests for centralized logging solutions.

gptomics Bundle

Stores and operates on sparse expression matrices for single-cell and large bulk RNA-seq, covering dgCMatrix/dgRMatrix/dgTMatrix when-each-is-fast, the dgCMatrix (CSC, R) <-> CSR (Python) implicit transpose, AnnData (cells-rows) <-> SingleCellExperiment (cells-cols) orientation flip, HDF5/h5ad vs Zarr cloud-native shift, HDF5SummarizedExperiment + DelayedArray for out-of-memory bulk, scanpy backed mode for large h5ad, the ~10-15% density crossover where dense beats sparse, 10X format proliferation (MTX vs CellRanger H5 vs h5ad), the dense-conversion memory blow-up, and Dask + Zarr for consortium-scale matrices. Use when choosing sparse format, working with single-cell-sized matrices, importing/exporting 10X, debugging R/Python interop transposes, processing matrices too large for RAM, or building cloud-native pipelines.

sboghossian-mini-claude-for-legal Skill

Use when a user uploads a scanned PDF (no text layer) and needs it processed through automatic OCR before any legal analysis, chat, or document workspace ingestion can proceed. This is the lightweight router-level entry point for scanned PDF handling; it detects the absence of a text layer and delegates to the full OCR pipeline, supporting Arabic, English, and French documents with a user-confirmation fallback when confidence is low.

intent-solutions-io Skill

This skill empowers Claude to build AutoML pipelines using the automl-pipeline-builder plugin. It is triggered when the user requests the creation of an automated machine learning pipeline, specifies the use of AutoML techniques, or asks for assistance in automating the machine learning model building process. The skill analyzes the context, generates code for the ML task, includes data validation and error handling, provides performance metrics, and saves artifacts with documentation. Use this skill when the user explicitly asks to "build automl pipeline", "create automated ml pipeline", or needs help with "automating machine learning workflows".

intent-solutions-io Skill

This skill enables Claude to construct GitOps workflows using ArgoCD and Flux. It is designed to generate production-ready configurations, implement best practices, and ensure a security-first approach for Kubernetes deployments. Use this skill when the user explicitly requests "GitOps workflow", "ArgoCD", "Flux", or asks for help with setting up a continuous delivery pipeline using GitOps principles. The skill will generate the necessary configuration files and setup code based on the user's specific requirements and infrastructure.

intent-solutions-io Skill

This skill enables Claude to deploy machine learning models to production environments. It automates the deployment workflow, implements best practices for serving models, optimizes performance, and handles potential errors. Use this skill when the user requests to deploy a model, serve a model via an API, or put a trained model into a production environment. The skill is triggered by requests containing terms like "deploy model," "productionize model," "serve model," or "model deployment."

intent-solutions-io Skill

This skill creates Ansible playbooks for automating configuration management tasks. It generates production-ready, multi-platform playbooks based on user-defined requirements, incorporating best practices and a security-first approach. Use this skill when you need to automate server configurations, software deployments, or infrastructure management using Ansible. Trigger this skill by requesting "Ansible playbook," specifying configuration details, or asking for automation of a particular setup.

intent-solutions-io Skill

This skill automates database archival processes. It helps reduce primary database size by moving historical records to archive tables or cold storage solutions like S3, Azure Blob, or GCS. The plugin supports PostgreSQL and MySQL, implementing automated retention policies, compression, compliance tracking, and zero-downtime migration. Use this when the user mentions "database archival", "archive old database records", "retention policies", "cold storage", or "reduce database size." It is particularly useful for handling requests related to data lifecycle management and compliance requirements in database systems.

gptomics Bundle

Authors bioinformatics pipelines in WDL (Workflow Description Language) run by Cromwell or miniwdl, targeting the GATK/Broad and Terra/AnVIL/BioData Catalyst cloud ecosystem, with tasks, workflows, scatter-gather parallelism, structs, and a runtime block that sizes the cloud VM. Use when deciding to target Terra/AnVIL/GATK/WARP (chosen for the ecosystem, not the language); sizing runtime disks dynamically for a fresh-per-task cloud VM (ceil(size(f)*factor)+buffer); choosing preemptible vs on-demand VMs by task length and idempotency; picking Cromwell (production, cloud, call-caching) vs miniwdl (local dev, miniwdl check linting, readable errors); enabling and debugging call-caching silent-miss modes; pinning Docker by digest for reproducibility and cache stability; or scattering an array for parallel fan-out.

