Developer Builds Self-Grading AI Agent That Blocks Low-Quality Reports From Publishing

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A developer has replaced a manually reviewed AI workflow called ORACLE PRIME with an automated agent system built on Anthropic's Managed Agents platform that refuses to publish output until it meets a quality threshold. The upgraded system uses a separate grader model to score each weekly competitive intelligence briefing against an eight-criteria rubric, preventing the original model's completion bias from letting weak reports slip through. If the briefing scores too low, the writer agent retries up to three times using the grader's feedback before escalating to a human reviewer. The architecture separates the writing and grading into distinct context windows so the evaluator has no knowledge of the writer's intent, only the artifact and the rubric. The entire scan cycle, which pulls from over 40 sources and produces a structured 1,200–1,800 word report, costs $2.36 per run.

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