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.
Already linked to a challenge workflow.
Sign in to keep private prompt variations.
Prompt content
Original prompt text with formatting preserved for inspection and clean copy.
Define at least two distinct crypto financial anomaly patterns you expect your system to detect within a synthetic transaction dataset (e.g., 'Smurfing', 'Wash Trading', 'Ponzi Scheme Pattern'). For each, describe the graph characteristics and transaction properties that would indicate its presence.
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.
Crypto Financial Anomaly Detection
Build a cutting-edge agentic system using LangGraph to analyze complex crypto financial transaction networks. The system will leverage Gemini 2.5 Pro (specifically its 'Deep Think' mode for advanced reasoning) to identify unusual patterns, potential fraud, or hidden relationships within a simulated cryptocurrency transaction dataset. This challenge focuses on designing graph-based agent workflows, implementing hybrid reasoning, and exploring A2A protocol for secure, verifiable data exchange for compliance or audit purposes. Participants will create agents that can traverse transaction graphs, apply heuristic rules and LLM-powered reasoning to detect anomalies, and generate detailed explanations for flagged transactions. The system should demonstrate how graph-based state management can enhance financial oversight in a highly dynamic asset class.
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.