gptomics Bundle

End-to-end clinical trial analysis workflow from CDISC SDTM/ADaM loading through ICH E9(R1) estimand-driven primary analysis to CONSORT 2025 regulatory-compliant reporting. Covers data preparation, FDA 2023 marginal vs conditional logistic regression, categorical tests with Boschloo, modern HTE/subgroup methods, missing-data sensitivity (MMRM, reference-based MI, Permutt tipping point), graphical multiplicity (Bretz-Maurer), survival analysis (Cox/RMST/competing risks) when applicable, and Table 1. Use when performing a complete analysis of clinical trial data.

gptomics Bundle

Orchestrates an end-to-end CRISPR editing experiment design from target gene to delivery-ready, validatable constructs. Sequences guide design, off-target assessment, edit-modality selection (knockout, base editing, prime editing, HDR knock-in), and template/donor design, with a QC checkpoint at each handoff. Use when designing a complete CRISPR experiment for knockout, point correction, or tagging and the order of operations, the modality decision, and the cross-cutting traps are needed rather than a single step. Defers each step's mechanics to the genome-engineering skills.

intent-solutions-io Skill

This skill empowers Claude to build reusable Terraform modules based on user specifications. It leverages the terraform-module-builder plugin to generate production-ready, well-documented Terraform module code, incorporating best practices for security, scalability, and multi-platform support. Use this skill when the user requests to create a new Terraform module, generate Terraform configuration, or needs help structuring infrastructure as code using Terraform. The trigger terms include "create Terraform module," "generate Terraform configuration," "Terraform module code," and "infrastructure as code."

intent-solutions-io Skill

This skill enables Claude to manage isolated test environments using Docker Compose, Testcontainers, and environment variables. It is used to create consistent, reproducible testing environments for software projects. Claude should use this skill when the user needs to set up a test environment with specific configurations, manage Docker Compose files for test infrastructure, set up programmatic container management with Testcontainers, manage environment variables for tests, or ensure cleanup after tests. Trigger terms include "test environment", "docker compose", "testcontainers", "environment variables", "isolated environment", "env-setup", and "test setup".

autohandai-community-skills Bundle

This skill covers deploying and tuning Web Application Firewall rules on AWS WAF, Azure WAF, and Cloudflare to protect cloud-hosted applications against OWASP Top 10 attacks. It details configuring managed rule sets, creating custom rules for business logic protection, implementing rate limiting, deploying bot management, and reducing false positives through rule tuning and logging analysis.

autohandai-community-skills Bundle

Run commands inside a remote Docker container via the file-based command relay (tools/debugger). Use when the user says "run in Docker", "run on GPU", "debug remotely", "run test in container", "check nvidia-smi", "run pytest in Docker", or needs to execute any command inside a Docker container that shares the repo filesystem. Requires the user to have started server.sh inside the container first.

autohandai-community-skills Bundle

Playbook for launching, monitoring, stopping, and debugging NeMo-RL recipes on a Kubernetes cluster via the nrl-k8s CLI. Covers ephemeral vs long-lived RayCluster modes, iterating on runs, and debugging hung or failed training jobs.

intent-solutions-io Skill

This skill enables Claude to seamlessly integrate with various secrets managers like HashiCorp Vault and AWS Secrets Manager. It generates configurations and setup code, ensuring best practices for secure credential management. Use this skill when you need to manage sensitive information, generate production-ready configurations, or implement a security-first approach for your DevOps infrastructure. Trigger terms include "integrate secrets manager", "configure Vault", "AWS Secrets Manager setup", "manage credentials securely", or requests for secure configuration generation.

intent-solutions-io Skill

This skill empowers Claude to preprocess and clean data using automated pipelines. It is designed to streamline data preparation for machine learning tasks, implementing best practices for data validation, transformation, and error handling. Claude should use this skill when the user requests data preprocessing, data cleaning, ETL tasks, or mentions the need for automated pipelines for data preparation. Trigger terms include "preprocess data", "clean data", "ETL pipeline", "data transformation", and "data validation". The skill ensures data quality and prepares it for effective analysis and model training.

