LLM Mart Basic
@llm-mart · Joined Jun 2026
Integrate ManagedCode.Orleans.Graph into an Orleans-based .NET application for graph-oriented relationships, edge management, and traversal logic on top of Orleans grains. Use when the application models graph structures in a distributed Orleans system.
Use ManagedCode.Orleans.SignalR when a distributed .NET application needs Orleans-based coordination of SignalR real-time messaging, hub delivery, and grain-driven push flows.
Use ManagedCode.Storage when a .NET application needs a provider-agnostic storage abstraction with explicit configuration, container selection, upload and download flows, and backend-specific integration kept behind one library contract.
Build, review, or migrate .NET MAUI applications across Android, iOS, macOS, and Windows with correct cross-platform UI, platform integration, and native packaging assumptions.
Adopt MCAF governance in a .NET repository with the right AGENTS.md layout, repo-native docs, skill installation, verification rules, and non-trivial task workflow. Use when bootstrapping or updating MCAF alongside the dotnet-skills catalog.
Apply MCAF agile-delivery guidance for backlog quality, roles, ceremonies, and engineering feedback. Use when defining how the team plans, tracks work, and turns feedback into durable improvements.
Apply MCAF developer-experience guidance for onboarding, F5 contract, cross-platform tasks, local inner loop, and reproducible setup. Use when the repo is hard to run, debug, test, or onboard into.
Apply MCAF documentation guidance for docs structure, navigation, source-of-truth placement, and writing quality. Use when a repo’s docs are missing, stale, duplicated, or hard to navigate, or when adding new durable engineering guidance.
Apply MCAF human-review-planning guidance for a large AI-generated code drop by reading the target area, tracing the natural user and system flows, identifying the riskiest boundaries, and prioritizing the files a human should inspect first. Use when the codebase is too large to
Apply MCAF ML/AI delivery guidance for data exploration, feasibility, experimentation, testing, responsible AI, and operating ML systems. Use when the repo includes model training, inference, data science workflows, or ML-specific delivery planning.
Apply MCAF non-functional-requirements guidance to capture or refine explicit quality attributes such as accessibility, reliability, scalability, maintainability, performance, and compliance. Use when a feature or architecture change needs explicit quality attributes and trade-of
Apply MCAF source-control guidance for repository structure, branch naming, merge strategy, commit hygiene, and secrets-in-git discipline. Use when bootstrapping a repo, tightening PR flow, or documenting branch and release policy.
Apply MCAF UI/UX guidance for design systems, accessibility, front-end technology selection, and design-to-development collaboration. Use when bootstrapping a UI project, choosing front-end stack, or tightening design and accessibility practices.
Build or consume Model Context Protocol (MCP) servers and clients in .NET using the official MCP C# SDK, including stdio, Streamable HTTP, tools, prompts, resources, and capability negotiation.
Use Metalint in .NET repositories that ship Node-based frontend assets and want one CLI entrypoint over several underlying linters. Use when a repo wants to orchestrate ESLint, Stylelint, HTMLHint, and related frontend checks from a single checked-in `.metalint/` configuration.
Use the open-source free `Meziantou.Analyzer` package for design, usage, security, performance, and style rules in .NET. Use when a repo wants broader analyzer coverage with a single NuGet package.
Build .NET AI agents and multi-agent workflows with Microsoft Agent Framework using the right agent type, threads, tools, workflows, hosting protocols, and enterprise guardrails.
Use the Microsoft.Extensions stack correctly across Generic Host, dependency injection, configuration, logging, options, HttpClientFactory, and other shared infrastructure patterns.
Build provider-agnostic .NET AI integrations with `Microsoft.Extensions.AI`, `IChatClient`, embeddings, middleware, structured output, vector search, and evaluation.
Design and implement Minimal APIs in ASP.NET Core using handler-first endpoints, route groups, filters, and lightweight composition suited to modern .NET services.
/group-chat
Group chat
Create a multi-agent group chat with AG2 using configurable speaker selection patterns
/new-a2a-agent
New a2a agent
Scaffold an A2A-compliant AG2 agent with server wiring, card settings, and skill definitions
/new-agent
New agent
Scaffold a new AG2 ConversableAgent with tool functions, system prompt, and LLM config
/new-tool
New tool
Create a tool function for an AG2 agent with type annotations, docstrings, and JSON return contracts
/sequential-workflow
Sequential workflow
Create a sequential multi-agent pipeline where each agent processes and passes results to the next
/workflow-from-spec
Workflow from spec
Design a complete multi-agent workflow from a natural language description, selecting the right orchestration pattern
/act
Act
Follow RED-GREEN-REFACTOR cycle approach for test-driven development
/add-authentication-system
Add authentication system
Implement secure user authentication system
/add-changelog
Add changelog
Generate and maintain project changelog
/add-mutation-testing
Add mutation testing
Setup mutation testing for code quality
/add-package
Add package
Add and configure new project dependencies
/add-performance-monitoring
Add performance monitoring
Setup application performance monitoring
/add-property-based-testing
Add property based testing
Implement property-based testing framework
/add-to-changelog
Add to changelog
Add a new entry to the project's CHANGELOG.md file following Keep a Changelog format
/agent-preflight
Agent preflight
Preflight a repo before AI agents change files
/all-tools
All tools
Display all available development tools
/architecture-review
Architecture review
Review and improve system architecture
/architecture-scenario-explorer
Architecture scenario explorer
Explore architectural decisions through systematic scenario analysis with trade-off evaluation and future-proofing assessment.
/bidirectional-sync
Bidirectional sync
Enable bidirectional GitHub-Linear synchronization
/big-features-interview
Big features interview
Interview to flesh out a plan/spec
Make any song you can imagine
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