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.
Run your complete LangGraph workflow from a user prompt through generation and moderation. Provide at least three distinct prompts, one of which is designed to intentionally violate a moderation rule. For each, submit the final generated content (or refined content after iteration) and the moderation report. Demonstrate how Guidance effectively prevented or flagged violations, and how iterative feedback improved compliant content.
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.
Craft Generative AI for User Generated Content
Inspired by vision to include generative AI-powered user-generated content (UGC), this challenge tasks participants with building a sophisticated multi-agent system for creating, moderating, and personalizing short-form multimodal content. The system will employ Claude Opus 4.1 for its advanced creative generation and nuanced ethical reasoning capabilities, ensuring content aligns with user defined brand safety and creative guidelines. LangGraph will be used to orchestrate a dynamic, graph-based workflow for content generation, review, and iteration. This will include agents specializing in ideation, multimodal asset generation (text-to-video/image), and a crucial moderation agent that applies 'Guidance' for constrained generation, ensuring content adheres to specific brand safety and thematic rules. The challenge emphasizes balancing creative freedom with strict content policy enforcement.
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.