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Design LangGraph Workflow for Neutrality Analysis
Inspect the original prompt language first, then copy or adapt it once you know how it fits your workflow.
Linked challenge: Neutrality Score for Bias Detection & Fact-Checking
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1
Sections
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Linked challenge
Neutrality Score for Bias Detection & Fact-Checking
Prompt source
Original prompt text with formatting preserved for inspection.
1 lines
1 sections
No variables
0 checklist items
Outline the full LangGraph DAG for your neutrality analysis system. Define the nodes (agents/functions) and edges (transitions) for processing a text. Consider nodes for initial text parsing, RAG-based context retrieval, bias detection, fact-checking, and final synthesis/revision suggestion. Clearly illustrate the state transitions and how the A2A protocol will be leveraged for specific cross-verification steps between fact-checking and bias detection.
Adaptation plan
Keep the source stable, then change the prompt in a predictable order so the next run is easier to evaluate.
Keep stable
Preserve the role framing, objective, and reporting structure so comparison runs stay coherent.
Tune next
Swap in your own domain constraints, anomaly thresholds, and examples before you branch variants.
Verify after
Check whether the prompt asks for the right evidence, confidence signal, and escalation path.