Umbrella skill for document workflows (PDF/DOCX/XLSX/PPTX). Dispatches to the most specific document skill to reduce noise and improve routing precision.

Access Human Metabolome Database (220K+ metabolites). Search by name/ID/structure, retrieve chemical properties, biomarker data, NMR/MS spectra, pathways, for metabolomics and identification.

hypothesis-testing

property-based-testing

Perform cross-artifact consistency analysis across spec.md, plan.md,

Execute all tasks from the task breakdown to build the feature. Use after

Generate technical implementation plans from feature specifications.

Break down implementation plans into actionable task lists. Use after

Use ONLY when user says "search", "find", "look up", "ask", "research", or "what's the latest" for generic queries. NOT for library/framework docs (use Context7), gt CLI (use Graphite MCP), or workspa

Creates VS Code custom agent files (.agent.md) for specialized AI personas with tools, instructions, and handoffs. Use when scaffolding new custom agents, configuring agent workflows, or setting up agent-to-agent handoffs.

Scaffolds new agent skills for the dotnet/skills repository. Use when creating a new skill, generating SKILL.md files, or setting up skill directory structures. Handles frontmatter generation, section templates, and validation guidance.

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Guides technology selection and implementation of AI and ML features in .NET 8+ applications using ML.NET, Microsoft.Extensions.AI (MEAI), Microsoft Agent Framework (MAF), GitHub Copilot SDK, ONNX Runtime, and OllamaSharp. Covers the full spectrum from classic ML through modern LLM orchestration to local inference. Use when adding classification, regression, clustering, anomaly detection, recommendation, LLM integration (text generation, summarization, reasoning), RAG pipelines with vector search, agentic workflows with tool calling, Copilot extensions, or custom model inference via ONNX Runtime to a .NET project. DO NOT USE FOR projects targeting .NET Framework (requires .NET 8+), the task is pure data engineering or ETL with no ML/AI component, or the project needs a custom deep learning training loop (use Python with PyTorch/TensorFlow, then export to ONNX for .NET inference).

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Golang benchmarking, profiling, and performance measurement. Use when writing, running, or comparing Go benchmarks, profiling hot paths with pprof, interpreting CPU/memory/trace profiles, analyzing results with benchstat, setting up CI benchmark regression detection, or investigating production performance with Prometheus runtime metrics. Also use when the developer needs deep analysis on a specific performance indicator - this skill provides the measurement methodology, while golang-performance provides the optimization patterns.

Comprehensive guide for dependency injection (DI) in Golang. Covers why DI matters (testability, loose coupling, separation of concerns, lifecycle management), manual constructor injection, and DI library comparison (google/wire, uber-go/dig, uber-go/fx, samber/do). Use this skill when designing service architecture, setting up dependency injection, refactoring tightly coupled code, managing singletons or service factories, or when the user asks about inversion of control, service containers, or wiring dependencies in Go.

Provides a comprehensive guide for writing production-ready Golang tests. Covers table-driven tests, test suites with testify, mocks, unit tests, integration tests, benchmarks, code coverage, parallel tests, fuzzing, fixtures, goroutine leak detection with goleak, snapshot testing, memory leaks, CI with GitHub Actions, and idiomatic naming conventions. Use this whenever writing tests, asking about testing patterns or setting up CI for Go projects. Essential for ANY test-related conversation in Go.

Troubleshoot Golang programs systematically - find and fix the root cause. Use when encountering bugs, crashes, deadlocks, or unexpected behavior in Go code. Covers debugging methodology, common Go pitfalls, test-driven debugging, pprof setup and capture, Delve debugger, race detection, GODEBUG tracing, and production debugging. Start here for any 'something is wrong' situation. Not for interpreting profiles or benchmarking (see golang-benchmark skill) or applying optimization patterns (see golang-performance skill).

Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends AIPex's capabilities with specialized knowledge, workflows, or tool integrations.

WCAG 2.2 Accessibility Audit skill that systematically evaluates web pages against 8 core Success Criteria (1.1.1, 1.4.3, 1.4.11, 2.1.1, 2.1.2, 2.4.3, 2.4.7, 4.1.2) using accessibility tree inspection and visual analysis. Use this skill when you need to perform accessibility testing/auditing on a live webpage.

Clarify requirements before implementing. Do not use automatically, only when invoked explicitly.

