DevOps & Infra

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.

autohandai-community-skills Bundle

Serve a quantized or unquantized LLM checkpoint as an OpenAI-compatible API endpoint using vLLM, SGLang, or TRT-LLM. Use when user says "deploy model", "serve model", "start vLLM server", "launch SGLang", "TRT-LLM deploy", "AutoDeploy", "benchmark throughput", "serve checkpoint", or needs an inference endpoint from a HuggingFace or ModelOpt-quantized checkpoint. Do NOT use for quantizing models (use ptq) or evaluating accuracy (use evaluation).

autohandai-community-skills Bundle

Trivy is a comprehensive open-source vulnerability scanner by Aqua Security that detects vulnerabilities in OS packages, language-specific dependencies, misconfigurations, secrets, and license violati

autohandai-community-skills Bundle

Detect unusual API call patterns in AWS CloudTrail logs using boto3, statistical baselining, and behavioral analysis to identify credential compromise, privilege escalation, and unauthorized resource access.

gptomics Bundle

Analyzes base-editing screens for variant function. Covers library design (Hanna 2021 ClinVar-scale CBE screen benchmarked on BRCA1/2, Cuella-Martin 2021 DDR saturation), CBE vs ABE chemistry choice (BE3/BE4 vs ABE7.10/ABE8.20/ABE8e), editing-window math (positions 4-8 from PAM-distal end; 4-7 for ABE7.10), bystander-edit quantification and the variant-call ambiguity it creates, sgRNA-efficiency filtering before hit calling, indel byproduct interpretation, the substitution-vs-indel diagnostic, variant annotation against ClinVar / COSMIC, and the Broad be-validation-pipeline. Use when designing a BE variant screen, choosing CBE vs ABE for a specific edit, interpreting bystander-confounded hits, distinguishing functional signal from indel artifact, integrating CRISPResso2 output with screen scoring, or deciding BE vs PE for SNV installation.

gptomics Bundle

Discovers, classifies, filters, and quantifies full-length transcript isoforms from PacBio Iso-Seq/Kinnex (HiFi) and Oxford Nanopore (cDNA/direct-RNA) long reads, using the isoseq+pigeon pipeline, SQANTI3, and ONT tools (IsoQuant, FLAIR, Bambu, StringTie2). Covers why a novel isoform is an artifact until proven otherwise (RT template-switching, intra-priming, and 5' degradation manufacture junctions and truncations), the SQANTI3 structural categories and their trust order, the Kinnex skera-split step, orthogonal CAGE/poly-A/short-read-junction validation, and why long-read isoform quantification needs EM. Use when building a full-length isoform catalog, classifying/filtering long-read transcripts, running Iso-Seq or ONT cDNA/dRNA analysis, or judging novel-isoform reliability.

sboghossian-mini-claude-for-legal Skill

Use when implementing the document ingestion pipeline that splits legal texts into retrieval-optimized chunks for embedding and vector storage. Defines chunk-size targets, boundary rules, overlap strategy, and metadata tagging specific to the structure of legal documents (contracts, legislation, court decisions) across English, Arabic, and French.

autohandai-community-skills Bundle

Explains how to run NemoClaw on a remote GPU instance, including the deprecated Brev compatibility path and the preferred installer plus onboard flow. Use when deploying NemoClaw to a remote VM, onboarding a Brev instance, or migrating away from the legacy `nemoclaw deploy` wrapper. Trigger keywords - deploy nemoclaw remote gpu, nemoclaw brev cloud deployment, nemoclaw plugins, openclaw plugins, install openclaw plugin, nemoclaw onboard from dockerfile, nemoclaw brev web ui, nemoclaw getting started, brev quickstart, nvidia nemotron agent, nemoclaw sandbox hardening, container security, docker capabilities, process limits.

autohandai-community-skills Bundle

Deploy Nemotron Voice Agent on Workstation (x86), Jetson Thor, or Cloud NIMs. Real-time speech-to-speech using NVIDIA ASR, TTS, LLM with WebRTC/WebSocket transport.

autohandai-community-skills Bundle

Build and dependency management for NeMo-RL. Covers Docker image building and running, uv usage, venv setup, and adding dependencies.

