▸case-01 I'm building a plan-and-execute agent in C# and need a code snippet showing how to initialize the main orchestrator, register my custom API tools, and wire up a vector database for context storage. Please provide the complete setup code. | fail→fail | 18,368 | 12,586 | -31% | 1 | 1 | 0% | 3,458 | 2,845 | -18% | 0 | 0 | — |
▸case-02 I need an architectural overview and a starter code template for linking multiple prompt-based tasks together sequentially, where the output of one feeds into the next. Please include the recommended approach for managing failures during this sequence. | fail→pass | 19,108 | 14,748 | -23% | 1 | 1 | 0% | 3,718 | 2,914 | -22% | 0 | 0 | — |
▸case-03 When building an AI application that needs to break down a user's high-level goal into a sequence of executable steps, what specific component should I use to handle this decomposition? I've seen people use LangChain agents, but I want the recommended approach for the Microsoft ecosystem. | fail→fail | 12,632 | 8,951 | -29% | 1 | 1 | 0% | 2,109 | 1,767 | -16% | 0 | 0 | — |
▸case-04 I am setting up a new C# AI project. I need a central object that acts as the main orchestrator to hold my AI services, tools, and configuration. Should I just use a static dictionary, or is there a specific class I should instantiate? | fail→fail | 11,777 | 7,807 | -34% | 1 | 1 | 0% | 2,300 | 1,621 | -30% | 0 | 0 | — |
▸case-05 I have several dozen utility functions (like math operations and string formatting) that I want my AI to be able to call. Instead of passing them all as a massive flat JSON array to the OpenAI API, how should I group and register these collections in my orchestration setup? | fail→pass | 15,652 | 11,761 | -25% | 1 | 1 | 0% | 2,664 | 2,399 | -10% | 0 | 0 | — |
▸case-06 My chatbot needs to remember past conversations and retrieve relevant documents based on semantic similarity. Instead of writing raw HTTP calls to Pinecone or Qdrant, what abstraction should I implement in my orchestration framework to handle this context storage? | fail→fail | 14,169 | 11,944 | -16% | 1 | 1 | 0% | 2,649 | 2,452 | -7% | 0 | 0 | — |
▸case-07 I am building a function-calling-agent. I want the LLM to automatically invoke my registered tools without me having to manually parse the tool_calls response and write a while-loop. How do I configure the execution settings to achieve this? | fail→fail | 11,714 | 11,208 | -4% | 1 | 1 | 0% | 2,280 | 2,503 | +10% | 0 | 0 | — |
▸case-08 I need a planner that can generate complex plans using a templating language, allowing for loops and conditionals within the plan itself before execution. The old ActionPlanner doesn't support this. Which specific planner type should I select? | fail→fail | 5,392 | 5,802 | +8% | 1 | 1 | 0% | 911 | 1,231 | +35% | 0 | 0 | — |
▸case-09 I am designing an agent that needs to perform iterative reasoning, where it takes an action, observes the result, and then decides the next action (similar to a ReAct loop). Which specific planner type is designed for this iterative discovery process? | fail→fail | 10,504 | 5,773 | -45% | 1 | 1 | 0% | 1,805 | 1,324 | -27% | 0 | 0 | — |
▸case-10 I need an iterative reasoning planner that specifically leverages the native tool-calling capabilities of modern models (like GPT-4's tool use) rather than relying purely on prompt-based text parsing for its ReAct loop. Which planner type should I configure? | pass→pass | 11,421 | 7,968 | -30% | 1 | 1 | 0% | 2,073 | 1,618 | -22% | 0 | 0 | — |
▸case-11 To power my orchestration framework, I need to connect it to a backend LLM. What are the primary configuration options or components I should use to link the framework to models hosted on Microsoft's cloud or directly from the creators of GPT-4? | fail→fail | 11,441 | 9,521 | -17% | 1 | 1 | 0% | 2,205 | 2,207 | +0% | 0 | 0 | — |
