Operator-ready prompt for reuse, tuning, and workspace runs.
This item is set up for developers who want to inspect the original language, fork it into Workspace, and adapt the evidence model without losing the source prompt structure.
Implementation handoffs, eval setup, and prompt tuning where you need the original structure intact.
Inspect first, copy once, then fork into Workspace when you want variants, notes, and model settings attached to the same run.
Swap domain facts, examples, and any hard-coded entities for your own context.
Tighten the evidence or verification requirement if this is headed toward production.
Decide which failure mode you want to evaluate first before you branch the prompt.
This prompt already carries implementation detail, tool context, and a final-output instruction. Keep that structure intact when you tune it, or your comparison runs get noisy fast.
Open this prompt inside Workspace when you want a live iteration loop.
Copy for quick reuse, or run it in Workspace to keep prompt variants, model settings, and prompt-history changes in one place.
Structured source with 1 active lines to adapt.
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Prompt content
Original prompt text with formatting preserved for inspection and clean copy.
Test your LlamaIndex agent with a complex M&A due diligence query requiring both internal document lookup and simulated web search. For example: "Summarize Acme Corp's recent financial performance, identify their top 3 competitors based on market news, and list any recent legal issues." Demonstrate how the agent breaks down the query, uses its tools, and synthesizes a comprehensive answer, ensuring accurate source attribution and high confidence scores from Gemini 2.5 Pro.
Adaptation plan
Keep the source stable, then branch your edits in a predictable order so the next prompt run is easier to evaluate.
Preserve the rubric, target behavior, and pass-fail criteria as the baseline for evaluation.
Adjust fixtures, mocks, and thresholds to the system under test instead of weakening the assertions.
Make sure the prompt catches regressions instead of just mirroring the happy-path examples.
Copy once for a pristine source snapshot, then move the prompt into Workspace when you want variants, run history, and side-by-side tuning without losing the original.
Prompt diagnostics
Quick signals for how structured this prompt already is and where adaptation work is likely to happen first.
This prompt is mostly narrative and instruction-driven, so you can adapt examples and output constraints first without disturbing the structure.
Agent for Enterprise M&A Due Diligence
This challenge focuses on building an advanced RAG-powered agent using LlamaIndex for enterprise M&A due diligence, inspired by the news of cloud providers acquiring AI search companies to enhance agent capabilities. Participants will create an intelligent agent capable of querying internal and external knowledge bases to gather, synthesize, and analyze critical information pertinent to a potential acquisition target. The agent will need to handle diverse data types (documents, web pages, internal reports) and provide concise, actionable insights. The system should demonstrate sophisticated retrieval augmentation, dynamic tool selection, and the ability to answer complex, multi-hop questions about a target company's financials, market position, and technological landscape. This requires leveraging LlamaIndex's advanced indexing, query engine capabilities, and agent orchestration to ensure accurate and up-to-date information retrieval.
Use the challenge page to recover the original task boundaries before you tune the prompt. That keeps your variants grounded in the same evaluation target instead of drifting into a different problem.