Developer Tools

Discover and install specialized agent skills from the open ecosystem when users need extended capabilities. Helps identify relevant skills by domain and task when users ask "how do I do X" or "find a skill for X" Provides npx skills find [query] command to search interactively and npx skills add <package> to install from GitHub or other sources Recommends skills based on install count (prefer 1K+), source reputation (official sources like Vercel, Anthropic), and GitHub stars to ensure quality Checks the skills.sh leaderboard first for battle-tested, popular options before running CLI searches

Relentless interviewing skill that stress-tests plans and designs through systematic questioning. Conducts deep-dive questioning across all aspects of a plan, walking through decision trees branch-by-branch until shared understanding is reached Automatically explores the codebase to answer questions where code context is available, reducing redundant back-and-forth Designed for design reviews, architecture validation, and pre-implementation planning where thorough vetting prevents downstream issues

Relentless design interrogation that stress-tests plans against your domain model and sharpens terminology inline. Explores your codebase to ground discussions in existing code, glossaries (CONTEXT.md), and architectural decisions (ADRs) Challenges fuzzy language, resolves terminology conflicts, and updates your domain glossary as decisions crystallize Tests design decisions against concrete scenarios to expose edge cases and boundary violations Creates or updates CONTEXT.md and ADRs only when warranted, keeping documentation lean and decision-focused

Analyze codebases for architectural friction and propose module-deepening refactors as testability improvements. Explores codebases organically to surface shallow modules, tightly-coupled components, and untested seams rather than following rigid heuristics Applies John Ousterhout's "deep module" principle: small interfaces hiding large implementations for better testability and AI navigability Generates multiple radically different interface designs (minimalist, flexible, caller-optimized, ports & adapters) via parallel sub-agents, then recommends the strongest approach Creates GitHub issue RFCs documenting the problem space, design trade-offs, and refactoring rationale

Test-driven development with vertical slices, behavior-focused tests, and incremental red-green-refactor cycles. Emphasizes integration-style tests that verify behavior through public APIs, not implementation details; tests should survive refactors unchanged Requires vertical slicing (one test → one implementation → repeat) instead of horizontal slicing (all tests first, then all code), preventing brittle, behavior-insensitive test suites Includes planning phase to confirm interface changes, prioritize behaviors to test, and design for testability before writing code Provides refactoring guidelines covering duplication extraction, module deepening, and SOLID principles, applied only after all tests pass

Fast, persistent browser automation with session continuity across sequential agent commands. Supports three browser modes: headless Chromium, real Chrome with profile support, and cloud-hosted remote browsers with proxy configuration Includes 15+ command categories covering navigation, page inspection, interactions, data extraction, cookie management, and JavaScript execution Offers cloud session management, local server tunneling via Cloudflare, and parallel subagent execution through remote sessions Built-in Python integration for setting variables, accessing the browser object, and running scripts within the automation context

Configuration scaffold for engineering skills to locate issue tracker, triage labels, and domain documentation. Explores the current repo to detect GitHub/GitLab remotes, existing AGENTS.md or CLAUDE.md , and domain doc layout before prompting Walks through three guided decisions one at a time: issue tracker location (GitHub, GitLab, local markdown, or custom), triage label vocabulary mapping, and domain doc structure (single or multi-context) Writes an ## Agent skills block to the appropriate root file and creates three reference docs under docs/agents/ that downstream skills ( to-issues , triage , diagnose , tdd , improve-codebase-architecture ) will read Allows editing of the draft configuration before committing changes; re-running is only needed if switching trackers or restarting from scratch

State machine-driven issue triage with role-based workflow management and agent brief generation. Two category roles ( bug , enhancement ) and five state roles ( needs-triage , needs-info , ready-for-agent , ready-for-human , wontfix ) guide issues through a standardized workflow Supports querying unlabeled issues, in-progress triage, and issues awaiting reporter feedback; presents results in priority buckets with one-line summaries Includes reproduction testing for bugs, grilling sessions for incomplete issues, and templates for triage notes and agent briefs Respects prior triage context, codebase ADRs, and out-of-scope knowledge bases to avoid re-asking resolved questions and surfacing prior rejections

Throwaway code that answers a single design or logic question through an interactive prototype. Choose between two branches: a terminal app for testing state machines and business logic, or multiple toggleable UI variations on a single route for design exploration Minimal setup with one command to run; state lives in memory with no persistence unless the question explicitly requires it Surface full state after every action so changes are immediately visible and the prototype's answer is clear Delete or fold validated decisions back into production code once the question is answered; capture the verdict before cleanup