intent-solutions-io Skill

This skill enables Claude to validate application performance against defined budgets. It's useful for identifying performance regressions early in the development lifecycle. The skill is triggered when the user mentions "performance budget", "validate budget", "performance regression", or requests a check against performance metrics like "page load times", "bundle sizes", "API response times", or "Lighthouse scores". The plugin validates against predefined thresholds and alerts on violations. It is especially helpful in CI/CD pipelines to prevent performance degradation in production.

intent-solutions-io Skill

This skill enables Claude to automatically detect performance regressions in a CI/CD pipeline. It analyzes performance metrics, such as response time and throughput, and compares them against baselines or thresholds. Use this skill when the user requests to "detect performance regressions", "analyze performance metrics for regressions", or "find performance degradation" in a CI/CD environment. The skill is also triggered when the user mentions "baseline comparison", "statistical significance analysis", or "performance budget violations". It helps identify and report performance issues early in the development cycle.

intent-solutions-io Skill

This skill orchestrates complex, multi-stage deployment pipelines. It generates production-ready configurations and setup code based on user-specified requirements and infrastructure. Use this skill when the user asks to create a deployment pipeline, generate CI/CD configurations, or needs help with automating software deployments. Trigger terms include "deployment pipeline", "CI/CD", "automate deployment", "pipeline configuration", and "deployment orchestration".

gptomics Bundle

Detects m6A modifications from Oxford Nanopore direct-RNA-seq (DRS) signal using m6Anet (multiple-instance-learning over DRACH 5-mer signal). Covers the upstream pipeline (Dorado/Guppy basecalling -> minimap2 map-ont -> nanopolish eventalign -> m6anet dataprep -> m6anet inference), per-site vs per-read probability including the mod_ratio stoichiometry column, the DRACH-only constraint, minimum-coverage thresholds (20-50 reads/site), multi-condition comparison via xPore/Nanocompore/ELIGOS, Dorado native modification calling (RNA004, 2024+), and the cDNA-vs-DRS distinction (cDNA Nanopore CANNOT detect modifications). Use when calling m6A from ONT DRS without immunoprecipitation, choosing m6Anet vs xPore vs Nanocompore vs ELIGOS vs Dorado native, interpreting probability_modified vs mod_ratio vs per-read probabilities, deciding between m6Anet (known DRACH sites) and Dorado/Remora (genome-wide screening), pinning RNA002 vs RNA004 chemistry and basecaller versions, or troubleshooting eventalign/dataprep failures.

autohandai-community-skills Bundle

Parses Kubernetes API server audit logs (JSON lines) to detect exec-into-pod, secret access, RBAC modifications, privileged pod creation, and anonymous API access. Builds threat detection rules from audit event patterns. Use when investigating Kubernetes cluster compromise or building k8s-specific SIEM detection rules.

autohandai-community-skills Bundle

Detect unauthorized SaaS and cloud service usage (shadow IT) by analyzing proxy logs, DNS query logs, and netflow data using Python pandas for traffic pattern analysis and domain classification.

autohandai-community-skills Bundle

Secure Helm chart deployments by validating chart integrity, scanning templates for misconfigurations, and enforcing security contexts in Kubernetes releases.

intent-solutions-io Skill

This skill enables Claude to generate Infrastructure as Code (IaC) configurations. It uses the infrastructure-as-code-generator plugin to create production-ready IaC for Terraform, CloudFormation, Pulumi, ARM Templates, and CDK. Use this skill when the user requests IaC configurations for cloud infrastructure, specifying the platform (e.g., Terraform, CloudFormation) and cloud provider (e.g., AWS, Azure, GCP), or when the user needs help automating infrastructure deployment. Trigger terms include: "generate IaC", "create Terraform", "CloudFormation template", "Pulumi program", "infrastructure code".

intent-solutions-io Bundle

This skill enables Claude to generate CI/CD pipeline configurations for various platforms, including GitHub Actions, GitLab CI, and Jenkins. It is used when a user requests the creation of a CI/CD pipeline, specifies a platform (e.g., "GitHub Actions"), or mentions specific pipeline stages like "test," "build," "security," or "deploy." This skill is also useful when the user needs to automate software delivery, integrate security scanning, or set up multi-environment deployments. The skill is triggered by terms such as "CI/CD pipeline," "GitHub Actions pipeline," "GitLab CI configuration," or "Jenkins pipeline."

