Implement Gemini 2.5 Pro Creative Analysis

Prompt detail, context, and execution controls for real reuse instead of one-off copying.

implementationMulti-Agent Ad Fraud DetectionPublic prompt

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.

Best for

Implementation handoffs, eval setup, and prompt tuning where you need the original structure intact.

Reuse pattern

Inspect first, copy once, then fork into Workspace when you want variants, notes, and model settings attached to the same run.

Before first 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.

Operator lens

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.

Best practice: keep one pristine source version, then branch variants around evaluation criteria, evidence thresholds, and output format.
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Open this prompt inside Workspace when you want a live iteration loop.

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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.

Source prompt
1 active lines
1 sections
No variables
0 checklist items
Raw prompt
Formatting preserved for direct reuse
Implement the 'Creative Analyzer' agent using Gemini 2.5 Pro. This agent should take an ad creative (image URL and associated text) and generate an initial risk assessment for visual and textual cues of fraud (e.g., urgency, unrealistic claims, suspicious branding). Ensure it queries a RAG system for relevant historical fraud indicators.

Adaptation plan

Keep the source stable, then branch your edits in a predictable order so the next prompt run is easier to evaluate.

Keep stable

Hold the task contract and output shape stable so generated implementations remain comparable.

Tune next

Update libraries, interfaces, and environment assumptions to match the stack you actually run.

Verify after

Test failure handling, edge cases, and any code paths that depend on hidden context or secrets.

Safe workflow

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.

Sections
1
Variables
0
Lists
0
Code blocks
0
Reuse posture

This prompt is mostly narrative and instruction-driven, so you can adapt examples and output constraints first without disturbing the structure.

Linked challenge

Multi-Agent Ad Fraud Detection

This challenge tasks you with building a robust multi-agent system capable of proactively detecting, analyzing, and preventing fraudulent ad placements and scam campaigns within a simulated digital advertising platform. Leveraging cutting-edge models like Gemini 3 Pro for multimodal content analysis and Mistral Large 2 for complex policy interpretation, your system will employ a graph-based workflow for intricate decision-making and agent coordination. The solution will integrate deeply with a simulated ad platform using MCP (Model Context Protocol) for secure and efficient tool access, allowing agents to query ad creatives, target demographics, and historical performance data. Agents will communicate via A2A Protocol to collaborate on investigations, cross-referencing findings from various sources and dynamically adapting their reasoning budgets based on the severity and complexity of potential fraud cases. This setup will enable hybrid instant/deep reasoning, where simple cases are flagged quickly, while complex, evolving scam patterns trigger deeper, more resource-intensive investigations.

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Prompt origin
Why open it

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.

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