gptomics Bundle

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 classification, and the limits of depth-only amplification calls. Use when a focal amplification needs structural characterization, when distinguishing ecDNA from chromosomal amplification, suspecting ecDNA-driven oncogene amplification or therapy resistance, or selecting copy-number seeds for amplicon reconstruction.

autohandai-community-skills Bundle

Kubernetes Role-Based Access Control (RBAC) auditing systematically reviews roles, cluster roles, bindings, and service account permissions to identify overly permissive access, privilege escalation p

autohandai-community-skills Bundle

Analyze WAF (ModSecurity/AWS WAF/Cloudflare) logs to detect SQL injection attack campaigns. Parses ModSecurity audit logs and JSON WAF event logs to identify SQLi patterns (UNION SELECT, OR 1=1, SLEEP(), BENCHMARK()), tracks attack sources, correlates multi-stage injection attempts, and generates incident reports with OWASP classification.

gptomics Bundle

Runs and configures curated nf-core community Nextflow pipelines (rnaseq, sarek, atacseq, methylseq, ampliseq, taxprofiler, fetchngs) reproducibly, pinning the pipeline revision with -r and selecting a container engine and institutional config via -profile. Use when deciding to adopt a community pipeline versus author one from scratch; picking a pipeline and pinning its -r revision; selecting -profile test/docker/singularity/conda plus an institutional config from nf-core/configs; building and validating a samplesheet CSV against the pipeline schema (nf-schema); choosing --genome/iGenomes versus custom references; configuring resources and max_memory for SLURM/AWS Batch; using -resume and -stub; and reading MultiQC outputs.

autohandai-community-skills Bundle

Deploy privileged access management for database systems including Oracle, SQL Server, PostgreSQL, and MySQL. Covers session proxy configuration, credential vaulting, query auditing, dynamic credentia

autohandai-community-skills Bundle

Bump the NVIDIA PyTorch base image using the nvcr.io/nvidia/pytorch YY.MM py3 tag used by Megatron-LM CI. Covers the two pin sites (GitHub CI in `docker/.ngc_version.dev` and GitLab CI in `.gitlab/stages/01.build.yml`), the post-bump CI loop (re-run functional tests, refresh golden values, mark broken tests), and the gotchas that bit PRs

autohandai-community-skills Bundle

Performs authorized penetration testing of cloud environments across AWS, Azure, and GCP to identify IAM misconfigurations, exposed storage buckets, overly permissive security groups, serverless function vulnerabilities, and cloud-specific attack paths from initial access to account compromise. The tester uses cloud-native tools and specialized frameworks like Pacu and ScoutSuite to enumerate and exploit cloud infrastructure. Activates for requests involving cloud pentest, AWS security assessment, Azure penetration testing, or cloud infrastructure security testing.

sboghossian-mini-claude-for-legal Skill

Use when migrating a Lawvable skill-optimizer tool into the mini-claude-for-legal format. The adapter maps Lawvable's skill-improvement pipeline — prompt quality scoring, output consistency testing, jurisdiction coverage gaps, and iterative refinement recommendations — into the standard skill model. Triggers when importing any Lawvable-native skill quality assurance or optimisation workflow.

sboghossian-mini-claude-for-legal Skill

Use when implementing or debugging the LLM token-streaming pipeline on iOS or Android clients. Defines buffering rules, reconnection logic, RTL rendering constraints, and mobile-specific UX patterns for streaming legal AI responses — including how to handle long-form document drafts that arrive over slow or intermittent mobile connections.

autohandai-community-skills Bundle

Detecting unauthorized cryptocurrency mining activity in cloud environments by analyzing compute usage anomalies, network traffic to mining pools, GuardDuty findings, and container workload behavior using AWS, Azure, and GCP native security services.

autohandai-community-skills Bundle

Harden the Docker daemon by configuring daemon.json with user namespace remapping, TLS authentication, rootless mode, and CIS benchmark controls.

autohandai-community-skills Bundle

Implement GCP Binary Authorization to enforce deploy-time security controls that ensure only trusted, attested container images are deployed to Google Kubernetes Engine and Cloud Run.