Use when moving skills between library workspaces or upgrading from a personal library to a team library. Export from one workspace, import into another.

Discovers, searches, and installs skills from multiple AI agent skill marketplaces (400K+ skills) using the SkillKit CLI. Supports browsing official partner collections (Anthropic, Vercel, Supabase, Stripe, and more) and community repositories, searching by domain or technology, and installing specific skills from GitHub. Use when the user wants to find, browse, or install new agent skills, plugins, extensions, or add-ons; asks 'is there a skill for X' or 'find a skill for X'; wants to explore a skill store or marketplace; needs to extend agent capabilities in areas like React, testing, DevOps, security, or APIs; or says 'browse skills', 'search skill marketplace', 'install a skill', or 'what skills are available'.

Bug diagnosis and fixing specialist - analyzes errors, identifies root causes, provides fixes, and writes regression tests. Use for bug, debug, error, crash, traceback, exception, and regression work.

Use when setting up or optimizing developer workflows in a monorepo, managing mise tasks, git hooks, CI/CD pipelines, database migrations, or release automation. Invoke for development environment setup, build automation, testing workflows, and release coordination.

Intent-based observability + traceability router across layers, boundaries, and signals. Routes to vendor-specific skills via category taxonomy; owns transport tuning, meta-observability, incident forensics. Use for observability, traceability, telemetry, APM, RUM, metrics, logs, traces, profiles, SLO, incident forensics, tracing architecture work.

Automated multi-agent orchestrator that spawns CLI subagents in parallel, coordinates via MCP Memory, and monitors progress. Use for orchestration, parallel execution, and automated multi-agent workflows.

Infrastructure-as-code specialist for multi-cloud provisioning using Terraform across any provider (AWS, GCP, Azure, Oracle Cloud). Use for terraform plan/apply, state management, compute, databases, storage, networking, IAM, OIDC, cost optimization, policy-as-code, ISO/IEC 42001 AI controls, ISO 22301 continuity, and ISO/IEC/IEEE 42010 architecture documentation.

Orchestrates AWS Amplify Gen 2 workflows for building full-stack apps with React, Next.js, Vue, Angular, React Native, Flutter, Swift, or Android. Use when user wants to BUILD, CREATE, or DEPLOY Amplify projects, add authentication, data models, storage, GraphQL APIs, Lambda functions, or deploy to sandbox/production. Do NOT invoke for conceptual questions, comparisons, or troubleshooting unrelated to active development.

Design, build, deploy, test, and debug serverless applications with AWS Lambda. Triggers on phrases like: Lambda function, event source, serverless application, API Gateway, EventBridge, Step Functions, serverless API, event-driven architecture, Lambda trigger. For deploying non-serverless apps to AWS, use deploy-on-aws plugin instead.

Creates a reusable use case specification file that defines the business problem, stakeholders, and measurable success criteria for model customization, as recommended by the AWS Responsible AI Lens. Use as the default first step in any model customization plan. Skip only if the user explicitly declines or already has a use case specification to reuse. Captures problem statement, primary users, and LLM-as-a-Judge success tenets.

Initialize evo for the current repository by exploring the codebase, proposing unexplored optimization dimensions, constructing the benchmark inside a baseline worktree, and running the first experiment. Use when the user invokes /evo:discover, mentions setting up evo, wants to instrument a codebase for autonomous optimization, or asks to start a new evo run on a project.

Expert knowledge for Azure App Testing development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when using Azure Load Testing with VNets/private endpoints, JMeter/Locust/Playwright, CI/CD pipelines, or Playwright Workspaces, and other Azure App Testing related development tasks. Not for Azure Test Plans (use azure-test-plans), Playwright Workspaces (use azure-playwright-workspaces), Azure DevOps (use azure-devops), Azure App Service (use azure-app-service).

Expert knowledge for Azure Business Process Tracking development including deployment. Use when creating CI/CD pipelines, automating builds, running tests, and deploying tracking solutions via DevOps tools, and other Azure Business Process Tracking related development tasks. Not for Azure Monitor (use azure-monitor), Azure Logic Apps (use azure-logic-apps), Azure Data Factory (use azure-data-factory), Azure Machine Learning (use azure-machine-learning).

