testing

Gentrace Integration for Evaluation

Inspect the original prompt language first, then copy or adapt it once you know how it fits your workflow.

Linked challenge: AI Policy Argument Generation Agent

Format

Code-aware

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Sections

Linked challenge

AI Policy Argument Generation Agent

Prompt source

Original prompt text with formatting preserved for inspection.

1 lines

1 sections

No variables

0 checklist items

Integrate Gentrace into your agent workflow. After an argument is generated, log the input prompt, the generated argument, and any intermediate steps from the Claude Agents SDK to Gentrace. Configure custom metrics in Gentrace (e.g., 'LogicalCoherence_Score', 'Persuasiveness_Rating') and implement a simple function to calculate these for initial evaluation. The goal is to track and improve the argument quality over iterations.

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 rubric, target behavior, and pass-fail criteria as the baseline for evaluation.

Tune next

Adjust fixtures, mocks, and thresholds to the system under test instead of weakening the assertions.

Verify after

Make sure the prompt catches regressions instead of just mirroring the happy-path examples.

Prompt diagnostics

Variables

Lists

Code blocks

Purpose

testing

This prompt already mixes executable detail with instructions, so tune examples and interfaces before rewriting the scaffold.

Linked challenge

AI Policy Argument Generation Agent

Develop an advanced AI agent system using the Claude Agents SDK to assist in complex policy negotiations, drawing inspiration from the SAG-AFTRA talks regarding an 'AI tax' on synthetic actors. This challenge requires building a system capable of analyzing diverse policy documents, legal texts, and economic data to generate well-reasoned arguments and counter-arguments for specific stakeholders, such as labor unions and production studios. The core of the solution will be a multi-agent workflow orchestrated by the Claude Agents SDK, leveraging Claude 3.5 Sonnet for its robust reasoning and document understanding capabilities. The agents will be tasked with identifying key points of contention, forecasting potential impacts of proposed policies, and synthesizing persuasive rhetoric. Evaluation of the generated arguments will be conducted using Gentrace, focusing on logical coherence, factual accuracy, and persuasive strength. The system will rely on Azure Blob Storage and Azure Cognitive Search for efficient storage and retrieval of relevant policy documents and background information.

Open challenge

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