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.
Propose an Optuna-based strategy to optimize the prompt for the 'Compliance Assessor' agent. This agent takes a DMA/DSA article and a company's internal practice description. Optuna should tune prompt parameters (e.g., tone, specificity of instructions, few-shot examples) to improve the accuracy of compliance status identification (compliant/non-compliant/at-risk). Describe the objective function for Optuna.
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 already mixes executable detail with instructions, so the safest path is to tune examples and interfaces before you rewrite the overall scaffold.
EU DMA/DSA Policy Compliance Graph Agent
Create a graph-based multi-agent system using LangGraph and Claude Sonnet 4 to assist enterprises in navigating the complexities of EU Digital Markets Act (DMA) and Digital Services Act (DSA) compliance, given the intensified enforcement. This challenge requires building agents that can interpret intricate legal texts, assess company practices against regulations, and identify potential compliance gaps. The system will employ an A2A protocol for agents to communicate and collaborate on different aspects of regulatory analysis. MCP tool integration will provide agents with access to internal company policies, platform usage data, and legal databases. Optuna will be used to optimize prompt engineering and agent workflow parameters, ensuring the most accurate and efficient interpretation of legal documents. The final output will be a detailed compliance report and actionable recommendations for mitigating risks.
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.