Expert knowledge for Azure Confidential Ledger development including decision making, security, integrations & coding patterns, and deployment. Use when configuring Entra ID/RBAC, client certs, node attestation, .NET SDK, JavaScript UDFs, or ARM/Terraform deployments, and other Azure Confidential Ledger related development tasks. Not for Azure Confidential Computing (use azure-confidential-computing), Azure Key Vault (use azure-key-vault), Azure Dedicated HSM (use azure-dedicated-hsm), Azure Cloud Hsm (use azure-cloud-hsm).

Expert knowledge for Azure Deployment Environments development including troubleshooting, best practices, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when designing ADE catalogs, environment.yaml schemas, custom images, RBAC/roles, or CI/CD image pipelines, and other Azure Deployment Environments related development tasks. Not for Azure DevTest Labs (use azure-devtest-labs), Azure Dev Box (use azure-dev-box), Azure Integration Environments (use azure-integration-environments), Azure Managed Applications (use azure-managed-applications).

Expert knowledge for Azure Dev Box development including troubleshooting, best practices, decision making, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when designing Dev Box images, catalogs, policies, schedules, RBAC/SSO access, or VS Code dev tunnel workflows, and other Azure Dev Box related development tasks. Not for Azure DevTest Labs (use azure-devtest-labs), Azure Virtual Machines (use azure-virtual-machines), Azure Virtual Desktop (use azure-virtual-desktop).

Expert knowledge for Azure DevOps development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when managing Boards/work items, pipelines, repos, Analytics/OData/Power BI, or Azure DevOps Server deployments, and other Azure DevOps related development tasks. Not for Azure Boards (use azure-boards), Azure Pipelines (use azure-pipelines), Azure Repos (use azure-repos), Azure Test Plans (use azure-test-plans).

Expert knowledge for Azure DevTest Labs development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when managing DevTest Labs VMs, images/artifacts, ARM/CLI automation, RBAC/Key Vault security, or hub-spoke lab setups, and other Azure DevTest Labs related development tasks. Not for Azure Dev Box (use azure-dev-box), Azure Lab Services (use azure-lab-services), Azure Virtual Machines (use azure-virtual-machines), Azure Virtual Desktop (use azure-virtual-desktop).

Expert knowledge for Azure Lab Services development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when configuring lab plans, VM templates/schedules, VNet-integrated labs, GPU/nested virtualization, or Canvas/Teams integration, and other Azure Lab Services related development tasks. Not for Azure DevTest Labs (use azure-devtest-labs), Azure Virtual Machines (use azure-virtual-machines), Azure Virtual Desktop (use azure-virtual-desktop).

Expert knowledge for Azure Pipelines development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when configuring YAML pipelines, self-hosted agents, service connections, Key Vault secrets, or Web App/Kubernetes deploys, and other Azure Pipelines related development tasks. Not for Azure DevOps (use azure-devops), Azure Boards (use azure-boards), Azure Repos (use azure-repos), Azure Test Plans (use azure-test-plans).

Expert knowledge for Azure Resource Manager development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when authoring Bicep/ARM templates, CI/CD deployments, template specs, deployment stacks, or ARM REST/CLI automations, and other Azure Resource Manager related development tasks. Not for Azure Blueprints (use azure-blueprints), Azure Policy (use azure-policy), Azure Portal (use azure-portal), Azure Resource Graph (use azure-resource-graph).

Expert knowledge for Azure Test Plans development including limits & quotas, security, and integrations & coding patterns. Use when configuring custom test run fields, managing test access, or automating suites via tcm.exe and test configs, and other Azure Test Plans related development tasks. Not for Azure DevOps (use azure-devops), Azure Boards (use azure-boards), Azure Pipelines (use azure-pipelines), Azure App Testing (use azure-app-testing).

Manages iOS Simulator devices and tests app behavior using xcrun simctl. Covers device lifecycle (create, boot, shutdown, erase, delete), app install and launch, push notification simulation, location simulation, permission grants via privacy subcommand, deep link testing via openurl, status bar overrides, screenshot and video recording, log streaming with os_log filtering, get_app_container paths, and #if targetEnvironment(simulator) compile-time checks. Use when creating or managing simulator devices, testing push notifications without APNs, simulating GPS locations, granting or resetting privacy permissions, capturing screenshots or screen recordings from the command line, streaming device logs, debugging simulator boot failures, troubleshooting CoreSimulator issues, or checking simulator hardware limitations.