▸case-12 When exposing my native C# methods to the AI orchestrator, the model sometimes hallucinates arguments or misunderstands what the method does. What is the most critical best practice I must apply to my method definitions to fix this? | fail→fail | 12,950 | 8,185 | -37% | 1 | 1 | 0% | 1,802 | 1,626 | -10% | 0 | 0 | — |
▸case-13 As my AI project grows, I have hundreds of tools for file system access, database queries, and API calls. What best practice should I follow to manage this complexity within the orchestrator? | fail→fail | 13,809 | 13,062 | -5% | 1 | 1 | 0% | 2,360 | 2,480 | +5% | 0 | 0 | — |
▸case-14 My application has both simple single-step commands and complex multi-step research tasks. Should I just use a Stepwise approach for everything to be safe, or is there a specific best practice regarding how to choose the execution strategy? | fail→pass | 15,095 | 14,174 | -6% | 1 | 1 | 0% | 2,465 | 2,691 | +9% | 0 | 0 | — |
▸case-15 When executing a chain of AI tasks, API rate limits or malformed model outputs frequently cause the entire process to crash. What best practice must be implemented in the orchestration setup to ensure robustness? | fail→pass | 10,139 | 9,622 | -5% | 1 | 1 | 0% | 1,899 | 1,812 | -5% | 0 | 0 | — |
▸case-16 I am setting up a new .NET project to build a plan-and-execute agent using Microsoft's official AI orchestration patterns. What is the primary NuGet package dependency I need to install to get the core orchestrator, planners, and plugin system? | fail→fail | 5,906 | 3,607 | -39% | 1 | 1 | 0% | 1,095 | 868 | -21% | 0 | 0 | — |
▸case-17 In this orchestration framework, I need to create reusable components. Some of these will be written as prompts for the LLM, while others will be standard C# code that executes locally. What are the two specific terms used to categorize these creations? | fail→fail | 4,654 | 2,861 | -39% | 1 | 1 | 0% | 853 | 707 | -17% | 0 | 0 | — |
▸case-18 I need visibility into what my AI agent is doing under the hood—specifically the exact prompts being sent to the LLM and the raw responses coming back. What configuration option should I enable on the central orchestrator to capture this data? | fail→fail | 11,578 | 10,125 | -13% | 1 | 1 | 0% | 2,031 | 2,183 | +7% | 0 | 0 | — |
▸case-19 I want to swap out my local volatile vector storage for a persistent Redis instance so my agent's context survives restarts. What specific configuration option do I need to update in the orchestrator setup? | fail→pass | 11,462 | 7,346 | -36% | 1 | 1 | 0% | 2,035 | 1,512 | -26% | 0 | 0 | — |
▸case-20 I am using Microsoft's AI orchestration framework in C#. I need to parse a large HTML document to extract all the <a> tags and their href attributes before passing the text to the LLM. Which specific native function built into the orchestration framework should I call to parse the DOM? | fail→fail | 8,784 | 7,596 | -14% | 1 | 1 | 0% | 1,690 | 1,654 | -2% | 0 | 0 | — |
▸case-21 I am configuring my C# AI agent's memory store using Microsoft's orchestration framework. I need to store 500GB of relational user profile data with complex SQL joins. Which specific memory connector in the framework is optimized for executing complex SQL joins? | fail→fail | 14,867 | 10,144 | -32% | 1 | 1 | 0% | 2,640 | 2,184 | -17% | 0 | 0 | — |
▸case-22 I am building a C# AI agent. I need to authenticate my users using OAuth2 and issue JWT tokens when they log into the web application. Which specific planner in Microsoft's AI orchestration framework should I use to generate and sign the JWT tokens? | fail→fail | 12,532 | 11,325 | -10% | 1 | 1 | 0% | 2,150 | 2,207 | +3% | 0 | 0 | — |