gptomics Bundle

End-to-end post-GWAS causal inference pipeline orchestrating heritability partitioning, genetic correlation, Mendelian randomization with CHP-aware sensitivity (CAUSE / LHC-MR), colocalization, fine-mapping with SuSiE / FOCUS, mediation, TWAS triangulation, cis-pQTL drug-target MR, effector-gene prioritization (L2G / PoPS / cS2G), and GenomicSEM common-factor GWAS. Use when triangulating causal inference across multiple complementary methods, prioritizing tissues via stratified LDSC, nominating or de-risking drug targets, mapping a lead SNP to a candidate effector gene, modeling shared genetic architecture across correlated traits, or producing a STROBE-MR-compliant publication-grade evidence battery from GWAS summary statistics.

gptomics Bundle

Orchestrates an end-to-end de novo genome assembly project, routing each step to the right genome-assembly skill rather than restating it. Profiles the genome first (k-mer spectrum -> size, heterozygosity, ploidy), QCs reads, chooses an assembly path by data type (SPAdes for Illumina, Flye for noisy long reads, hifiasm for HiFi, metaFlye for communities), polishes only when needed, decontaminates, scaffolds with Hi-C, and finishes with three-axis QC (contiguity + completeness + correctness). Use when assembling a genome from raw reads and deciding which assembler, whether to polish, and how to prove the result is good.

gptomics Bundle

Chains a somatic (tumor-normal) SNV/indel and structural-variant pipeline end to end with GATK Mutect2 (or Strelka2), wiring the somatic-specific machinery - panel-of-normals and gnomAD germline-resource priors, GetPileupSummaries/CalculateContamination, and LearnReadOrientationModel FFPE/oxoG orientation-bias filtering fed into FilterMutectCalls. Use when calling somatic mutations from a tumor-normal pair (or tumor-only with PoN caveats), deciding which artifact filter removes which class of false positive, reasoning about VAF/purity/ploidy and clonal-vs-subclonal detection, adding somatic SV/CNV or TMB/MSI/signatures, or routing variants to AMP/ASCO/CAP tier and oncogenicity interpretation (never germline ACMG).

gptomics Bundle

Estimates bivariate genetic correlation (rg) between traits from GWAS summary statistics or individual-level genotypes using cross-trait LDSC, HDL, LAVA, rho-HESS, GREML-bivariate, Popcorn, and HDL-L. Use when quantifying shared genetic architecture between two traits, screening MR validity before causal inference, distinguishing global from locus-level rg, estimating trans-ancestry rg, separating partial from full causation via LCV gcp, or producing a STROBE-MR-compliant cross-trait sensitivity battery. Cross-trait LDSC intercept absorbs sample overlap and is NOT a bias; HDL is biased under sample overlap above ~5%. High rg between exposure and outcome motivates CHP-aware MR sensitivity (CAUSE, LHC-MR).

autohandai-community-skills Bundle

Detect lateral movement in Azure AD/Entra ID environments using Microsoft Graph API audit logs, Azure Sentinel KQL hunting queries, and sign-in anomaly correlation to identify privilege escalation, token theft, and cross-tenant pivoting.

autohandai-community-skills Bundle

Installs NemoClaw, launches a sandbox, and runs the first agent prompt. Use when onboarding, installing, or launching a NemoClaw sandbox for the first time. Trigger keywords - nemoclaw quickstart, install nemoclaw openclaw sandbox, nemohermes quickstart, hermes agent nemoclaw, run hermes openshell sandbox, nemoclaw prerequisites, nemoclaw supported platforms, nemoclaw hardware software, nemoclaw windows wsl2 setup, nemoclaw install windows docker desktop.

autohandai-community-skills Bundle

Parses API Gateway access logs (AWS API Gateway, Kong, Nginx) to detect BOLA/IDOR attacks, rate limit bypass, credential scanning, and injection attempts. Uses pandas for statistical analysis of request patterns and anomaly detection. Use when investigating API abuse or building API-specific threat detection rules.