Systematic diagnosis and remediation for Azure production issues using AppLens, Monitor, and resource health. Covers Container Apps, Function Apps, and AKS troubleshooting with service-specific guides for image pulls, cold starts, health probes, invocation failures, and node/pod issues Integrates AppLens (MCP) for AI-powered root cause analysis and Azure Monitor (MCP) for KQL-based log and metric queries Provides a five-step diagnostic flow: identify symptoms, check resource health, review logs, analyze metrics, and investigate recent changes Includes quick reference commands for activity logs, container logs, and App Insights queries, plus routing guidance for AKS-specific incidents

Execute Azure deployments for prepared applications with built-in error recovery and validation. Requires .azure/plan.md with Validated status from azure-validate and azure-prepare skills; will not proceed without both prerequisites Executes azd up , azd deploy , terraform apply , and az deployment commands with error handling and post-deployment verification Includes pre-deploy checklist, recipe-based deployment workflows, and post-deploy configuration for SQL managed identity and Entity Framework migrations Supports applications with API Management gateway infrastructure created during preparation phase

Prepare Azure applications for deployment with infrastructure-as-code, configuration, and containerization. Generates Bicep or Terraform infrastructure code, azure.yaml configuration, and Dockerfiles based on application type and deployment target Requires mandatory plan-first workflow: analyze workspace, gather requirements, select recipe (AZD, AZCLI, Bicep, or Terraform), design architecture, then execute only after user approval Covers new app creation, modernization, and updates; routes specialized requests (copilot SDK, cloud migration, AI gateway) to dedicated skills before resuming preparation Hands off to azure-validate for infrastructure validation and azure-deploy for deployment execution; plan status must be updated to "Ready for Validation" before validation begins

Pre-deployment validation for Azure readiness with configuration, infrastructure, RBAC, and identity checks. Runs recipe-specific validation commands including Bicep builds, Terraform validation, and Azure CLI preflight checks Verifies RBAC role assignments in infrastructure code and managed identity permissions before deployment Requires .azure/deployment-plan.md from azure-prepare skill; records validation proof and updates plan status to Validated only after all checks pass Integrates into the three-step workflow: azure-prepare → azure-validate → azure-deploy

Unified access to Azure blob storage, file shares, queues, tables, and data lake services. Supports five storage service types: Blob Storage for objects and backups, File Shares for SMB access, Queue Storage for async messaging, Table Storage for NoSQL key-value data, and Data Lake for big data analytics MCP server tools enable listing storage accounts, containers, and blobs, plus downloading and uploading blob content directly Configurable access tiers (hot, cool, cold, archive) and redundancy options (LRS, ZRS, GRS, GZRS) for cost and durability optimization CLI fallback available via az storage commands when MCP is not enabled; SDK references provided for Python, TypeScript, Java, Rust, and Go

Microsoft Entra ID app registration, OAuth 2.0 configuration, and MSAL integration for secure application authentication. Covers app registration setup, authentication configuration, API permissions, and client credential management across web apps, SPAs, mobile apps, and daemon services Includes step-by-step workflows for first-time registration, console application authentication, and service-to-service credential flows Provides Azure CLI commands, MSAL library examples for .NET, JavaScript, Python, and Java, plus security best practices for secret rotation and token validation Distinguishes scope clearly: handles identity and authentication setup but excludes Azure RBAC, Key Vault secrets management, and resource security

Guidance and reference material for instrumenting webapps with Azure Application Insights. Covers SDK setup, telemetry patterns, and configuration for ASP.NET Core and Node.js applications hosted in Azure Distinguishes between this skill (reference and guidance) and azure-prepare (actual implementation); invoke azure-prepare when the user wants to add instrumentation to their project Provides auto-instrumentation guidance for C# ASP.NET Core apps in Azure App Service, plus manual instrumentation paths for creating App Insights resources via Bicep templates or Azure CLI Includes language-specific code modification guides for ASP.NET Core, Node.js, and Python, plus quick references for OpenTelemetry SDKs and exporters

Fast discovery and inventory of Azure resources across subscriptions using Resource Graph queries. Queries any Azure resource type (VMs, storage accounts, web apps, container apps, Key Vaults, etc.) across subscriptions and resource groups in a single command Supports cross-cutting searches for orphaned resources, missing tags, unhealthy states, and resource inventory counts Routes single-resource-type queries to dedicated MCP tools when available; falls back to Azure Resource Graph for broader or unsupported resource types Uses KQL (Kusto Query Language) for flexible filtering, with built-in error handling for authorization, syntax, and scope issues

Transform Azure resource groups into detailed architecture diagrams showing resource relationships and configurations. Discovers all resources within a resource group and analyzes their configurations, dependencies, and interconnections Generates Mermaid diagrams organized by logical layers (Network, Compute, Data, Security, Monitoring) with SKU details and connection labels Maps relationships including network connections, data flows, identity bindings, and configuration dependencies across resources Creates comprehensive markdown documentation with resource inventory tables, architecture diagrams, and relationship explanations