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Found 3,341 Skills
Create and configure git hooks with intelligent project analysis, suggestions, and automated testing
Perform comprehensive gene enrichment and pathway analysis using gseapy (ORA and GSEA), PANTHER, STRING, Reactome, and 40+ ToolUniverse tools. Supports GO enrichment (BP, MF, CC), KEGG, Reactome, WikiPathways, MSigDB Hallmark, and 220+ Enrichr libraries. Handles multiple ID types (gene symbols, Ensembl, Entrez, UniProt), multiple organisms (human, mouse, rat, fly, worm, yeast), customizable backgrounds, and multiple testing correction (BH, Bonferroni). Use when users ask about gene enrichment, pathway analysis, GO term enrichment, KEGG pathway analysis, GSEA, over-representation analysis, functional annotation, or gene set analysis.
Production-ready RNA-seq differential expression analysis using PyDESeq2. Performs DESeq2 normalization, dispersion estimation, Wald testing, LFC shrinkage, and result filtering. Handles multi-factor designs, multiple contrasts, batch effects, and integrates with gene enrichment (gseapy) and ToolUniverse annotation tools (UniProt, Ensembl, OpenTargets). Supports CSV/TSV/H5AD input formats and any organism. Use when analyzing RNA-seq count matrices, identifying DEGs, performing differential expression with statistical rigor, or answering questions about gene expression changes.
Write idiomatic Ruby code with metaprogramming, Rails patterns, and performance optimization. Specializes in Ruby on Rails, gem development, and testing frameworks. Use PROACTIVELY for Ruby refactoring, optimization, or complex Ruby features.
Titanium SDK architecture and implementation expert. Use when designing, reviewing, analyzing, or examining Titanium project structure (Alloy or Classic), creating controllers/views/services, choosing models vs collections, implementing communication patterns, handling memory cleanup, testing, auditing code, or migrating legacy apps. Automatically identifies project type.
Shared Python best practices for LlamaFarm. Covers patterns, async, typing, testing, error handling, and security.
Comprehensive toolkit for validating, linting, testing, and automating Terragrunt configurations, HCL files, and Stacks. Use this skill when working with Terragrunt files (.hcl, terragrunt.hcl, terragrunt.stack.hcl), validating infrastructure-as-code, debugging Terragrunt configurations, performing dry-run testing with terragrunt plan, working with Terragrunt Stacks, or working with custom providers and modules.
Disaster recovery drill exercises and security checklists for web application projects (SPA, SSR, full-stack web apps). Focused on solo/indie developers using free-tier infrastructure (Vercel, Supabase, Cloudflare, Netlify, Railway, etc.). Bridges big-tech best practices (NIST, Google SRE DiRT, ISO 22301) to indie scale. Use when the user mentions drills, disaster recovery, security audit, incident simulation, project health check, resilience testing, backup strategies, secret rotation, or incident response for web projects. Not for mobile apps, desktop software, CLI tools, or games.
Build and operate Convex backends: functions (queries/mutations/actions/http actions), schemas, auth patterns, scheduling (cron/scheduled/workflows), file storage, testing, and debugging. Triggers: "convex", "query", "mutation", "action", "httpAction", "schema", "validator", "cron", "schedule", "workflow", "workpool", "ctx.db", "ctx.auth", "convex dev".
Comprehensively reviews Python libraries for quality across project structure, packaging, code quality, testing, security, documentation, API design, and CI/CD. Provides actionable feedback and improvement recommendations. Use when evaluating library health, preparing for major releases, or auditing dependencies.
Configure Exa local development with hot reload and testing. Use when setting up a development environment, configuring test workflows, or establishing a fast iteration cycle with Exa. Trigger with phrases like "exa dev setup", "exa local development", "exa dev environment", "develop with exa".
Set up uv (Rust-based Python package manager) in CI/CD pipelines. Use when configuring GitHub Actions workflows, GitLab CI/CD, Docker builds, or matrix testing across Python versions. Includes patterns for cache optimization, frozen lockfiles, multi-stage builds, and PyPI publishing with trusted publishing. Covers GitHub Actions setup-uv action, Docker multi-stage production/development builds, and deployment patterns.